HS – Hydrological Sciences

HS1.1.1 – The MacGyver session for innovative and/or self made tools to observe the geosphere

EGU2020-8316 | Displays | HS1.1.1

How to circumvent the limitations of open source software and orthorectify how (or better) than with commercial software

Valerio Baiocchi, Roberta Onori, Felicia Monti, and Francesca Giannone

High and very high resolution satellite images are now an irreplaceable resource for earth observation in general and for the extraction of hydrogeological information in particular. In order to use them correctly and compare them with previous surveys and maps, they must be treated geometrically to remove the distortions introduced by the acquisition process. Orthorectification is not a simple georeferencing because the process must take into account the three-dimensional acquisition geometry of the sensor. For this reason orthorectification must be performed within specific commercial software with additional costs compared to image acquisition which, in some cases, is currently free of charge.
Some orthorectification algorithms, mainly based on the RPC approach, are available in open source GIS software such as QGIS. OTB (Orpheus toolbox) for QGIS contains some of these algorithms but its interfaces are not clear and there are some incomprehensible limitations such as the impossibility to input three-dimensional ground control points (GCPs). This severely limits the final achievable accuracy because it does not allow to correctly estimate the influence of different ground morphologies on the acquisition geometry. To get around these limitations you can make a "pseudo DEM" and other expedients to complete the whole process obtaining absolute results comparable if not better than those of commercial software.
The proposed procedure may not be the fastest but it can be a valid alternative for those who use satellite images as a tool in their research work.


How to cite: Baiocchi, V., Onori, R., Monti, F., and Giannone, F.: How to circumvent the limitations of open source software and orthorectify how (or better) than with commercial software, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8316,, 2020.

The conservation and long-term protection of our environment require a better understanding of ecosystems through cross-domain integration of data and knowledge from different disciplines. Current methods used in applied environmental research and scientific surveys are not sufficient to address the heterogeneity and dynamics of ecosystems appropriately. To this end, an urgent need is seen in introducing new technology and methods for a service-oriented and holistic in-situ monitoring with increased spatio-temporal resolution and cutting edge functionalities. Recent developments in the field of digital information processing, the internet of things (IoT) or the the analysis of complex datasets are opening up new possibilities for data-based environmental research. This rapidly developing fields are calling for a disruptive paradigm shift towards a service-oriented earth observation (smart monitoring). To this end, future earth observation approaches will have a much stronger coupling between the modeling and the data acquisition. The development, implementation and evaluation of such an interface is one of the overall objectives of this project. To achieve this goal, a basic data model and a special hardware architecture must be defined. A realistic application scenario will be used to demonstrate the advantages of developing a monitoring strategy that is no longer based on static data collection but on the coupling of modeling and empiricism using integrated sensors for an advanced modeling. Since current methods have so far failed to allow a holistic assessment of varying, large-scale environmental phenomena there is a corresponding need for capable hardware which is specialized for exactly this purpose.

The project aims to introduce an integrated sensor system for advanced modeling of turbidity and dissolved organic matter using miniaturized optical sensors in the ultraviolett and infrared range. Moreover, a data-driven, open-source architecture for service-oriented observation methods and in-stream process modeling close to real-time was developed. In addition to the hardware-related requirements of such a sensor system, the creation of an interface between the physical environment (sensor level) or abstracted model assumption (model level) is a particular focus of the research project. A sampling theorem, the predictive object specific exposure (POSE), is introduced as an underlying measurement paradigm and data model. This allows to consider not only the measured value in the evaluation but also accompanied parameters, which is called the context of a measurement. The development and provision of a first adaptive sensor concept resulted in promising prototype enabling the possibility to record environmental data depending on decision criteria such as location, time or context. Thus, the project is representing an interesting practical contribution to Digital Earth.

How to cite: Wagner, R. and Goblirsch, T.: A data-driven open-source architecture for service-oriented observation methods and in-stream process modeling of turbidity and dissolved organic matter, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21587,, 2020.

EGU2020-6102 | Displays | HS1.1.1

DIY approach to measuring surface water properties in the estuary

Vladimir Divić, Morena Galešić, Mariaines Di Dato, Marina Tavra, and Roko Andričević

The monitoring of water bodies, specifically complex ones such as estuaries, has been historically limited. Various research efforts were hindered due to the gaps in the technology implementation and accompanied by the price of developed solutions (usually as a black box for the end-user). However, thanks to the growing trend of open source solutions both in hardware and software domain, it has become more available to apply the DIY (do it yourself) approach and build the equipment that one might need. As all frugal innovations tend to emerge from a problem that had an existing commercial solution but was too demanding on resources, the floating measurement system presented in this study was designed to get surface water properties simultaneously in multiple points. Using multiple commercial probes to do such measurements was too expensive. Therefore, we have developed an innovative low-cost drifter based on the Arduino platform as an alternative. Our device is designed to measure position, temperature, and electrical conductivity in multiple drifter realisations or short-term moored measurements. The system consists of a floating container equipped with the following components: an Arduino Mega development board, a power management module, an SD card logging module, a Bluetooth module, a temperature measuring module, a global positioning satellite (GPS) position module, and a newly developed module for measuring electrical conductivity (EC). The applicability was tested at the estuary of River Jadro near Split (Croatia) and obtained spatial data (velocity, temperature, electrical conductivity and salinity) was analysed and compared with analytical models. All used tools are open-source and greatly supported by the worldwide community. Furthermore, we consider this prototype to be one of the first steps toward development of various DIY monitoring systems with a potential for a broader range of applications. We present our work with a purpose to initiate a dialogue with more collaborators interested in developing different variations of custom-built sensors for water properties.

How to cite: Divić, V., Galešić, M., Di Dato, M., Tavra, M., and Andričević, R.: DIY approach to measuring surface water properties in the estuary, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6102,, 2020.

EGU2020-20175 | Displays | HS1.1.1

Low Cost Sensor Node for Monitoring River Floods

Evangelos Skoubris and George Hloupis

River floods occupy a respectable percentage among all natural disasters, are presenting high risk, and usually cause great damage. Important tools in managing and preventing river floods are the Early Warning Systems (EWS), which are usually consisted both by a hardware infrastructure (sensors, communication network) and a relevant software infrastructure (data logging, signal processing, modeling, risk detection).

In the current work we are presenting preliminary results from a novel, low-cost and low-power hardware system, part of a EWS aimed for river floods. The system consists of multiple sensing nodes, each to be strategically positioned at certain points along the route of river Evros, Greece. Each sensing node will bear a low-cost and high-quality ultrasonic water level sensor, along with an embedded microcomputer to control its functionality. An additional novelty of the proposed work is the design and utilization of a private low-power wide-area wireless network (LPWAN), taking advantage of IoT technologies and especially the LoRaWAN implementation. This way, the proposed system will have even lower power demands, together with greater expandability by allowing many nodes to be simultaneously connected and measuring, and having the ability to utilize crowd-sensing techniques. The power supply is battery based and autonomously recharged with the aid of small solar panel. Each node will measure the water level of the river, and upload the data to a cloud server at variable time intervals, depending on the actual water level variation and the system’s power consumption optimization.

Future upgrades of the system will involve extra sensors, allowing the nodes to measure water quality parameters i.e. suspended solids, pH, etc. Although of secondary importance, these parameters might prove to be important in the development of the risk detection and alarm issuing algorithms.

How to cite: Skoubris, E. and Hloupis, G.: Low Cost Sensor Node for Monitoring River Floods, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20175,, 2020.

EGU2020-83 | Displays | HS1.1.1

Multipurpose IoT network watchdog device with capability of add on sensors for multi instrument field stations.

Panagiotis Argyrakis, Theodore Chinis, Alexandra Moshou, and Nikolaos Sagias

Several stations (seismological, geodetical, etc.) suffer from communications problems, such problems create data gaps in real-time data transmission, also excess humidity and temperatures further than manufacturer limits, usually make components and circuitry, of expensive instruments, failure, and results to unaffordable service or unrepairable damage.

We create a low-cost opensource device that will raise the reliability of the stations and secure the instruments from severe damage, such a device installed as prototype at UOA (University of Athens) seismological station KARY (Karistos Greece) for a year and the reliability of the station raised tremendously, since then the device upgraded to provide wireless connection and IoT GUI (mobile app). A local server was built to serve all the devices uninterrupted and provide a secured network.

The software is fully customizable and multiple inputs can provide addon sensors capability, for example, gas sensor, humidity sensor, etc., all the data are collected to a remote database for real-time visualization and archiving for further analysis.

The shell which covers the circuitry is 3D-printed with a high temperature and humidity-resistant material and it’s also fully customizable by the user. 

How to cite: Argyrakis, P., Chinis, T., Moshou, A., and Sagias, N.: Multipurpose IoT network watchdog device with capability of add on sensors for multi instrument field stations., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-83,, 2020.

The collective term ‘Internet of Things’ (IoT) encompasses a variety of technologies and methods providing novel opportunities for data acquisition and control in environmental sciences. Availability of cost effective components as well as support of large open source communities allow scientists to gain more flexibility and control over their experimental setups. However quality of measurements, stability of instruments as well as real costs for development and maintenance are often underestimated challenges. The presentation introduces current best practices of IoT principles in scientific applications. Examples of low cost sensors, low power electronics, wireless data transmission protocols, time series databases as well as real-time visualization are presented and discussed. Furthermore light is shed on non-technological issues of the ‘do-it-yourself’ or ‘maker’ approach such as social and psychological aspects. The ‘make-share-learn’ paradigm of the maker culture can be utilized to raise awareness. It provides significant opportunities for environmental education and community building which constantly gain more importance in the context of climate and environmental change.

How to cite: Becker, R.: ‘Internet of Things’ for environmental sciences and education, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19810,, 2020.

EGU2020-3032 | Displays | HS1.1.1

Microcontrollers beyond Arduino: a stationary and a mobile environmental monitoring system

Daniel Beiter, Tobias Vetter, Markus Morgner, Carlo Seehaus, Stephan Schröder, and Theresa Blume

In the course of the Helmholtz MOSES initiative two monitoring systems are being developed which consist of the same key components and thus functionality but with very different scopes of application. One is a stationary data logger with a classic measurement routine (on/off duty cycle) and support for various hardware interfaces (2xSDI12, 1xRS485, 2xUART, amongst others). The other is a drifting data logger that stays idle until a flood event activates the logger and carries it downstream. On-board are turbidity, EC and temperature sensors, a GPS and an inertial measurement unit (IMU) monitoring turbulence.

Advancements in electronics driven by automotive, mobile and IoT applications led to the development of very powerful, small and low power microcontrollers. This is why we decided to leave the realms of ATMega 8-bit systems (such as Arduino) and move towards ARM Cortex 32-bit systems. More precisely we used the Teensy 3.5 microcontroller development system as the core for the two systems. It is superior to Arduino in terms of performance while its developing team tries to maintain compatibility to Arduino in terms of programming vocabulary. This allows easier migration but comes also with restrictions regarding the capabilities of the hardware.
The other key component is the FiPy which supports five different wireless network types (WiFi, Bluetooth, LoRa, Sigfox, LTE-M) in one module. In comparison to most other hardware it runs MicroPython which adds more complexity to the project. Even though it is a microcontroller and features also several hardware interfaces, power consumption is far from low power, which is why it is used here only for remote communication and data transmission. In addition, several design decisions were made regarding power path routing and jumper configuration to improve the systems’ overall versatility, debugging capabilities and low power functionality, which are often key to the feasibility of a remote monitoring system.

How to cite: Beiter, D., Vetter, T., Morgner, M., Seehaus, C., Schröder, S., and Blume, T.: Microcontrollers beyond Arduino: a stationary and a mobile environmental monitoring system, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3032,, 2020.

EGU2020-18989 | Displays | HS1.1.1 | Highlight

A high capacity, automatic and small-volume water sampler

Núria Martínez-Carreras, François Barnich, Jean François Iffly, Oliver O'Nagy, and Andrei Popleteev

Field deployable and portable automatic water samplers are common tools in hydrology. They allow the unattended collection of water samples at predetermined times or triggered by external sensors, reducing personnel labour and costs. Several automated water samplers have been described in the literature. However, the vast majority of these samplers are not commercialised and their use is very limited or restricted to research applications. We can broadly classify these samplers in three groups: in situ samplers, sequential precipitation samplers and siphon automatic samplers. The latest are commonly used by hydrologists, environmental monitoring agencies and in wastewater treatment plants. They were first patented and commercialized in the 1980s by Teledyne-ISCO (Lincoln, NE, USA). They use a peristaltic pump to transfer water into several containers. However, the siphon automatic samplers are large, heavy and typically collect a maximum of 24 samples of 0.5 or 1 L. Here, we present a new automatic water sampler that has a larger and variable storage capacity (from 64 to 400) of smaller containers (from 2 to 40 mL). We argue that for many applications large sample volumes are no longer required due to the improvement of chemical analytic techniques. Standard laboratory storage boxes are filled with standard laboratory containers and directly placed inside the sampler, reducing the processing time once the samplers are back in the laboratory. Containers remain always closed with a septum cap to prevent evaporation. The sampler allows tub rinsing between sample collection to prevent contamination and memory effects. It is portable, has a low-power consumption and is robust for its use under field conditions. We tested the prototype in the laboratory and in the field. We will present the sampler mechanical functioning, the results of the tests (e.g. sample preservation and memory effects) and the user-friendly interface to define sampling schemes.

How to cite: Martínez-Carreras, N., Barnich, F., Iffly, J. F., O'Nagy, O., and Popleteev, A.: A high capacity, automatic and small-volume water sampler, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18989,, 2020.

EGU2020-13711 | Displays | HS1.1.1

Automated high resolution rain water sampler for stable water isotope monitoring

Christoff Andermann, Torsten Queißer, Markus Reich, Bijaya Puri, Niels Hovius, and Dirk Sachse

With global climate change, one of the largest short-term threats to our societies comes from changes in the hydro-meteorological cycle: droughts, flooding and potentially increasing extreme rain events may have far greater direct impact on humans than rising temperatures alone. These changes often have sever consequences and widespread impact on society and ecosystems, yet they are difficult to track, trace and measure in order to fully understand the underlying process of delivering moisture and recharging water reservoirs. Only through the comprehensive monitoring of precipitation waters in space and time can we improve our process understanding and better predict the direction and magnitude of future hydro-meteorological changes, in particular on regional spatial scales. However, no commercial automated sampling solution exists, which fulfills the quality criteria for sophisticated hydrochemical water analysis. Here, we present an advanced prototype automatic precipitation water sampler for stable water isotope analysis of precipitation. The device is designed to be highly autonomous and robust for campaign deployment in harsh remote areas and fulfills the high demands on sampling and storage for isotope analysis (i.e. sealing of samples from atmospheric influences, no contamination and preservation of the sample material). The sampling device is portable, has low power consumption and a real-time adaptable sampling protocol strategy, and can be maintained at distance without any need to visit the location. Furthermore, the obtained water samples are not restricted to isotope analysis but can be used for any type of environmental water analysis. The current configuration can obtain 165 discrete rainwater samples with a minimum timely resolution of 5min or volume wise 2mm of rainfall. Our lab tests with dyed waters and waters with strongly differing isotopic signature demonstrate that the device can obtain, store and conserve samples without cross contamination over long periods of time. The device has been tested so far under several conditions, e.g. heavy summer thunderstorms with more than 50mm/24h of rainfall, sustained winter rainfall and in cold conditions involving melting of snow. This automated rainwater sampler provides an economic and sophisticated technological solution for monitoring moisture pathways and water transfer processes with the analytical quality of laboratory standard measurements on a new level of temporal and spatial resolution.

How to cite: Andermann, C., Queißer, T., Reich, M., Puri, B., Hovius, N., and Sachse, D.: Automated high resolution rain water sampler for stable water isotope monitoring , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13711,, 2020.

EGU2020-3141 | Displays | HS1.1.1 | Highlight

Developing an Autonomous Hovercraft for Benthic Surveying in Very Shallow Waters

Meghan Troup, David Barclay, and Matthew Hatcher

Benthic surveys in very shallow water (< 1 meter) are often carried out by remote sensing methods such as LiDAR, satellite imagery, and aerial photography, or by written observations paired with GPS point measurements and underwater video. Remote sensing can be helpful for large scale mapping endeavors, but the optical methods commonly used are limited in their effectiveness by cloud cover and water clarity. In situ surveys are often carried out manually and can therefore be quite inefficient. A proposed alternative method of small scale, high resolution mapping is an autonomous, amphibious hovercraft, fitted with high frequency single-beam and side-scan sonar instruments. A hovercraft can move seamlessly from land to water which allows for convenient and simple deployment. The sonar instruments are attached to a boat-shaped outrigger hull that can be raised and lowered automatically, enabling data collection in water as shallow as 10 cm. These data are used to extract seafloor characteristics in order to create detailed maps of the research area that include information such as sediment type, presence and extent of flora and fauna, and small-scale bathymetry.

How to cite: Troup, M., Barclay, D., and Hatcher, M.: Developing an Autonomous Hovercraft for Benthic Surveying in Very Shallow Waters, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3141,, 2020.

EGU2020-10190 * | Displays | HS1.1.1 | Highlight

Democratizing ocean technology: low-cost innovations in underwater robotics

Allison Chua, Aaron MacNeill, and Douglas Wallace

In comparison to the ocean’s immense volume and diversity of research areas, the number of sensors required to make the majority of desired measurements is quite small. This inequality of supply and demand elevates prices, adding further barriers for developing nations or fledgling research programs with smaller budgets attempting ocean science. Our work aims to demonstrate the potential of combining commercially available, open-source products to create inexpensive, configurable, and user-friendly platforms that can be adapted for underwater navigation and integration with most commercial oceanographic sensors.

Specifically, we will highlight modifications made to a Blue Robotics BlueROV2, which we have configured for various missions including vertical profiling of a coastal fjord and three-dimensional mapping of crude oil spills. The BlueROV2 offers an easily modified platform for physical mounting of sensors and streaming of sensor data via its onboard computer, a Raspberry Pi. Our custom circuit board is “sensor-agnostic”, powering sensors from a common source (the ROV battery) and using an Arduino that accepts analog or digital sensor inputs, allowing us to choose from a wide range of sensors. Physical modifications make use of inexpensive, readily available materials, and range from simple plastic brackets for small sensors to a skid for a sensor with half the ROV’s original weight, which utilizes pop bottles for buoyancy.

While products such as Pixhawk, Raspberry Pi, Arduino, and BlueROV have inspired hobbyists and youth around the world, they paradoxically have not been as widely embraced in the academic community, who perhaps remain unaware of their research potential. Thus, while there has yet to be an analogous push to develop inexpensive, small, power-efficient, and open-source sensors, these platforms offer exciting opportunities to build a new generation of oceanographic tools with measurement abilities far exceeding those of their predecessors. We are at an ocean technology tipping point, and, as MacGyver says, “With a little bit of imagination, anything is possible.”

How to cite: Chua, A., MacNeill, A., and Wallace, D.: Democratizing ocean technology: low-cost innovations in underwater robotics, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10190,, 2020.

EGU2020-4291 | Displays | HS1.1.1

Open-source surface watercraft for Riverscape mapping

James Dietrich, Mark Fonstad, and Aaron Zettler-Mann

Most river system analyses use either intensive, small-area surveys, or extensive, low-resolution surveys. Recent research trends have shown that both high-resolution and river-extent information are necessary to understand fundamental questions of river processes including patterns of critical habitat, sediment links, and river instability. As part of a larger NSF-funded research project, we have developed an open-source, boat-based mapping approach to measure river geometry, sediment size patterns, hydraulic habitats, and riverbank erosion patterns. The custom catamaran design we have developed integrates off-the-shelf, lower-cost sensors including high-resolution RTK/PPK GPS, inertial measurement (IMU), side-scan sonar, single-beam sonar, temperature, and a multi-camera array for 3D mapping above and below water. The design is meant to be “garage build friendly”, utilizing a minimum number of common tools and basic construction techniques. The sensor package will be user-friendly enough for non-expert use, allowing the boat to be deployed for citizen-science based data collection by loaning it to groups like watershed councils or volunteer conservation organizations. This will allow data to be collected over larger areas in less time than would be possible by “expert” researchers. The boat designs and software are developed as an open-source project and all hardware and software and will be made public as our testing and validation progress.

How to cite: Dietrich, J., Fonstad, M., and Zettler-Mann, A.: Open-source surface watercraft for Riverscape mapping, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4291,, 2020.

EGU2020-9114 | Displays | HS1.1.1

Drifting away from reality : A cheap way to get lagrangian measurements

Cristèle Chevalier and Guillaume Koenig

Beauty may sometimes lie in the eyes of the beholder, but in science it always lies in simplicity. We tested a very simple concept to get drifting platforms  that we could track and equip with sensors. We equipped an available floating device with a commercial GPS tracking system.  We tested this in several campaigns ( Italia, New-Caledonia, Tunisia and Guadeloupe) to study surface drifts. Later, we added chemical sensors to collect of lagrangian measurements. Here we present  the general setting of the drifter and the results of the first tests, which proved its efficiency and robustness despite its cheapness and its simplicity to use. We also discuss possibility of adding various kinds of sensors.

How to cite: Chevalier, C. and Koenig, G.: Drifting away from reality : A cheap way to get lagrangian measurements, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9114,, 2020.

EGU2020-8446 | Displays | HS1.1.1

Low-cost, high accuracy Global Navigation Satellite System positioning for understanding floods

Hessel Winsemius, Andreas Krietemeyer, Kirsten Van Dongen, Ivan Gayton, Frank Annor, Christiaan Tiberius, Marie-Claire Ten Veldhuis, Hubert Samboko, Rolf Hut, and Nick Van de Giesen

Detailed elevation is a prerequisite for many hydrological applications. To name a few, understanding of urban and rural flood hazard and risk; understanding floodplain geometries and conveyance; and monitoring morphological changes. The accuracy of traditional Global Navigation Satellite System (GNSS) chipsets in smart phones is typically in the order of several meters, too low to be useful for such applications. Structure from Motion photogrammetry methods or Light Detection and Ranging (LIDAR), may be used to establish 3D point clouds from drone photos or lidar instrumentation, but even these require very accurate Ground Control Point (GCP) observations for a satisfactory result. These can be acquired through specialised GNSS rover equipment, combined with a multi-frequency GNSS base station or base station network, providing a Real-Time (RTK) or Post-Processing Kinematics (PPK) solution. These techniques are too expensive and too difficult to maintain for use within low resource settings and are usually deployed by experts or specialised firms.

Here we investigate if accurate positioning (horizontal and vertical) can be acquired using a very recently released low-cost multi-constellation dual-frequency receiver (ublox ZED-F9P), connected with a simple antenna and a smart phone. The setup is remarkably small and easy to carry into the field. Using a geodetic (high-grade) GNSS antenna and receiver as base station, initial results over baselines in the order of a few km with the low-cost receiver revealed a positioning performance in the centimeter domain. Currently, we are testing the solution using a smart phone setup as base station within Dar es Salaam, to improve elevation mapping within the community mapping project “Ramani Huria”. We will also test the equipment for use in GCP observations within the ZAMSECUR project in Zambia and TWIGA project in Ghana. This new technology opens doors to affordable and robust observations of positions and elevation in low resource settings.

How to cite: Winsemius, H., Krietemeyer, A., Van Dongen, K., Gayton, I., Annor, F., Tiberius, C., Ten Veldhuis, M.-C., Samboko, H., Hut, R., and Van de Giesen, N.: Low-cost, high accuracy Global Navigation Satellite System positioning for understanding floods, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8446,, 2020.

For the understanding of the carbon cycle in terrestrial ecosystems as well as of plant stress responses to drought and hypoxia, the study of fine root dynamics plays an important role. However, the number of relevant studies is still limited, which may be due, among other things, to the high costs of commercial minirhizotron systems. Here, we present an affordable (<500 €) and fully automated minirhizotron system, utilizing new developments in low-cost electronics and 3D-printing. The camera system is based on a Raspberry Pi and can be controlled by the user via a Python-based GUI. The open source character of the program also allows it to be adapted to the needs of the user or other requirements. The camera is controlled automatically by a stepper motor, which allows the precise recording of images at defined depths. The highest possible resolution is 3280 x 2464 pixels (8 MP) for an image area of about 2.5 cm x 2.5 cm, thus allowing the imaging of even root hairs and fungal hyphae. The structural components were manufactured using 3D printing. To protect against moisture, the camera and drive system are installed in a waterproof acrylic tube (60 mm diameter), which in turn is inserted into the rhizotron tubes (70 mm diameter) used in the field, making it possible to use the system in humid ecosystems.

How to cite: Thomsen, S. and Jensen, K.: An affordable, fully-automated minirhizotron system for observing fine-root dynamics, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22448,, 2020.

EGU2020-5584 | Displays | HS1.1.1

Tiny diameter downhole pressure monitoring

Bernd Wiese, Wolfgang Weinzierl, Peter Pilz, Tobias Raab, and Cornelia Schmidt-Hattenberger

Cheap and efficient groundwater pressure monitoring is a standard task in subsurface hydrology. We present application experience from a tube based pressure monitoring system that is applied to the Svelvik field laboratory for CO2  storage, Norway. In total 13 monitoring points were installed in depths between 51 and 89 m below ground level.

The pressure sensor is located above ground. It is temperature compensated to reduce measurement errors due to temperature variations. The pressure sensor is connected to a downhole low diameter tube that has a perforation in the respective measurement depth. The tubes are installed as smart casing installations, i.e. in the borehole annulus. This allows to keep the borehole open during installation of other monitoring devices.

Clean pumping of the well was not possible. Some filters were protected with fleece, while others were just perforated tubes. During installation, all tubes had hydraulic contact to the groundwater. After settling of the mud 3 of 4 fleece protected filters show sufficient communication, while all 9 filters that were just perforated were clogged and not usable for pressure monitoring.

The system has following advantages: (i) the downhole material is robust and cheap, allowing for multiple measurement points; (ii) has a small diameter (6 mm in the present case); (iii) since the static pressure is removed, a smaller sensor range is required; (iv) the sensors are located at the top of the borehole and can be retrieved after the campaign. Further, it can be installed without downhole metal parts.

The system has two disadvantages by design compared to submerged pressure sensors. (i) The absolute pressure can only be approximately determined, limited by the accuracy of the fluid density inside the tube. (ii) Pressure decreases can only be measured up to about 1 bar below piezometric head when the tube is filled with water.

The upper metres, that may be exposed to temperatures below 0 °C are filled with antifreeze. The choice of antifreeze allows for a certain static pressure correction. Minimum weight liquid is pure ethanol with a density of about 0.8 kg, allowing to measure pressure up to 2.8 bars below piezometric head for e.g. the 89 m deep measurement.


This work has been produced with support from the SINTEF-coordinated Pre-ACT project (Project No. 271497) funded by RCN (Norway), Gassnova (Norway), BEIS (UK), RVO (Netherlands), and BMWi (Ger-many) and co-funded by the European Commission under the Horizon 2020 programme, ACT Grant Agreement No 691712. We also acknowledge the industry partners for their contributions: Total, Equinor, Shell, TAQA. We thank the SINTEF-owned Svelvik CO2 Field Lab (funded by ECCSEL through RCN, with additional support from Pre-ACT and SINTEF) for assistance during installation and for financial support.

How to cite: Wiese, B., Weinzierl, W., Pilz, P., Raab, T., and Schmidt-Hattenberger, C.: Tiny diameter downhole pressure monitoring , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5584,, 2020.

EGU2020-5819 | Displays | HS1.1.1

Application of a low-cost NDIR sensor module for measurements of in situ soil CO2 concentration

Adrian Heger, Volker Kleinschmidt, Alexander Gröngröft, Lars Kutzbach, and Annette Eschenbach

We applied the low-cost non-dispersive infrared sensor module K33 (ICB, Senseair, Sweden) for measurements of soil CO2 concentration. We integrated the sensor module in a new soil probe suitable for in situ measurements of soil gas CO2 concentration. Therefore, we covered the sensor module with epoxy resin. For continuous measurements, we connected our soil CO2 probe to a microcontroller (MEGA 2560 Rev3,, Italy) equipped with a data logging shield (Adalogger FeatherWing, Adafruit, USA). In a laboratory experiment, we evaluated the accuracy and precision of our soil CO2 probe at changing temperature and humidity by comparison with the often used CO2 probe GMP343 (Vaisala, Finland) as a reference. In a field experiment, we buried our soil CO2 probe to test its performance under natural environmental conditions.

The result of the laboratory experiment is that our soil CO2 probe compares well with the GMP343, even at maximum relative humidity. The accuracy (<0.1 % CO2) was below the accuracy given by the manufacturer. The field experiment demonstrated that our soil CO2 probe provides high-quality measurements of soil CO2 concentrations under in situ soil conditions. After retrieving it, it still measured with the same accuracy and precision as before.

In summary, we used the sensor module K33 for the first time to measure in situ soil CO2 concentrations by integrating it into a newly developed probe. The cost-efficient availability of our CO2 probe opens up the opportunity to carry out continuous soil CO2 measurements over long time periods with simultaneously high spatial resolution.

How to cite: Heger, A., Kleinschmidt, V., Gröngröft, A., Kutzbach, L., and Eschenbach, A.: Application of a low-cost NDIR sensor module for measurements of in situ soil CO2 concentration, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5819,, 2020.

EGU2020-10966 | Displays | HS1.1.1 | Highlight

MEMS Accelerometers Mini-Array (MAMA) - initial results and lessons learned

Ran N. Nof, Angela I. Chung, Horst Rademacher, and Richard M. Allen

Most operational earthquake early warning systems (EEWS) consider earthquakes to be point-sources and have difficulty providing imminent and robust source locations and magnitudes, especially at the edge of the seismic network or where seismic stations are sparse. Mini-arrays have the potential to estimate reliable hypocentral locations by beam forming (FK-analysis) techniques. They can also characterize the rupture dimensions and account for finite-source effects, leading to more reliable estimates of ground motions for large magnitude earthquakes. In the past, the high price of multiple seismometers has made creating arrays cost- prohibitive. Here, we present a setup of two mini-arrays of a new low-cost (<$150) seismic acquisition unit based on a high-performance MEMS accelerometer around conventional seismic stations. The expected benefits of such an approach include decreasing alert-times, improving real-time shaking predictions and mitigating false alarms.

We will present our new 24-bit device details, benchmarks, and results from two MAMAs deployed at the UC Berkeley and Humboldt State University campuses. The new device shows lower noise levels than the currently available off-the-shelf 16-bit sensors, commonly used by several citizen-science projects (e.g. QCN, CSN, MyShake, etc.). This lower noise level enables us to record and process lower magnitude events. We show examples of back-azimuth calculations of M>=2.5 events at a range of <100km from the MAMA center and discuss some of the limitations and considerations of the MAMA deployments.

How to cite: Nof, R. N., Chung, A. I., Rademacher, H., and Allen, R. M.: MEMS Accelerometers Mini-Array (MAMA) - initial results and lessons learned, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10966,, 2020.

The work sets out a method and evaluates the accuracy of a 3D printed turbine flow meter for open channel and pipe flow; that can be optimised for different situations.  The motivation for this project was to create flow meters that are low cost and available to community groups and interested individuals, this work was conducted as part of the CAMELLIA project (Community Water Management for a Liveable London).  The flowmeters have been trialled in a number of locations by users with different skill sets and technical know-how.  Hall effect sensors have been coupled with consumer grade electronics to develop the most opensource system possible.  This work has taken advantage of recent advances in DLP printing, allowing for greater resolution at a lower cost than previous generations of 3D printers.  This is combined with work developed by the Open Prop software team, has enabled user customisable sensors to be built.  

The presented work aims to create an opensource, low cost and easy to use solution to some flow monitoring problems.  This paper details the lessons learnt and successes of this approach; it aims to create a basis for which further development and deployment of these sensors can be achieved.  

How to cite: Butler, A., Rowan, T., and Colyer, A.: On the development of low cost, optimizable, 3D printed turbine flow meters for pipe and open channel applications, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21929,, 2020.

EGU2020-2953 | Displays | HS1.1.1

Night-Time Cooling of Surface Water: Laboratory experiment and numerical simulation

Nick van de Giesen, John Selker, Koen Hilgersom, and Anna Solcerova

In the framework of the Small Reservoirs Project (, evaporation in semi-arid areas from open water has been measured through water balances, floating evaporation pans, and eddy covariance measurements. Each method showed that the actual evaporation was 30%-50% less than the evaporation from open water as predicted by Penman. During daytime, this reduced evaporation may be due to the formation of a stable internal boundary layer over the reservoirs. One would expect that this evaporation reducing effect would at least partially be offset during the night when the warm water would induce strong turbulent transport through an unstable local boundary layer. Through detailed Distributed Temperature Sensing observation in ponds, lakes, and reservoirs in different parts of the world, it was observed that during cloudless nights with low wind speeds or no wind, the top layer (1cm-2cm) of the water was one to two degrees colder than the air immediately above it. Such a temperature difference would again set up a stable layer, hindering turbulent transport of heat and water vapor into the atmosphere. 


It was hypothesized that outward longwave radiation, which during cloudless nights can quickly reach 200 W/m2, would cause a thin layer of cold water on top of the warmer water body. Through conduction, this cold layer would grow until it would become unstable, at which point the surface would be (partially) refreshed through downward finger flow. Detailed numerical simulations of the heat transport in the water body were undertaken to test this hypothesis. The numerical results indeed showed the cooling of the top layer and formation of instabilities with characteristic length and time scales. To test these results and the general concept, a MacGyver-worthy laboratory set-up was built consisting of an insulated 20 liter bucket, covered by a double hemispheric dome of perspex. On the inside of the dome, a thermal camera was attached at the apex. The space between the inner and outer dome was filled with dry ice to create an inside surface temperature of about 230K. After the dry ice was added, surface cooling was observed, followed by the formation of zones with upwelling warm water and downwelling cold water. These circulation cells were comparable in size to the simulated ones. A detailed analysis of spatial and temporal scales of the laboratory and simulation results will be presented.

How to cite: van de Giesen, N., Selker, J., Hilgersom, K., and Solcerova, A.: Night-Time Cooling of Surface Water: Laboratory experiment and numerical simulation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2953,, 2020.

EGU2020-22195 | Displays | HS1.1.1

Novel methods for identifying and quantifying hyporheic exchange fluxes using Fibre Bragg Grating sensor arrays

John Arkwright, Eddie W Banks, Margaret Shanafield, and Anthony Papageorgiou

Most streambed heat tracer studies use vertical, ambient temperature profiles and a 1D analytical solution of the heat diffusion–advection equation to estimate hyporheic exchange fluxes (HEF). This approach has limited capacity in complex flow settings, which has led to the successful development of active heat pulse sensing to investigate the dynamic 3D flow fields in the near subsurface and to quantify HEF. At the scale of the hyporheic zone very small water level fluctuations drive changes in the hydraulic gradients across streambed bedform structures. Generally, hydraulic head gradients are measured with pressure sensors deployed in shallow monitoring wells, but such devices do not have the required vertical spatial resolution and precision to accurately evaluate these processes. New and novel research developed by the biomedical community for in-vivo medical devices can now be used in the geosciences field to measure temperature and pressure at a much higher spatial and temporal resolution to overcome these challenges. As part of this research we have developed a fibre optic, active heat pulse and pressure sensing instrument (formed from Fibre Bragg Grating sensor arrays) to determine small hydraulic gradients in the subsurface and to quantify the exchange fluxes. The instrument was tested in a controlled laboratory environment and in the field. Combining point-scale measurements from this novel instrument with near surface geophysical data and other hydrological observations (i.e. measurements with fibre optic distributed temperature sensing) can be used to upscale some of the key physical exchange processes to the stream reach and river scale.

How to cite: Arkwright, J., Banks, E. W., Shanafield, M., and Papageorgiou, A.: Novel methods for identifying and quantifying hyporheic exchange fluxes using Fibre Bragg Grating sensor arrays, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22195,, 2020.

Satellite data for West Africa still struggle with local climate and farming practices. Despite the increasing data frequency, the rainy season in West Africa features such a dense cloud cover that many satellites cannot provide cloud free images. In addition, many farmers practice intercropping, where a single plot can be used to grow different crops such as maize and beans or even feature trees. Although the spatial resolution of satellites is ever increasing, this very small-scale intercropping still poses challenges for satellite data analysis. Yet, spatial data on vegetation status and distribution is required for running crop models.

Within the EU project TWIGA we therefore developed a smartphone app that allows farmers to collect vegetation data where it matters – on their plot!

Based on field trial that started in August 2019 we present vegetation metrics derived from smartphone photos as well as auxiliary data collected by test users in Ghana. The vegetation metrics are further combined with Sentinel 2A NDVI timeseries and fill a cloud cover caused data gap during the peak growing season.

How to cite: Ahmed, S. and Friesen, J.: Farmers see where the satellite is blind – using citizen science to fill satellite-derived vegetation data gaps, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13145,, 2020.

HS1.1.3 – Innovative methods for non-invasive monitoring of hydrological processes from field to catchment scale

EGU2020-10728 | Displays | HS1.1.3

Scene Setting for the ESA HydroGNSS GNSS-Reflectometry Scout Mission

Martin Unwin, Nazzareno Pierdicca, Kimmo Rautiainen, Estel Cardellach, Giuseppe Foti, Paul Blunt, Michel Tossaint, and Elliott Worsley

HydroGNSS is a mission concept selected by ESA as a Scout candidate, and consists of a 40 kg satellite that addresses land hydrological parameters using the technique of GNSS Reflectometry, a form of bistatic L-Band radar using satnav signals as the radar source. The four targeted essential climate variables (ECVs) are of established importance to our understanding of the climate evolution and human interaction, and comprise of soil moisture, inundation / wetlands, freeze /thaw (notably over permafrost) and above ground biomass.

The technique of GNSS Reflectometry shows potential over all geophysical surfaces for low cost measurement of ocean winds, ocean roughness, soil moisture, flood & ice mapping, and other climate and operational parameters. SSTL developed and flew the SGR-ReSI GNSS remote sensing instrument on the 160 kg UK TechDemoSat-1 (TDS-1) in July 2014 and, with sponsorship from ESA, collected data until TDS-1’s drag-sail was deployed in May 2019. TDS-1 was a precursor for NASA’s CYGNSS mission which uses the SGR-ReSI on its 8-microsatellite constellation for sensing hurricanes. The datasets from TDS-1 have been released via the MERRByS website, and include ocean wind speed measurements and ice extent maps from National Oceanography Centre’s C-BRE inversion. At the same time, researchers recognised the benefits of GNSS reflectometry over land, including the unique capability to sense rivers under forest canopies to a high resolution.

HydroGNSS has been proposed for the ESA Scout mission opportunity by a SSTL and a team of partners with a broad range of experience in GNSS technology, GNSS-Reflectometry modelling and applications, and Earth Observation from GNSS-R measurements. The instrument takes significant steps forward from previous GNSS-R experiments by including capability in dual polarisation, dual frequency and coherent reflected signal reception, that are expected to help separate out ECVs and improve measurement resolution. The satellite platform is the 40 kg SSTL-Micro, which has improved attitude determination and a high data link to support the collection of copious quantities scientific data with a short time delay. HydroGNSS builds upon the growing GNSS-R knowledge gained from UK-DMC, TDS-1, and ORORO / DoT-1, and is anticipated to generate a new research data set in GNSS Earth Observation, specifically targeting land and hydrological applications.

State of the art satellites that target soil moisture such as ESA SMOS and NASA SMAP are highly valued by scientists and operational weather forecasters, but will be expensive to replace. As evidenced by TDS-1 and CYGNSS, HydroGNSS will be able to take GNSS-R measurements using GNSS signals as a radar source, reducing the size of the satellite platform required. The forward scatter L-band nature of the measurement means that they are complementary to other techniques, and HydroGNSS brings further new measurement types compared to TDS-1 and CYGNSS. The small size and low recurring cost of the HydroGNSS satellite design opens the door to a larger constellation that can further improve spatial and temporal global hydrological measurements to an unprecedented resolution, invaluable to the better understanding of our climate.

How to cite: Unwin, M., Pierdicca, N., Rautiainen, K., Cardellach, E., Foti, G., Blunt, P., Tossaint, M., and Worsley, E.: Scene Setting for the ESA HydroGNSS GNSS-Reflectometry Scout Mission, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10728,, 2020.

EGU2020-8285 | Displays | HS1.1.3

Monitoring intermittent streams with low-cost water-presence sensors

Francesca Zanetti, Nicola Durighetto, Filippo Vingiani, and Gianluca Botter

The study of intermittent and ephemeral streams is gaining more and more popularity, as the scientific community has acknowledged the fundamental impact of these streams on basic hydrological processes and important ecosystem services. Nevertheless, the understanding of the physical processes that drive this intermittency has been long hampered by the limited availability of empirical data. In fact, monitoring the event-based expansion and contraction of temporary streams through visual inspection is very demanding and time-consuming. To circumvent this limitation, several low-cost sensor designs for monitoring flow presence have been suggested in recent years. These sensor exploit either water temperature or electrical conductivity. However, these sensors are typically characterized by pointwise probes that water flows can easily dodge, particularly in streams with complex and unstable morphologies. Moreover, very few studies have been conducted that use networks of probes to monitor stream intermittency at the catchment-scale.

Here we present a field-application of an advanced version of the low-cost water presence sensor developed by Chapin et al., 2016. In particular, we tested a new probe design to continuously measure the electrical conductivity across a channel cross-section and, thus, infer the presence of water therein. More than 50 probes were installed to monitor the dynamics of several intermittent tributaries of a small headwater catchment in northern Italy during the summer and fall of 2019. This catchment encompasses a wide variety of stream types: mild and steep slopes, incised and flat geometries, rocky and vegetated riverbeds. The field application shows that the proposed probes are able to provide useful information about the temporary activation of ephemeral streams under a variety of environments and conditions. The reconstructed temporal dynamics of the stream network comply with the persistency maps previously derived based on visual inspection. This new sensor design enables the continuous-time monitoring of the activity of intermittent streams, providing easily interpretable data under diverse conditions. We conclude that low-cost water presence sensors provide a unique opportunity to expand the coverage of the available datasets about the dynamics of intermittent streams.

How to cite: Zanetti, F., Durighetto, N., Vingiani, F., and Botter, G.: Monitoring intermittent streams with low-cost water-presence sensors, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8285,, 2020.

EGU2020-11751 | Displays | HS1.1.3

Proximal remote sensing to quantify plot-scale overland flow connectivity

Chandra Prasad Ghimire, Val Snow, Stuart Bradley, and Laura Grundy

Irrigation of crops and grazed pastures can lead to harmful losses of nutrients via overland flow across the edge of the field. While good irrigation design can assist with avoiding overland flow, soil surface conditions can change rapidly and lead to surface flow even under well-designed irrigation systems. Therefore, real-time methods to detect emerging flow conditions, early enough to prevent substantial flow from the field during irrigation, is a potential mitigation option. But these methods require a prediction of the initiation of overland flow conditions in order to make the connection with real-time observations.

On a naturally-rough agricultural soil, triggering of overland flow is primarily related to the process of gradual filling of small (~50 mm across) depressions. As depressions fill, hydraulic connections are established with their neighbours and this eventually leads to sufficient connectivity that overland flow is initiated. The initiation of overland flow generally occurs at a critical value of connectivity (COF); the proportion of the soil surface that is connected via a water-filled pathway to an exit point of the field. As water ponding in, and flowing through, local depressions increases, the COF of the field increases and this leads to flow across the field boundaries. Quantifying the development of COF during an irrigation event, therefore, is key to predicting the initiation of overland flow.

We propose a method to continuously monitor the development of COF during an irrigation event that requires two elements. The first is a new proximal sensing technique, which exploits acoustic technology to continuously monitor Asw, the proportion of the soil surface covered in water. The acoustic method comprises directional acoustic transmitter and receiver arrays. The directionality of the arrays provides a well-defined footprint area on the ground beneath the instrument. The Asw can be reliably estimated from changes in the amplitude of reflected sound waves. The second element is a ponding and redistribution model which simulates the flow of water over a rough soil surface and assists by converting Asw into COF.

Our preliminary results show that this real-time method of monitoring COF has a considerable scope in a variety of environments where prediction of overland flow initiation is desirable.

How to cite: Ghimire, C. P., Snow, V., Bradley, S., and Grundy, L.: Proximal remote sensing to quantify plot-scale overland flow connectivity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11751,, 2020.

EGU2020-16516 | Displays | HS1.1.3

Large-scale alternative detection systems for CRNS

Markus Köhli, Jannis Weimar, and Ulrich Schmidt

Cosmic-Ray neutron (CRN) sensors are widely used to determine soil moisture on the hectar scale. Precise measurements, especially in the case of mobile application, demand for neutron detectors with high counting rates and high signal-to-noise ratios. For a long time CRNS instruments have relied on helium-3 as an efficient neutron converter. Its ongoing scarcity demands for technological solutions using alternative converters, which are lithium-6 and boron-10. In order to scale up the method and to reduce costs we recently have developed large-scale neutron detectors including readout electronics and data acquisition systems based on Arduino microcontrollers. These boron-lined detectors shall offer an alternative platform to current Helium-3 based systems and allow for modular instrument designs. Individual shieldings of different segments within the detector introduces the capability of gaining spectral information. This opens the possibility for active signal correction during mobile measurements, where the influence of the constantly changing near-field to the overall signal should be corrected. Furthermore, the signal-to-noise ratio could be increased by combining pulse-height and pulse-length spectra to discriminate between neutrons and other environmental radiation. This novel detector therefore combines high-selective counting electronics with large-scale instrumentation technology. The successful implementation of our design allowed also to build the largest up to now existing CRNS detector. 

How to cite: Köhli, M., Weimar, J., and Schmidt, U.: Large-scale alternative detection systems for CRNS, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16516,, 2020.

EGU2020-11180 | Displays | HS1.1.3

Local high-energy particles measurements for detecting primary cosmic-ray variations: application for soil moisture estimation

Luca Stevanato, Gabriele Baroni, Cristiano Fontana, Marcello Lunardon, Sandra Moretto, and Paul Schattan

In the last decade the measurement of secondary cosmic ray neutrons has been established as a unique approach for intermediate scale observation of land surface hydrogen pools. Originally developed for soil moisture measurements, it has shown also promising applications for snow, biomass and canopy interception. The approach relies on the correlation between natural neutron background as created by cosmic-ray fluxes and local hydrogen pools. Due to the specific capabilities of the neutrons to move in air, the signal detected by the sensor installed above-ground is sensitive to an area of hundreds of meters providing a new perspective for proximal land-surface observations. The measurements are generally performed based on moderated proportional counters filled with Helium-3 or Boron and the moderation is created by adding shielding material (mostly polyethylene) around the counter.

The signal is affected by the temporal variability of the incoming neutron fluxes. At first, the variability of neutron fluxes is due to solar activities. The neutrons are further attenuated by the mass of the air and air humidity.

Specific corrections have been proposed to account for these effects. Air pressure and humidity corrections rely on local measurements that could be easily collected. Incoming correction due to solar cosmic-ray fluctuation is based on a worldwide network monitoring station (NMDB). This network provides online access to their data in real-time. However, this approach showed some limitations in region where incoming fluxes could be not representative of local conditions introducing errors that could be relevant for the estimation of the targeted variable. In addition, it requires the need of post-processing of the data resulting in some difficulties to provide, e.g., soil moisture observations in real-time.

In the present contribution, we show the results of tests conducted on an alternative commercial sensor based on scintillators. The new probe has the capability to identify different neutron energies ranges and gamma-rays providing new opportunities for hydrological observations at different spatial scales. In addition, the probe is sensitive to high energy particles that can be used for correcting the neutron signal by the variations of primary cosmic-ray flux. We present results from the comparison of the new probe with standard proportional counters and neutron monitor database in a long-term outdoor case study. We show how the use of local high energy particles is a practical alternative to account atmospheric corrections and overcome the limitation of using data from NMDB.

How to cite: Stevanato, L., Baroni, G., Fontana, C., Lunardon, M., Moretto, S., and Schattan, P.: Local high-energy particles measurements for detecting primary cosmic-ray variations: application for soil moisture estimation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11180,, 2020.

EGU2020-17856 | Displays | HS1.1.3

Moisture and humidity dependence of the above-ground cosmic-ray neutron intensity

Jannis Weimar, Markus Köhli, Martin Schrön, and Ulrich Schmidt

The novel method of Cosmic-ray neutron sensing (CRNS) allows non-invasive soil moisture measurements at a hectometer scaled footprint. Using this technique one can relate the flux density of albedo neutrons, generated in cosmic-ray induced air showers, to the amount of water within a radius of several hundred meters. In the recent years the understanding of neutron transport by Monte Carlo simulations led to major advancements in precision, which have successfully targeted a manifold of use cases. For example the improvements in the signal interpretation have meanwhile also been applied to the determination of snow water in Alpine regions. Up to now, the conversion of soil moisture to a detectable neutron count rate relies mainly on the equation presented by Desilets and Zreda. While in general a hyperbolic expression can be derived from theoretical considerations, their empiric parameterisation needs to be revised as many groups have found site-specific calibrations, which are simply based on different empirical data sets.

Investigating the above-ground neutron intensity by a broadly based Monte Carlo simulation campaign revealed a more detailed understanding of different contributions to this signal, especially targeting air humidity corrections. The packages MCNP and URANOS were used to derive a function able to describe the respective dependencies including the effect of different hydrogen pools and the sensor response function. The resulting formula significantly improves the soil-moisture-to-intensity conversion and allows for a more comprehensive instrument data quality, which especially closes the gap between observations of very dry and wet conditions.

How to cite: Weimar, J., Köhli, M., Schrön, M., and Schmidt, U.: Moisture and humidity dependence of the above-ground cosmic-ray neutron intensity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17856,, 2020.

A Critical Zone Observatory (CZO) was recently established in the Alento River Catchment (ARC; southern Italy) within the TERENO (TERrestrial ENvironmental Observatories) long-term ecosystem infrastructure network. In 2016 SoilNet wireless sensor networks and cosmic ray neutron probes (CRNP) were installed in the upper part of this catchment and specifically in two experimental sub-catchments (MFC2 and GOR1) characterized by different topographic, pedological, land-use, and weather conditions. The Soilnet end-devices are monitoring soil moisture and matric potential at two different soil depths (15 cm and 30 cm) in 20 locations around the cosmic ray neutron probe. We evaluated the the relationship between Soil Moisture Index (SMI) and rainfall deficits (considered as rainfall minus potential evapotranspiration) at monthly time scale. The cropland site on the south-facing hillslope of ARC is characterized by more extreme dry and wet conditions. Another goal is to identify the dominant controls that most govern the spatial soil moisture patterns in these two different sites. The relationship between the CRNP-based soil moisture and spatial variability of SoilNet-based soil moisture is nearly linear in the case of the cropland site (MFC2) but follows a fairly concave curve in the case of the forestland site (GOR1). The majority of the spatial variance in MFC2 is explained by terrain attributes, i.e. slope-induced during wet conditions and aspect-induced during dry conditions. In GOR1 the spatial variance of soil moisture data is mostly explained by topographic factors under wet conditions during the rainy season. In both sites the soil texture is able to explain only less than 10% of spatial variability of soil moisture data.

How to cite: Nasta, P., Bogena, H., Sica, B., Vereecken, H., and Romano, N.: Understanding the spatio-temporal variability of soil moisture by integrating cosmic-ray neutron probes with SoilNet wireless sensor netwoks under a seasonal Mediterranean-climate regime, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5295,, 2020.

EGU2020-4093 | Displays | HS1.1.3

Development of irrigation management services based on integration of innovative soil moisture monitoring and hydrological modelling

Vassilios Pisinaras, Cosimo Brogi, Heye Bogena, Harrie-Jan Hendricks-Franssen, Olga Dombrowski, and Andreas Panagopoulos

The H2020 ATLAS project ( aims to develop an open, flexible and distributed platform that will provide services for the agricultural sector based on the seamless interconnection of sensors and machines. Two interconnected services that will be included in the platform are the soil moisture monitoring and the irrigation management services. The soil moisture monitoring service will integrate both invasive (wireless sensor network (SoilNet)) and non-invasive soil moisture monitoring methods (cosmic-ray neutron sensors (CRNS)). Ultimately, a model will be developed that combines SoilNet and CRNS measurements to predict soil moisture time series. Soil water potential sensors will be incorporated as well.

Data provided by the above described service will be incorporated in an irrigation management service which will be based on hydrological modelling. The fully distributed, deterministic Community Land Model (CLM, version 5) will be applied which incorporates physically-based simulation of soil water balance and crop growth. Two different levels of application will be considered, namely the farm and watershed scale, which will be combined to weather forecast in order to provide irrigation scheduling advice. The farm scale application will take advantage of soil moisture monitoring data and provide farm specific irrigation scheduling, while the watershed scale application will provide a more generic irrigation advice based on the average cultivation practices. Furthermore, the CLM model will be coupled to a groundwater flow model in order to connect irrigation to groundwater availability. By doing so, it will be possible to support the efficient and sustainable groundwater management as well as competent water uses in an area that suffers from water scarcity.

These services will be implemented in the area of Pinios Hydrologic Observatory, located in central Greece. Three pilot orchards will be established introducing different soil moisture monitoring setups, while the boundaries of the Observatory will be used for the pilot implementation of irrigation management service on the watershed scale. Furthermore, two pilot vineyards located in northern Greece will be established in order to further test the services functionality on the farm scale.

How to cite: Pisinaras, V., Brogi, C., Bogena, H., Hendricks-Franssen, H.-J., Dombrowski, O., and Panagopoulos, A.: Development of irrigation management services based on integration of innovative soil moisture monitoring and hydrological modelling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4093,, 2020.

EGU2020-4618 | Displays | HS1.1.3

Field scale root zone soil moisture estimation by coupling cosmic-ray neutron sensor with soil moisture sensors

Hami Said, Georg Weltin, Lee Kheng Heng, Trenton Franz, Emil Fulajtar, and Gerd Dercon

Since it has become clear that climate change is having a major impact on water availability for agriculture and crop productivity, an accurate estimation of field-scale root-zone soil moisture (RZSM) is essential for improved agricultural water management. The Cosmic Ray Neutron Sensor (CRNS) has recently been used for field-scale soil moisture (SM) monitoring in large areas and is a credible and robust technique. Like other remote or proximal sensing techniques, the CRNS provides only SM data in the near surface. One of the challenges and needs is to extend the vertical footprint of the CRNS to the root zone of major crops. This can be achieved by coupling the CRNS measurements with conventional methods for soil moisture measurements, which provide information on soil moisture for whole rooting depth.

The objective of this poster presentation is to estimate field-scale RZSM by correlating the CRNS information with that from soil moisture sensors that provide soil moisture data for the whole root depth. In this study, the Drill and Drop probes which provide continuous profile soil moisture were selected. The RZSM estimate was calculated using an exponential filter approach.

Winter Wheat cropped fields in Rutzendorf, Marchfeld region (Austria) were instrumented with a CRNS and Drill & Drop probes. An exponential filter approach was applied on the CRNS and Drill and drop sensor data to characterize the RZSM. The preliminary results indicate the ability of the merging framework procedure to improve field-scale RZSM in real-time. This study demonstrated how to combine the advantages of CRNS nuclear technique (especially the large footprint and good representativeness of obtained data) with the advantages of conventional methods (providing data for whole soil profile) and overcome the shortcoming of both methods (the lack of information in the deeper part of soil profile being the major disadvantage of CRNS and the spatial limitation and low representativeness of point data being the major disadvantage of conventional capacitance sensors). This approach can be very helpful for improving agricultural water management.

How to cite: Said, H., Weltin, G., Heng, L. K., Franz, T., Fulajtar, E., and Dercon, G.: Field scale root zone soil moisture estimation by coupling cosmic-ray neutron sensor with soil moisture sensors, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4618,, 2020.

EGU2020-7668 | Displays | HS1.1.3

Long-term soil moisture observations using cosmic-ray neutron sensing in Austria

Emil Fulajtar, Hami Said Ahmed, Ammar Wahbi, Gabriele Baroni, Rafael Rosolem, Daniel Power, Trenton Franz, and Lee Kheng Heng

This study presents the results of soil moisture investigation carried by the Joint FAO/IAEA Division using Cosmic-Ray Neutron Sensor (CRNS). The measurements have been collected at several studied sites in Austria. The Petzenkirchen study which is within the Austrian Institute for Land and Water Management Research employing stationary CRNS has been established in Dec. 2013 and it provides major dataset for this study. It represents small watershed in hilly area of northern footslopes of Alps. Apart of that the short-term measurement campaigns were carried out using back-pack CRNS in alluvial plain east of Neusiedler See and in mountainous areas of Rauris Municipality in central part of Austrian Alps.

This study describes the results and interpretation of about 7 years of soil moisture data set (2013-2020). The analysis focused on improving the calibration approaches, CRNS footprint, heterogeneity soil moisture mapping, impacts of biomass and altitude on neutron counts. Further, the use of CRNS data for calibrating soil moisture calculated by soil water balance model was tested. The overall application is aimed at supporting agricultural water management and in developing methodology for soil moisture monitoring for water management in agriculture (under rainfed agriculture as well as for irrigation scheduling). This unique data-set can also provide additional information for hydrological modelling and remote sensing applications (at regional and global scales), as well as for extreme weather events (drought and flood) management and forecasting.

How to cite: Fulajtar, E., Said Ahmed, H., Wahbi, A., Baroni, G., Rosolem, R., Power, D., Franz, T., and Kheng Heng, L.: Long-term soil moisture observations using cosmic-ray neutron sensing in Austria, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7668,, 2020.

EGU2020-8488 | Displays | HS1.1.3

Error estimation for soil moisture measurements with cosmic-ray neutron sensing and implications for rover surveys

Jannis Jakobi, Johan Alexander Huisman, Martin Schrön, Justus Fiedler, Cosimo Brogi, Harry Vereecken, and Heye Bogena

The cosmic ray neutron (CRN) probe is a non-invasive device to measure soil moisture at the field scale. This instrument relies on the inverse correlation between aboveground epithermal neutron intensity (1eV – 100 keV) and environmental water content. The measurement uncertainty of the neutron detector follows Poisson statistics and thus decreases with decreasing neutron intensity, which corresponds to increasing soil moisture. In order to reduce measurement uncertainty (e.g. < 0.03 m3/m3), the neutron count rate is often aggregated over large time windows (e.g. 12h or 24h). To enable shorter aggregation intervals, the measurement uncertainty can be reduced either by using more efficient detectors or by using arrays of detectors, as in the case of CRN rover applications. Depending on soil moisture and driving speed, aggregation of neutron counts may also be necessary to obtain sufficiently accurate soil moisture estimates in rover applications. To date, signal aggregation has not been investigated sufficiently with respect to the optimisation of temporal (stationary probes) and spatial (roving applications) resolution. In this work, we present an easy-to-use method for uncertainty quantification of soil moisture observations from CRN sensors based on Gaussian error propagation theory. We have estimated the uncertainty using a third order Taylor expansion and compared the result with a more computationally intensive Monte Carlo approach and found excellent agreement. Furthermore, we used our method to quantify the dependence of soil moisture uncertainty on CRN rover survey design and on selected aggregation time. We anticipate that the new approach helps to quantify cosmic ray neutron measurement uncertainty. In particular, it is anticipated that the strategic planning and evaluation of CRN rover surveys based on uncertainty requirements can be improved considerably.

How to cite: Jakobi, J., Huisman, J. A., Schrön, M., Fiedler, J., Brogi, C., Vereecken, H., and Bogena, H.: Error estimation for soil moisture measurements with cosmic-ray neutron sensing and implications for rover surveys, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8488,, 2020.

EGU2020-8827 | Displays | HS1.1.3

Cosmic-ray neutron sensing based monitoring of snowpack dynamics: A comparison of four conversion methods

Heye Reemt Bogena, Frank Herrmann, Jannis Jakobi, Vassilios Pisinaras, Cosimo Brogi, Johan Alexander Huisman, and Andreas Panagopoulos

Snow monitoring instruments like snow pillows are influenced by disturbances such as energy transport into the snowpack, influences from wind fields or varying snow properties within the snowpack (e.g. ice layers). The intensity of epithermal neutrons that are produced in the soil by cosmic radiation and measured above the ground surface is sensitive to soil moisture in the upper decimetres of the ground within a radius of hectometres. Recently, it has been shown that aboveground cosmic ray neutron sensors (CRNS) are also a promising technique to monitor snow pack development thanks to the larger support that they provide and to the lower need for maintenance compared to conventional sensor systems. The basic principle is that snow water moderates neutron intensity in the footprint of the CRNS probe. The epithermal neutrons originating from the soil become increasingly attenuated with increasing depth of the snow cover, so that the neutron intensity measured by the CRN probe above the snow cover is directly related to the snow water equivalent.

In this paper, we use long-term CRNS measurements in the Pinios Hydrologic Observatory, Greece, to test different methods for the conversion from neutron count rates to snow pack characteristics, namely: i) linear regression, ii) the standard N0-calibration function, iii) a physically-based calibration approach and iv) the thermal to epithermal neutron ratio. The latter was also tested for its reliability in determining the start and end of snowpack development, respectively. The CRNS-derived snow pack dynamics are compared with snow depth measurements by a sonic sensor located near the CRNS probe. In the presentation, we will discuss the accuracy of the four conversion methods and provide recommendations for the application of CRNS-based snow pack measurements.

How to cite: Bogena, H. R., Herrmann, F., Jakobi, J., Pisinaras, V., Brogi, C., Huisman, J. A., and Panagopoulos, A.: Cosmic-ray neutron sensing based monitoring of snowpack dynamics: A comparison of four conversion methods, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8827,, 2020.

EGU2020-22317 | Displays | HS1.1.3

Monitoring and Mapping of Soil and Snow Water Across Scales with Cosmic-Ray Neutron Sensor Networks and Mobile Platforms

Martin Schrön, Sascha E Oswald, Steffen Zacharias, Peter Dietrich, and Sabine Attinger

Cosmic-ray neutron albedo sensing (CRNS) is a modern technology that can be used to non-invasively measure the average water content in the environment (i.e., in soil, snow, or vegetation). The sensor footprint encompasses an area of 10-15 hectares and extends tens of decimeters deep into the soil. This method might have the potential to bridge the scale gap between conventional in-situ sensors and remote-sensing data in both, the horizontal and the vertical domain.

Currently, more than 200 sensors are operated in the growing networks of national and continental observatories. While single CRNS stations are continuously monitoring the local water dynamics at fixed field sites, mobile CRNS platforms are used for on-demand soil moisture mapping at the regional scale. The sensors are rapidly operational on any ground- or airborne vehicle. The data is particularly useful to study hydrological extreme events, heatwaves, and snow melt/accumulation, and it is being applied in hydrological models and agricultural irrigation management.

In the presentation we will explore the potential of the CRNS method to support and complement in-situ and remote-sensing data for hydrological event monitoring. We will discuss ongoing research activities that are aimed at improving the operationality, frequency, and spatial extend of CRNS measurements. New measurement strategies that are currently explored are, for example: dense clusters of 20 CRNS stations fully covering a 100 hectare catchment; heat wave monitoring with mobile car-based CRNS; regular soil/snow water mapping using mobile CRNS on cars and trains; and airborne surveys using CRNS on gyrocopters.

Future CRNS observations could provide a valuable contribution to the multi-sensor approach, e.g. to help tracking and characterizing surface water movement, to map regional-scale soil moisture patterns, or to calibrate and evaluate satellite data.

How to cite: Schrön, M., Oswald, S. E., Zacharias, S., Dietrich, P., and Attinger, S.: Monitoring and Mapping of Soil and Snow Water Across Scales with Cosmic-Ray Neutron Sensor Networks and Mobile Platforms, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22317,, 2020.

EGU2020-18563 | Displays | HS1.1.3

Dynamic groundwater recharge rates at field scale: how to successfully use soil moisture from cosmic-ray neutron sensing

Lena M. Scheiffele, Matthias Munz, Gabriele Baroni, Sonja Bauer, and Sascha E. Oswald

Cosmic-ray neutron sensing (CRNS) is a non-invasive method that provides an average soil moisture for a large support volume (radial footprint up to 240 m, depth up to 80 cm) with high temporal resolution. It covers the most dynamic part of the vadose zone at a scale that is already a more substantial part of the landscape then local point measurements. This integral soil moisture value overcomes the limitations regarding issues of small-scale heterogeneity. Therefore, the use of CRNS soil moisture could improve the estimation of potential groundwater (GW) recharge at the field.

Besides the stochastic integration of point-scale soil moisture profiles, CRNS soil moisture estimates could be used for the inverse estimation of effective soil hydraulic properties by applying unsaturated soil hydrological models and to determine environmental fluxes such as GW recharge.

Within this study CRNS soil moisture is used to estimate the effective soil hydraulic properties within the model HYDRUS 1D. Resulting GW recharge represents the field scale because of the integrated nature of the soil moisture product, even though the model is calculating percolation fluxes for 1D - profiles. These integrated GW recharge fluxes are compared to established point scale methods of GW estimation using soil moisture from a distributed sensor network to inversely estimate the effective soil hydraulic properties within HYDRUS 1D.

CRNS is, however, sensitive to the vertical distribution of water content and this behavior should be explicitly considered. Two approaches are assessed further to account for that. On the one hand, a correction of CRNS, based on measured soil moisture profiles, is tested and CRNS soil moisture is directly used for recharge calculation in HYDRUS. On the other hand, the COSMIC-Operator, as implemented within HYDRUS, is used for calibrating the model by directly comparing neutron count rates from simulated soil moisture. Both approaches are assessed with respect to their ability to estimate natural groundwater recharge rates.

How to cite: Scheiffele, L. M., Munz, M., Baroni, G., Bauer, S., and Oswald, S. E.: Dynamic groundwater recharge rates at field scale: how to successfully use soil moisture from cosmic-ray neutron sensing, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18563,, 2020.

EGU2020-9020 | Displays | HS1.1.3

Detection of subsurface water storage dynamics with combined gravity - vertical gravity gradient monitoring and hydrological simulation

Anne-Karin Cooke, Cédric Champollion, Pierre Vermeulen, Camille Janvier, Bruno Desruelle, Nicolas Le Moigne, and Sébastien Merlet

Time-lapse ground-based gravimetry is increasingly applied in subsurface hydrology, providing mass balance constraints on water storage dynamics. For a given water content change as e.g. after a precipitation event, the simplest assumption is that of a homogeneous, infinite slab (Bouguer plate) of water column causing the measurable increase in gravitational attraction. For heterogeneous subsurface environments such as karst aquifers at field scale this assumption may not always hold. The gravity signal is depth-integrated and non-unique, hence indistinguishable from a heterogeneous distribution without further information.

Exploiting the different spatial sensitivities of gravity and vertical gravity gradient (VGG) data can shed light on the following questions:


  • Is the subsurface water content within the gravimeter’s footprint likely to be homogeneous or showing small-scale heterogeneity?

  • If not, at which distance are these mass heterogeneities and how large are they?

  • Which monitoring set-ups (tripod heights, number of and distance between VGG measurement locations) are likely to detect mass heterogeneity of which spatial characteristics?

One year of monthly vertical gravity gradient surveys has been completed in the geodetic observatory in karstic environment on the Larzac plateau in southern France. We interpret the VGG observations obtained in this field study in the context of further available hydraulic and geophysical data and hydro-gravimetrical simulation. Finally, practical applications in view of detecting near-surface voids and reservoirs of different porosities as well as their storage capacity and seasonal dynamics are evaluated.

How to cite: Cooke, A.-K., Champollion, C., Vermeulen, P., Janvier, C., Desruelle, B., Le Moigne, N., and Merlet, S.: Detection of subsurface water storage dynamics with combined gravity - vertical gravity gradient monitoring and hydrological simulation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9020,, 2020.

EGU2020-9522 | Displays | HS1.1.3

Evaluation of NMR and other soil water content measurement methods at the point and field scale

Matteo Bauckholt, Marco Pohle, Martin Schrön, Steffen Zacharias, Solveig Landmark, Susanne Kathage, Andreas Kathage, Carmen Zengerle, Mandy Kasner, and Ulrike Werban

Soil water content in the unsaturated zone is a key parameter of the environmental system. The understanding of soil moisture plays a major role with regard to questions of water and nutrient supply to plants, groundwater recharge, soil genesis and climatic interactions.

In our study we aim to test a new technology for the non-invasive measurement of soil moisture profiles, the so-called Surface-NMR (Nuclear Magnetic Resonance). The instrument applies magnetic fields to the ground and detects its changes caused by mobile and immobile hydrogen atoms in the soil column. Using four different frequencies, the data may provide insights into the water content of four distinct soil layers between the surface and 20 cm depth.

We carried out multiple NMR measurements at four different field sites in Germany and compared the data with conventional methods, such as gravimetric soil samples, Time Domain Reflectometry (TDR), and Cosmic-Ray Neutron Sensing (CRNS).

The dataset will be used to investigate the following research questions:

  1. Is the Surface-NMR method suitable to provide depth-resolved information of soil moisture under field conditions?
  2. Does Surface-NMR have the potential to replace or complement conventional methods of soil moisture measurement in the field?
  3. What can we learn about the spatial variability and scale dependency of soil moisture by combining three measurement methods of different scale (TDR, NMR, CRNS)?

How to cite: Bauckholt, M., Pohle, M., Schrön, M., Zacharias, S., Landmark, S., Kathage, S., Kathage, A., Zengerle, C., Kasner, M., and Werban, U.: Evaluation of NMR and other soil water content measurement methods at the point and field scale, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9522,, 2020.

EGU2020-1072 | Displays | HS1.1.3

Optimization of ambient seismic noise interferometry to monitor groundwater level variations.

Marco Taruselli, Diego Arosio, Laura Longoni, Monica Papini, and Luigi Zanzi

 In this work, we test the cross-correlation of ambient seismic noise method in monitoring underground water variations. Within this perspective we applied the abovementioned technique to study the water table changes occurring both in areas exploited for drinking water needs and inside landslides. Into detail, surveys were carried out in Crépieux-Charmy and Ventasso water catchment fields and in the Cà Lita landslide, respectively. Our aim is to optimize the outcome of the method by studying the effect of different processing steps involved in the computation of the cross-correlation technique. For this purpose, we analyzed the influence of filter types and different time windows length. Additionally, in order to address the problem of localization of the change in the medium the seismic velocity variations have been also derived from limited frequency bandwidths according to the characteristics observed in the signals spectrum. This work has shown the potential of this methodology as a valuable non-destructive toll to accurately describe hydrogeological dynamics. The monitoring system could thus be coupled with the traditional tools to improve the reconstruction of the underground water variations.

How to cite: Taruselli, M., Arosio, D., Longoni, L., Papini, M., and Zanzi, L.: Optimization of ambient seismic noise interferometry to monitor groundwater level variations., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1072,, 2020.

EGU2020-19014 | Displays | HS1.1.3

Observation of gravity fluctuations due to tide-induced groundwater table fluctuations with two superconducting gravimeters

Hiroki Goto, Mituhiko Sugihara, Yuji Nishi, and Hiroshi Ikeda

Estimation of aquifer hydraulic properties is necessary for predicting groundwater flow and hence managing groundwater resources. Analysis of tide-induced groundwater table fluctuations in unconfined aquifers is one of the methods to estimate aquifer properties. Changes in groundwater level affect surface gravity. Consequently, surface gravity in coastal regions is expected to fluctuate due to the groundwater table fluctuations and is potentially useful for estimating aquifer properties. Moreover, gravity measurements are sensitive to mass redistribution around the observation location and therefore are useful for estimating the storage coefficient of an aquifer. In this study, surface gravity and unconfined groundwater level were measured continuously near the coast of Japan to observe gravity fluctuations due to the tide-induced groundwater table fluctuations. Groundwater level measured in two wells at 60 and 90 m distances from the coastline fluctuated in response to ocean tides. Two superconducting gravimeters (SGs) were installed at 70 and 80 m distances from the coastline and at an elevation of 8 m. After taking the difference between gravity values recorded with the two SGs and then correcting the gravity difference for ocean loading effects, diurnal and semi-diurnal gravity fluctuations, which are possibly due to tide-induced groundwater table fluctuations, were recognized. These results suggest that gravity monitoring with two SGs at different distances from the coastline can be useful for observing gravity fluctuations due to tide-induced groundwater table fluctuations and possibly for estimating aquifer hydraulic properties.

How to cite: Goto, H., Sugihara, M., Nishi, Y., and Ikeda, H.: Observation of gravity fluctuations due to tide-induced groundwater table fluctuations with two superconducting gravimeters, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19014,, 2020.

EGU2020-22370 | Displays | HS1.1.3

Discriminating biomass and soil water content with proximal gamma-ray spectroscopy

Fabio Mantovani, Matteo Albéri, Carlo Bottardi, Enrico Chiarelli, Kassandra Giulia Cristina Raptis, Andrea Serafini, and Virginia Strati

The exceptional capabilities of proximal radiometric measurements to estimate Soil Water Content (SWC) have recently been proven effective for precision farming applications. The water contained in the growing vegetation (i.e. Biomass Water Content, BWC) attenuates the terrestrial gamma signal acquired by a permanent station in a crop field and it represents the most relevant source of systematic bias. In the perspective of employing proximal gamma-ray spectroscopy for automatic irrigation scheduling, the Biomass Water Content (BWC) correction is mandatory for assessing crop water demand and for a sustainable use of water.

In this study we model the time dependent gamma signal attenuation due to BWC and we demonstrate that the SWC estimated through the corrected spectrometric data during a crop life-cycle agrees on average within 4% with the measurements obtained by gravimetric sampling campaigns. A reliable Monte Carlo simulation of the gamma photon generation, propagation and detection phenomena permits to evaluate the shielding effect due to the linear increase of BWC associated to stems, leaves and fruits of the tomatoes during their crop life-cycle. Compared to a SWC gamma estimation in the case of bare soil, the percentage overestimation δ is linearly correlated with the thickness of a biomass equivalent water layer (Tk) as δ (%) = 9.7 · Tk (mm), with a coefficient of determination r2 = 0.99.

Generalizing this approach, we can conclude that the plant growth curve is a fundamental input for correcting the SWC estimates in proximal gamma-ray spectroscopy via Monte Carlo simulation, in the perspective of filling the gap between punctual and satellite soil moisture measurements using this technique.

How to cite: Mantovani, F., Albéri, M., Bottardi, C., Chiarelli, E., Raptis, K. G. C., Serafini, A., and Strati, V.: Discriminating biomass and soil water content with proximal gamma-ray spectroscopy, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22370,, 2020.

HS1.1.4 – Advances in river monitoring and modelling: data-scarce environments, real-time approaches, Inter-comparison of innovative and classical frameworks, uncertainties, Harmonisation of methods and good practices

EGU2020-5684 | Displays | HS1.1.4 | Highlight

Low-cost river discharge measurements using a transparent velocity-head rod

Aurélien Despax, Jérôme Le Coz, Francis Pernot, Alexis Buffet, and Céline Berni

The common streamgauging methods (ADCP, current-meter or tracer dilution) generally require expensive equipment, with the notable exception of volumetric gaugings and floats, which are however often difficult to implement and limited to specific conditions. The following work aims at testing and validating a reliable, easy-to-deploy and low-cost gauging method, at a cost typically below 40 € each.

The “velocity-head rod” firstly described by Wilm and Storey (1944), made transparent by Fonstad et al. (2005) and improved by Pike et al. (2016) meets these objectives, for wading gauging with velocities greater than 20 cm/s typically. The 9.85 cm wide clear plastic rod is placed vertically across the stream to identify upstream and downstream water levels using adjustable rulers. The difference in level (or velocity head) makes it possible to calculate the average velocity over the vertical, using a semi-empirical calibration relationship.

Experiments carried out in INRAE’s hydraulic laboratory and in the field have enabled us to find a calibration relationship similar to that proposed by Pike et al. (2016) and confirm the optimal conditions of use. The average deviation to a reference discharge has been found to be close to 5 % except for very slow-flow conditions. The influence of the width of the rod on the velocity-head was studied in the laboratory. The uncertainty of the velocity due to the reading of water levels has been estimated. It increases at low velocity due to decreasing sensitivity, and increases at high velocities due to water level fluctuations that are difficult to average.

Several improvements were tested in order to facilitate and improve the measurement operations, without increasing the cost too much: magnetic ruler, removal of a graduated steel rule (expensive), plastic ruler with water level and velocity graduations, reading the depth with another ruler, spirit level, electrical contact (so the operator has not to bend to the surface of the water). An operational procedure and a spreadsheet for computing discharge are proposed. The method being extremely simple and quick to apply is well suited for rapid estimates of flow (instead of floats), training or demonstrations, citizen science programs or cooperation with services with limited resources.

Acknowledgments: The authors thank Q. Morice, J. Cousseau, Y. Longefay (DREAL) who were involved in this study by carrying out field tests.

How to cite: Despax, A., Le Coz, J., Pernot, F., Buffet, A., and Berni, C.: Low-cost river discharge measurements using a transparent velocity-head rod, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5684,, 2020.

EGU2020-9943 | Displays | HS1.1.4

Wind effect on image-based river surface velocity measurements

Salvador Peña-Haro, Beat Lüthi, Robert Lukes, and Maxence Carrel

Image-based methods for measuring surface flow velocities in rivers have several advantages, one of them being that the sensor (camera) is not in contact with the water and its mounting position is very flexible hence there is no need of expensive structures to mount it. Additionally, it is possible to measure the whole river width. On the other hand, environmental factors, like wind, can affect the surface velocity and the have an impact on the accuracy of the measurements.

Herein we present an analysis of the wind effect on the image based surface velocity at Rhine river, at the border between Switzerland and Austria. At this location the river width is of approximately 100 meters under low flow conditions, while the width of its floodplain is of about 200 m. An ATMOS 22 ultrasonic anemometer was installed at the site to measure the wind intensity as well as its direction.

A time series of flow velocities and wind from May to October 2019 was analyzed. During this period, the average discharge was 320 m3/s and the average flow velocity 1.7 m/s. While the average wind velocity was of 2.3m/s which roughly follows the same direction of the river flow.

A rating curve following a power law function was fitted to the image based surface flow measurements. It was found that for maximum wind speeds of 10 m/s, blowing in the opposite direction of the river flow, there was a deviation of 8%. For the average wind speed of 2.3m/s, the deviation was found to be 3%.

How to cite: Peña-Haro, S., Lüthi, B., Lukes, R., and Carrel, M.: Wind effect on image-based river surface velocity measurements, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9943,, 2020.

EGU2020-10659 | Displays | HS1.1.4

UAV-based training for fully fuzzy classification of Sentinel-2 fluvial scenes

Patrice Carbonneau, Barbara Belletti, Marco Micotti, Andrea Casteletti, Stefano Mariani, and Simone Bizzi

In current fluvial remote sensing approaches, there exists a certain dichotomy between the analysis of small channels at local scales which is generally done with airborne data and the analysis of entire basins at regional and national scales with satellite data. One possible solution to this challenge is to use low-altitude imagery from low-cost UAVs to provide sub-metric scale class information which can then be used to train fuzzy classification models for entire Sentinel 2 tiles. The fuzzy classification approach can allow for sub-pixel information and when extended to entire Sentinel 2 tiles, the method therefore develops information at a resolution of less than 10 meters (the best spatial resolution of Sentinel 2 bands) at regional scales. In this contribution, we present such a method where UAV imagery is used as the training data for the fully fuzzy classification of Sentinel 2 imagery. We partition the fluvial corridor in three simple classes: water, dry sediment and vegetation.  Then we manually classify the local UAV imagery into highly accurate class rasters. In order to augment the value of the Sentinel 2 data, we use an established super-resolution method that delivers 10 meter spatial resolution across all 11 Sentinel 2 bands. We then use the sub-metric UAV classifications as training data for the 10 meter super-resolved Sentinel 2 imagery and we train fuzzy classification models using random forests, dense neural networks and convolutional neural networks (CNN). We find that CNN architectures perform best and can predict class membership within a pixel of a new Sentinel 2 tile not seen in the training phase with a mean error of 0% and an RMS error of 18%. Crisp class predictions derived from the fuzzy models range in accuracy from 88% to 99%, even in the case of tiles never seen in the training phase. With this approach, it is now possible to deploy a low-cost UAV in order to train a transferable CNN model that can predict fuzzy classes at very large scales from freely available Sentinel 2 imagery. This approach can therefore serve as the basis for multi temporal classification and change detection of the Sentinel 2 archives.

How to cite: Carbonneau, P., Belletti, B., Micotti, M., Casteletti, A., Mariani, S., and Bizzi, S.: UAV-based training for fully fuzzy classification of Sentinel-2 fluvial scenes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10659,, 2020.

Environmental Flow Release monitoring can be an expensive undertaking in active watercourses normally suitable for run-of-river hydropower projects.  In order to attain acceptable (<10%) uncertainty in the derived flow series, it is necessary for a Qualified Professional (QP) to make several site visits to measure a range of flows in order to calibrate a stage-discharge (rating) curve.  With climate change, the need to measure drought conditions and respond appropriately is crucial for habitat health and to prevent fish stranding.  The current study employs a Water Quality Mixing Model (WQMM) to estimate flows at a downstream site from an existing hydropower plant using a modified constant rate mixing model.  This is an independent estimate of flow entirely distinct from the stage-discharge curve.  The method can be employed anywhere there is a sufficient mixing length and sufficiently distinct WQ traits.  The method can reduce both maintenance costs and flow uncertainty where Environmental Flow Release Monitoring is required.

How to cite: Sentlinger, G.: Water Quality Mixing Model (WQMM) for Environmental Flow Release Monitoring, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11759,, 2020.

EGU2020-13832 | Displays | HS1.1.4

Uncertainty quantification of continuous streamflow monitoring in high elevation Alpine catchments

Florentin Hofmeister, Brenda Rubens Venegas, Markus Disse, and Gabriele Chiogna

Correct streamflow measurements are of fundamental importance for hydrology. Mountain catchments are particularly complex systems to obtain reliable discharge time series and several challenges have to be overcome. For example, turbulent flow of mountain streams leads to unstable streambed conditions by erosion and sedimentation and the irregular stream profile makes any streamflow measurements through the velocity-area method difficult. The salt dilution method provides reliable streamflow estimation for specific injection times. We can construct rating curves when these and river stage data are available. However, this relationship entails intrinsic uncertainties that derive from experimental errors as well as from extrapolation outside the measured range. In this work, we provide a rigorous quantification of the uncertainty of discharge measurement based on rating curves using error propagation techniques. During multiple field campaigns in 2019, we collected 74 streamflow measurements for nine sites over three high Alpine catchments (Horlachtal, Kaunertal and Martelltal). We then consider also continuous measurements of water level, water temperature and electrical conductivity. The aim is not only to get more information about the hydrological processes and response of these catchments but also to use this information to construct more robust and less uncertain rating curves. Our results show the high uncertainty affecting measured discharges in Alpine catchments and they are relevant for model applications as well. In fact, the uncertainty in river discharge observations affects the optimal value of the model objective function (e.g., Nash-Sutcliff Efficiency).

How to cite: Hofmeister, F., Rubens Venegas, B., Disse, M., and Chiogna, G.: Uncertainty quantification of continuous streamflow monitoring in high elevation Alpine catchments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13832,, 2020.

EGU2020-18413 | Displays | HS1.1.4 | Highlight

Continuous measurement of open channel discharge using a video data logger and subsequent LSPIV analysis

Peter Eichendorff and Andreas Schlenkhoff

Accurate flow data form the basis for describing hydrological runoff processes and extremes. While the continuous measurement of the water level is a standard task in hydrometry, the continuous measurement of flow velocity is more complex and often involves greater effort. Videometric methods like LSPIV (Large Scale Particle Image Velocimetry) allow a contactless acquisition of surface velocity distribution in open channels. Ready-to-use instrumentation for that purpose is hardly available and requires permanent electricity supply.
Therefore, a simple self-made measuring system, consisting of a data logger with camera and a distance sensor, is introduced. It enables not only the detection of the water level but also the recording and remote transmission of video data. Based on an Arduino microcontroller and a Raspberry Pi Single Board Computer the battery-powered data logger is freely programmable with open source software and supports the operation of various sensors with digital interface at low power consumption. 
The measuring system with its wide angle camera is intended to be mounted on bridges or steep banks with longitudinal or transverse to flow camera alignment. The water level is detected by an ultrasonic range transducer, a raspberry pi camera module with wide angle lens records videos in 1080p resolution.  The water level data and the videos are remotely transmitted via cellular network to a server that provides the data to the subsequent LSPIV analysis. The LSPIV analysis enables a high-resolution measurement of the velocity distribution at the water surface and in combination with the known channel geometry and the height of the water level it offers an accurate discharge determination.
Particularly with regard to extreme events the use of video data brings considerable advantages as it allows a visual on-site inspection of the situation. Information such as the condition of the local vegetation, icing or disturbing influences at the gauge site can be derived and included in the flow rate determination.

How to cite: Eichendorff, P. and Schlenkhoff, A.: Continuous measurement of open channel discharge using a video data logger and subsequent LSPIV analysis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18413,, 2020.

EGU2020-21652 | Displays | HS1.1.4 | Highlight

Use of Unmanned Aerial Systems for Hydrological Monitoring

Salvatore Manfreda and the HARMONIOUS TEAM

Unmanned Aerial Systems (UAS) are offering an extraordinary opportunity to improve our ability to monitor river basins. The wide use of UAS leaded to a significant grow of the number of applications and methodologies developed for specific scopes of environmental monitoring. For this reason, there is a serious challenge to harmonise and provide standardised guidance applicable across a broad range of environments and conditions. In this context, a network of scientists is cooperating within the framework of a COST (European Cooperation in Science and Technology) Action named “Harmonious - Given the wide use of UAS within environmental studies”. The intention of “Harmonious” is to promote monitoring strategies, establish harmonised monitoring practices, and transfer most recent advances on UAS methodologies to others within a global network. The working groups of Harmonious are currently working on the definition of practical guidance for environmental studies identifying critical processes and the interconnection of each step for a successful workflow. Given the number of environmental constraints and variables, it is impractical to provide a protocol that can be applied universally under all possible conditions, but it is possible to systematise the fragmented knowledge on this topic identifying the best-practices to improve the overall quality of the final products. Preliminary results of the HARMONIOUS COST Action will be given.

How to cite: Manfreda, S. and the HARMONIOUS TEAM: Use of Unmanned Aerial Systems for Hydrological Monitoring, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21652,, 2020.

EGU2020-324 | Displays | HS1.1.4

An evaluation of image velocimetry techniques under low flow conditions and high seeding densities using Unmanned Aerial Systems

Sophie Pearce, Robert Ljubicic, Salvador Pena-Haro, Matthew Perks, Flavia Tauro, Alonso Pizarro, Silvano Fortunato Dal Sasso, Dariia Strelnikova, Salvatore Grimaldi, Ian Maddock, Gernot Paulus, Jasna Plavsic, Dusan Prodanovic, Salvatore Manfreda, Mark Corbett, and Nick Everard

Image velocimetry (IV) is a remote technique which calculates surface flow velocities of rivers (or fluids) via a range of cross-correlation and tracking algorithms. IV can be implemented via a range of camera sensors which can be mounted on tri-pods, or Unmanned Aerial Systems (UAS). IV has proven a powerful technique for monitoring river flows during flood conditions, whereby traditional in-situ techniques would be unsafe to deploy. However, little research has focussed upon the application of such techniques during low flow conditions. The applicability of IV to low flow studies could aid data collection at a higher spatial and temporal resolution than is currently available. Many IV techniques are under-development, that utilise different cross-correlation and tracking algorithms, including, Large Scale Particle Image Velocimetry (LSPIV), Large Scale Particle Tracking Velocimetry (LSPTV), Optical Tracking Velocimetry (OTV), Kanade Lucas Tomasi Image Velocimetry (KLT-IV) and Surface Structure Image Velocimetry (SSIV). Nevertheless, the true applications and limitations of such algorithms have yet to be extensively tested. Therefore, this study aimed to conduct a sensitivity analysis on the commonly relatable parameters between the different algorithms, including the particle identification area parameters (such as Interrogation Area (LSPIV, LSPTV and SSIV), Block Size (KLT-IV) and Trajectory Length (OTV)) and the feature extraction rate (or sub sampled frame rate).

Fieldwork was carried out on Kolubara River near the city of Obrenovac in Central Serbia. Cross-sectional surface width was relatively constant, varying between 23.30 and 23.45m. During the experiment, low flow conditions were present with a discharge of approx. 3.4m3 s-1 (estimated using a Sontek M9 ADCP), and depths of up to 1.9m. A DJI Phantom 4 Pro UAS was used to collect video data of the surface flow. Artificial seeding material (wood-mulch) was distributed homogenously across the rivers’ surface, in order to improve the conditions for IV techniques during slow flows. Two 30-second videos were utilised for surface velocity analysis.

This study highlighted that KLT, SSIV, OTV and LSPIV are the least sensitive algorithms to changing parameters when no pre- or post-processing of results are conducted. On the other hand, LSPTV must undergo post-processing procedures in order to avoid spurious results and only then, results may be reliable. Furthermore, KLT and SSIV highlighted a slight sensitivity to changing the feature extraction rate, however changing the particle identification area did not affect significantly the outputted surface velocity results. OTV and LSPTV, on the other hand, highlighted that changing the particle identification area provided a higher variability in the results, whilst changing the feature extraction rate did not affect the surface velocity outputs. LSPIV proved to be sensitive to changing both the feature extraction rate and the particle identification area.

This analysis has led to the conclusions that during the conditions of sampling with surface velocities of approximately 0.12ms-1, and homogeneous seeding on the rivers surface, IV techniques can provide results comparable to traditional techniques such as ADCPs during low flow conditions. All IV algorithms provided results that were, on average, within 0.05ms-1 of the ADCP measurements.


How to cite: Pearce, S., Ljubicic, R., Pena-Haro, S., Perks, M., Tauro, F., Pizarro, A., Fortunato Dal Sasso, S., Strelnikova, D., Grimaldi, S., Maddock, I., Paulus, G., Plavsic, J., Prodanovic, D., Manfreda, S., Corbett, M., and Everard, N.: An evaluation of image velocimetry techniques under low flow conditions and high seeding densities using Unmanned Aerial Systems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-324,, 2020.

EGU2020-4229 | Displays | HS1.1.4 | Highlight

A drone-borne contactless method to jointly estimate discharge and Manning’s roughness in rivers

Filippo Bandini, Beat Lüthi, Salvador Peña-Haro, and Peter Bauer-Gottwein

Unmanned Aerial Systems (UASs) can monitor streams and rivers also in remote, inaccessible locations during extreme hydrological events. Image cross-correlation analysis techniques, such as Particle Image Velocimetry (PIV), applied to videos acquired using UASs can provide estimates of water surface velocity (WSV) in rivers. However, estimation of discharge from WSV is not trivial: it requires water depth and the mean vertical velocity (Um). Scientific studies show that Um is generally between 70% and 90% of WSV; however, an accurate estimation of Um from WSV requires assumptions on the full vertical velocity profile. We developed a new method for estimating WSV applying PIV techniques on UAS-borne videos. This method does not require any Ground Control Point (GCP), because the conversion of the velocity field from pixels into meters is performed by using a camera pinhole model where the distance from the pin-hole to the water surface is measured by an on-board radar altimeter. For approximately uniform flow conditions, Um becomes a function of Gauckler–Manning–Strickler roughness coefficient (Ks) and WSV. Our method can be used to jointly estimate Ks and discharge by informing a non-linear system of 2 equations and 2 unknowns (Ks and discharge): i) Manning equation ii) mid-section method equation for computing discharge from Um, which is a function of WSV and ks. This approach merely relies on bathymetry knowledge, on UAV-borne measurements of WSV and water surface slope.  Our approach was extensively validated in 27 case studies, in multiple Danish streams with different hydraulic conditions. Compared to discharge measured with a multi-depth electromagnetic velocity probe, PIV-estimates of discharge showed a mean absolute error of 18% and a mean bias error of -9%. The underestimation of discharge is caused by inaccuracies in WSV, by deviations from the uniform flow assumption and by the assumption of constant Ks coefficient for the entire cross section.

How to cite: Bandini, F., Lüthi, B., Peña-Haro, S., and Bauer-Gottwein, P.: A drone-borne contactless method to jointly estimate discharge and Manning’s roughness in rivers , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4229,, 2020.

EGU2020-4661 | Displays | HS1.1.4

Uncertainty of discharge measurement using salt dilution

Alexandre Hauet, Kristoffer Florvaag-Dybvik, Mads-Peter Jakob Dahl, Frode Thorset Kvernhaugen, Knut Magne Møen, and Gabriel Sentlinger

Discharge measurement using salt dilution is an old method, but it has been recently more and more used thanks to the development of new sensors making it possible to measure conductivity and compute discharge in real-time. Salt dilution is very well suited for turbulent rivers, such as mountain streams. The ISO standard ISO 9555 propose a normative framework to estimate uncertainty, but it was published in 1994 and is now obsolete for new sensors and computational capabilities. In this article, we propose a complete framework to compute the uncertainty of a salt dilution gauging following the GUM (Guide to the expression of uncertainty in measurement) method that take into account the following error sources:  (i) the uncertainty in the mass of salt injected, (ii)  the uncertainty in the measurement of time, (iii) the uncertainty in the Conductivity to Concentration law, (iv) the uncertainty if a measurement conductivity is out of the range of the Conductivity to Concentration law, (v) the uncertainty in the computation of the area under the conductivity curve, (vi) the uncertainty due to a not perfect mixing of the tracer if the mixing length between injection and the probes is not reached (vii) the uncertainty due to a loss or a gain of tracer between the injection and the probes if tracer can be adsorbed for example and (viii) the uncertainty due to unsteadiness of the flow  i.e. variation of discharge during the measurement. The method for computing each uncertainty source is presented and the new framework is applied to a set of real measurements and compared to the expertise of field hydrologists.

How to cite: Hauet, A., Florvaag-Dybvik, K., Dahl, M.-P. J., Kvernhaugen, F. T., Møen, K. M., and Sentlinger, G.: Uncertainty of discharge measurement using salt dilution , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4661,, 2020.

EGU2020-6779 | Displays | HS1.1.4 | Highlight

Comparison of rating-curve uncertainty estimation using hydraulic modelling and power-law methods

Ida Westerberg, Valentin Mansanarez, Steve Lyon, and Norris Lam

Establishing reliable rating curves and thereby reliable streamflow monitoring records is fundamental to much of hydrological science and water management practice. Cost-effective methods that enable rapid rating curve estimation with low uncertainty are needed given diminishing monitoring resources and increasing human-driven changes to the water cycle. Traditional power-law rating curves rely on numerous gaugings to estimate rating curves and their associated uncertainty. Hydraulically-modelled rating curves are a promising alternative to power-law methods as they rely on fewer gaugings, but they are associated with additional uncertainty sources in the hydraulic knowledge (bed slope, roughness, topography and vegetation), which need to be assessed.

Our aim with this study was to compare power-law and hydraulic-model based methods for estimating rating curves and their uncertainty. We focused on assessing their accuracy as well as the costs and time required for establishing rating curves. We compared the Rating curve Uncertainty estimation using Hydraulic Modelling (RUHM) framework with the Bayesian power-law method BaRatin. The RUHM framework combines a one-dimensional hydraulic model with Bayesian inference to incorporate information from both hydraulic knowledge and the calibration gauging data. We applied both methods to the 584 km2 River Röån station in Sweden under nine different gauging strategies associated with different costs. The gauging strategies differed in the number and flow magnitude of the gaugings used as well as the probability of observing the gauged flows.

We found that rating curves with low uncertainty could be modelled with fewer gaugings using the RUHM framework compared to BaRatin. As few as three gaugings were needed for RUHM if these gaugings covered low and medium flows, making the estimation both cost effective and time efficient. When using all the gaugings available (i.e. a high-cost gauging strategy), the uncertainty for RUHM and BaRatin was similar at the Röån station. Furthermore, we found that BaRatin needed gaugings with lower probability of occurrence (i.e. covering a larger part of the flow range) than needed when using hydraulic modelling (low and middle flow gaugings with high probability of occurrence gave good results). The results for this Swedish site show that hydraulic rating curve uncertainty estimation is a promising tool for quickly estimating rating curves and their uncertainties. In particular, it is useful for previously ungauged or remote sites, or at stations where there have been major temporal changes to the stage–discharge relation.

How to cite: Westerberg, I., Mansanarez, V., Lyon, S., and Lam, N.: Comparison of rating-curve uncertainty estimation using hydraulic modelling and power-law methods, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6779,, 2020.

EGU2020-8890 | Displays | HS1.1.4

Impacts of water resources management on the North China Plain revealed in multi-mission earth observation datasets

Jun Liu, Liguang Jiang, Filippo Bandini, Xingxing Zhang, and Peter Bauer-Gottwein

The natural conditions of surface water bodies and groundwater aquifers in many densely populated river basins have been altered in order to satisfy various human water demands, such as drinking water supply, irrigation, power generation and navigation. The North China Plain (NCP) accounts for about 24% of the country's population, and the huge water demand makes it one of the regions with the strongest artificial intervention in the water cycle. China has promoted the South-to-North Water Diversion (SNWD), which diverts surplus water from the Yangtze River Basin to the water-deficient North. Since the central line project of SNWD has become fully operational in 2014, more than 16 km3 of water have been supplied to the NCP, which has had a significant impact on water resources in the regions along the route. Monitoring the recent dynamics of surface and sub-surface water storage is essential for water resources management and sustainable use of ongoing and forthcoming SNWD water transfers. Multi-mission satellite earth observation methods provide timely and spatially resolved datasets for monitoring inland water bodies, which have been validated over the last two decades. In this study, first, we evaluate the influence of SNWD on the Terrestrial Water Storage (TWS) monitored by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on mission (GRACE-FO) over the NCP. The results indicate that the significant downward trend during 2002 – 2014 period, has stopped in the past 5 years, since the implementation of the central line project of SNWD. Second, Sentinel-3 radar altimetry and Sentinel-1 SAR missions were used to monitor the water surface extent and water surface elevation of surface water bodies. Sentinel-1 with its newly available Synthetic Aperture Radar (SAR), high spatial resolution and short temporal baselines shows potential for monitoring surface water area variations. Sentinel-3 benefits from the new Sentinel Ku/C Radar Altimeter (SRAL) and a modified on-board tracking system and shows great potential for monitoring inland water surface elevation (WSE) variations for several large and medium reservoirs and canals in this region. We show that, along with other policy measures, the SNWD transfers have had a significant impact on the water balance of the NCP region as evident from multiple satellite earth observation missions.

How to cite: Liu, J., Jiang, L., Bandini, F., Zhang, X., and Bauer-Gottwein, P.: Impacts of water resources management on the North China Plain revealed in multi-mission earth observation datasets, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8890,, 2020.

EGU2020-15525 | Displays | HS1.1.4

Image-velocimetry techniques under particle aggregation for streamflow monitoring: a numerical approach

Alonso Pizarro, Silvano Fortunato Dal Sasso, and Salvatore Manfreda

Monitoring extreme events with high accuracy and consistency is still a challenge, even by using up-to-date approaches. On the one side, field campaigns are in general expensive and time-consuming, requiring the presence of high-qualified personnel and forward planning. On the other side, non-contact approaches (such as image velocimetry, radars, and microwave systems) have had promising signs of progress in recent years, making now possible real-time flow monitoring. This work focuses on the estimation of surface flow velocities for streamflow monitoring under particle aggregation, in which tracers are not necessarily uniformly distributed across the entire field of view. This issue is extremely relevant for the computing stream flows since velocity errors are transmitted to river discharge estimations. Ad-hoc numerical simulations were performed to consider different levels of particle aggregation, particle colour and shapes, seeding density, and background noise. Particle Tracking Velocimetry (PTV) and Large-Scale Particle Image Velocimetry (LSPIV) were used for image velocimetry estimations due to their widely used worldwide. Comparisons between the theoretical and computed velocities were carried out to determine the associated uncertainty and optimal experimental setup that minimises those errors.

How to cite: Pizarro, A., Dal Sasso, S. F., and Manfreda, S.: Image-velocimetry techniques under particle aggregation for streamflow monitoring: a numerical approach, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15525,, 2020.

EGU2020-16011 | Displays | HS1.1.4

On the characterisation of open-flow seeding conditions for image-velocimetry techniques using UASs

Silvano Fortunato Dal Sasso, Alonso Pizarro, and Salvatore Manfreda

In the last years, new technologies have been developed to monitor rivers in a real-time framework opening new opportunities and challenges for the research community and practitioners. Acquiring data in open flow conditions can be performed through the use of Unmanned Aerial System (UAS) to derive surface velocity fields and in consequence, river discharge. Significant work has been done to investigate the reliability of image-velocimetry techniques using numerical simulations and laboratory flume experiments, but, to date, the effects of environmental factors on velocity estimates are not addressed adequately. In this context, a critical variable is represented by the number of particles transiting on the water surface (defined as seeding density) during field surveys and their challenging dynamics along the cross-section, on both time and space. Seeding density has a significant effect on surface velocity estimation and river discharge accuracy. The goal of this study was, therefore, to evaluate the accuracy and feasibility of LSPIV and PTV techniques under different seeding and flow conditions using several footages acquired employing UASs. To this purpose, the seeding behaviour during the whole acquisition time was examined for each case study focusing on the quantification of essential variables such as seeding density, average tracers’ dimension, coefficient of variation of tracers’ area, and spatial dispersion of them in the field of view. For each case study, both image-velocimetry techniques have been applied considering several different sets of images to locally measure the accuracy of velocity estimations in challenging seeding conditions. Results show that the local seeding density, tracers’ dimension and their spatial distribution can strongly influence the reconstruction of velocity fields in natural stream reaches. Therefore, prior knowledge of seeding characteristics in the field can deal with the choice of the optimal image-velocimetry technique to use and the related setting parameters.

How to cite: Dal Sasso, S. F., Pizarro, A., and Manfreda, S.: On the characterisation of open-flow seeding conditions for image-velocimetry techniques using UASs , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16011,, 2020.

We introduce a Python based software tool to measure surface flow velocities and to estimate discharge eventually. Minimum needed input are image sequences, some camera parameters and object space information to scale the image measurements. Reference information can be provided either indirectly via ground control point measurements or directly providing camera pose parameters. To improve the reliability and density of velocity measurements the area of interest has to be masked for image velocimetry. This can either be performed with a binary mask file or considering a 3D point cloud, for instance retrieved with Structure from Motion (SfM) photogrammetry, describing the region of interest. The tracking task can be done with particle image velocimetry (PIV) considering small interrogation regions or using particle tracking velocimetry (PTV) and thus detecting and tracking features at the water surface. To improve the robustness of the tracking results, filtering can be applied that implements statistical information about the flow direction, flow steadiness and average velocities.

The FlowVeloTool has been tested with two different datasets; one at a gauging station and one at a natural river reach. Thereby, UAV and terrestrial data were acquired and processed. Velocities can be estimated with an accuracy of 0.01 m/s. If information about the river topography and bathymetry are available, as in our demonstration, discharge can be estimated with an error ranging from 5 to 31 % (Eltner et al. 2019). Besides these results we demonstrate further developments of the FlowVeloTool regarding filtering of tracking results, discharge estimation, and processing of time series. Furthermore, we illustrate that thermal data can be used, as well, with our tool to retrieve river surface velocities.


Eltner, A., Sardemann, H., and Grundmann, J.: Flow velocity and discharge measurement in rivers using terrestrial and UAV imagery, Hydrol. Earth Syst. Sci. Discuss.,, 2019.

How to cite: Eltner, A. and Grundmann, J.: FlowVeloTool: Measuring flow velocities in terrestrial and UAV image sequences automatically with PIV and PTV, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17773,, 2020.

There is growth in evidence of intensification of the global hydrological cycle over the past few decades, possibly due to changing climate and/or land-use landcover associated with anthropogenic forcing. For sustainable water management, an efficient and effective streamflow network is essential as it facilitates accurate monitoring of spatio-temporal variations of surface water. However, in recent years a remarkable decline in stream gauge density is observed in both developed and developing countries, possibly due to economic constraints and changing government priorities. World Meteorological Organization recommends periodic reviewal of stream gauge networks (accounting for changes in budgetary, data and end user’s needs) to improve the database for better assessment of hydrological uncertainty. However, there is a dearth of such attempts in India. Entropy theory (specifically Shannon entropy-based method (SEBM)) has gained wide recognition over the past few decades for the optimal design of hydrometric networks owing to its advantages. However, the SEBM has some limitations, which include (i) lack of fixed upper bound for entropy when a uniform distribution is considered to determine the probability and (ii) loss of information due to discretization of data in analysis with continuous variables. In this backdrop, there is a need to locate feasible alternatives to the Shannon entropy method. There are various methods for entropy estimation and data discretization, but there is a lack of information on their relative performance. This study is envisaged to investigate these aspects and to propose a novel fuzzy approach for optimal design and performance assessment of a stream gauge monitoring network. The proposed methodology does not require the choice of bin size for the discretization of data to estimate entropy measures/indices. Therefore, it alleviates the associated uncertainty which is a concern in analysis with SEBM and its related theoretical improvement EEBM (exponential entropy-based methodology). This is demonstrated through case studies on 16 river basins of Peninsular India encompassing more than 600,000 km2 by considering objectives as prioritization of existing gauges, identification of gauge deficient zones and devising options for expansion of the existing stream gauge networks. Further, the effect of choice of bin size on entropy estimates obtained using SEBM and EEBM is demonstrated by considering nine bin size determination methods. Flows in ungauged catchments were simulated using SWAT (Soil and Water Assessment Tool) and optimization of the existing stream gauge network is performed using a Fast-Non-Dominated Sorting Genetic Algorithm (NSGA-II). The study indicated that all the stream gauge networks in peninsular India are inadequate for effective monitoring of flows and there is a growing need for their expansion.  This study is first of its kind which evaluates the potential of different entropy-based methods in stream gauge network design. The proposed methodology could be readily considered for the evaluation of networks monitoring other hydro-meteorological and hydrological variables, and water quality parameters.

How to cite: Vijay, S.: A Comparative Study of Entropy-based Methods for Optimal Design of Streamgauge Monitoring Networks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-398,, 2020.

Previous studies have established the ability to map river channel bathymetry accurately in clear water, shallow wadeable streams using imagery from Unmanned Aerial Vehicles (UAVs), Structure-from-Motion (SfM) photogrammetry and the application of refraction correction. However, because standard rotary-winged UAVs geotag imagery at a relatively low accuracy, there has been a need to use Ground Control Points (GCPs) to georeference the Digital Elevation Model (DEM). This is problematic in that is requires the operators to navigate around the site to place, survey and collect the GCPs which can be very time consuming and/or hazardous. A potential solution lies with the recent introduction of lower cost rotary-winged drones fitted with higher accuracy on-board RTK GPS sensors. These have raised the possibility of conducting UAV surveys with the use of very few or no GCPs across the survey site, saving time and removing the need to access all areas for GCP placement.

To test this possibility, we flew a 250 metre reach of the River Teme (max depth ~1m) on the English-Welsh border at 40m in July 2019 with two drones, i.e. a DJI Phantom 4 RTK UAV and base station and a DJI Phantom 4 PRO (non-rtk). The Phantom 4 RTK UAV was flown three times, i) using the flight program’s 2D option (nadir only and one flight path) ii) using the 3D option (camera angled at 60° and flown in two directions) and iii) using the RTK off option and then using post-processing (PPK) to correct the image locations. 20 GCPs were placed across the site and their locations surveyed with a Trimble R8 dGPS and an additional 20 Independent Validation Points (IVPs) were surveyed along the floodplain for terrestrial validation points and 100 points within the channel were surveyed submerged area validation points.

Imagery was processed with Agisoft Metashape (v1.5.5). A total of 28 DEMs were produced using the imagery from the two drones, different flight paths and different combinations of numbers and location of GCPs. These included reducing the number of GCPs from 20, to 10, 5, 3, 1 and 0. When using three GCPs, DEMs were produced by having them i) spread throughout the reach and ii) clustered close to one another. The bed heights of the submerged locations were corrected using the simple refraction correction first used by Westaway et al (2001) and then compared to the measured heights in the field. Accuracy was quantified using linear regression.

The results of this analysis demonstrated the ability to obtain accurate surveys of bathymetry in depths upto 1m using a DJI Phantom 4 RTK UAV and base station and a significantly reduced number of GCPS, combined with the application of refraction correction. This study confirms that considerable time saving in terms of fieldwork can be gained from the use of an RTK rotary-winged drone and base station. This technology can also be beneficial for obtaining accurate survey data in locations where it may be unsafe or impossible to place GCPs due to the hazardous nature of the terrain.

How to cite: Maddock, I. and Lynch, J.: Assessing the accuracy of river channel bathymetry measurements using an RTK rotary-winged Unmanned Aerial Vehicle (UAV) with varying Ground Control Point (GCP) number and placement, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1534,, 2020.

In this research, we conducted LSPIV (Large Scale Particle Image Velocimetry) measurements to measure river surface velocity based on images recorded by mobile phone. The realization of this research is based on the developments of two products. The first one is the digital camera, which has been combined with the mobile phone after several years of development. The second one is the three-axis accelerometer, which can measure the attitude of the object. A three-axis accelerometer is one of the necessary parts of the mobile phone nowadays, as many functions of the mobile phone, such as step counting, Do Not Disturb mode, games, require the detection of attitude.

In LSPIV, there are nine parameters of the collinear equation. Three of parameters are the coordinates of the perspective center in the image space (focus distance d and image center position (u, v)), which can be determined in advance in the laboratory; the other three parameters are the coordinates (x, y, z) of the perspective center in real space, which can be set to (0, 0, 0); the last three parameters are the attitude of the camera (i.e., the mobile phone), which is determined by the depression angle, the horizontal angle, and the left-right rotation angle and can be measured by three-axis accelerometer. Therefore, river surface velocity could be analyzed by LSPIV with not only continuous images captured by a camera of the mobile phone but also the acceleration values obtained by the three-axis accelerometer when each image was captured.

In the present study, Yufeng gauging station, which is in the upstream catchment of the Shihmen Reservoir in Taiwan, is selected as the study site. Two other measurement methods were used to measure the river surface velocity and the comparison was conducted. One is using a handheld digital flow meter and another is using LSPIV with control points to calculate the parameters for measuring the river surface velocity.

How to cite: Liu, W.-C. and Huang, W.-C.: Large scale particle image velocimetry measurement of river surface velocity based on images captured by a camera of the mobile phone, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1760,, 2020.

Robust predictions and forecasts of flood risks and hazards are reliant on accurate estimates of stream flow data.  However, the stage-discharge relationship is subject to substantial uncertainties from a range of error sources, particularly for out-of-bank flows where measurements are scarce and flows are often extrapolated.  Hydraulic modelling can be used to produce more reliable stage–discharge relationships beyond the range of observed measurements, but, these methods are often data intensive requiring topographical, bathymetric, calibration data etc. restricting their use across large samples of gauges.    

In this study, we present an automatable framework that can estimate out-of-bank discharge uncertainty using a hydrodynamic model and readily available national datasets.  The framework utilises LiDAR data, in-bank stage-discharge measurements and gauged river flows to calibrate a 1D/2D hydrodynamic model (LISFLOOD-FP) of a river reach and make predictions of river flow and rating curve uncertainty beyond bankfull.  A particularly novel aspect of this framework is the use of national LiDAR datasets of water surface elevation returns to estimate the bathymetry and friction in the channel using an inversion solver. 

The framework was applied to produce models of two gauged river reaches in the UK, the River Severn at Montford in Shropshire, and the River Tweed at Norham in Northumberland. Bathymetry estimates were consistent with observations, considering that the channel was simplified to rectangular below the LiDAR water surface, while Manning’s channel friction estimates were between 0.03 and 0.035. The model predictions showed a close fit to the official rating curve and out-of-bank stage-discharge measurements, with the model-predicted uncertainty bounds able to contain 89.5% and 100% of the out-of-bank flow measurements for Montford and Norham respectively. This holds promising results for quantifying out-of-bank discharge uncertainties across large samples of catchments to enable robust national flood risk assessment.

How to cite: Coxon, G., Milsom, R., and Neal, J.: Estimating out-of-bank discharge uncertainties using a hydrodynamic model and nationally available datasets, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3066,, 2020.

EGU2020-4300 | Displays | HS1.1.4

Application of Data Assimilation and Ensemble Kalman Filter for Flood Forecast in Tamsui River, Taiwan

Ming-hsi Hsu, Jin-Cheng Fu, Ming-Chun Tsao, and Nobuaki Kimura

Typhoon is the most frequent natural disaster that causes widespread damage during summer and autumn in Taiwan. On average, each year the island suffers four typhoons, which result in disastrous flash floods and losses in a short time because of steep terrains and intense rainfall. The Tamsui River Basin is located in northern Taiwan about 2,726 square kilometers and inhabited by eight million people. During flooding events, the emergency managers rely on accurate flood forecasting to take proper actions for damage reductions. The flood forecasting and warning system based on hydraulic models play an important role in flood risk management. This study first establishes river stage routing model based on dynamic wave theory. Then, both the real-time observed river stages and the least squares method are used to adjust the model currently flow conditions as the data assimilation. Finally, The Ensemble Kalman Filter method carries out the data correction with the computation of minimum error-covariance between the model prediction and the observation. The simulation results found the root-mean-square error of forecasted river stage using the data assimilation at the gauged stations of Taipei Bridge and Tudi-Gong-Bi for 1-3 hours lead time is 0.862m, 0.892m, 0.903m, and 0.281m, 0.326m, 0.345m, respectively. When the Ensemble Kalmen Filter is added in the model, the root-mean-square error reduces to 0.191m, 0.375m, 0.612m, and 0.062m, 0.090m, 0.145m at described gauged stations. It is found that the data assimilation and the Ensemble Kalmen Filter give reliable forecast water stages with a small root-mean-square error which successfully corrects the forecasted river stage at each time step of the flood routing process. The results reveal that the integrated model gains a better accuracy of the water-stage profiles with probabilistic uncertainties. The model provides reliable forecasts of the water-stage profiles for 1–3 hours lead time along the Tamsui River for specific locations in emergency response for flood risk management.

How to cite: Hsu, M., Fu, J.-C., Tsao, M.-C., and Kimura, N.: Application of Data Assimilation and Ensemble Kalman Filter for Flood Forecast in Tamsui River, Taiwan, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4300,, 2020.

EGU2020-5296 | Displays | HS1.1.4 | Highlight

Bathymetric mapping in turbid braided mountain streams using SfM-MVS photogrammetry and statistical approaches

Davide Mancini, Gilles Antoniazza, and Stuart Lane

River bathymetric investigation has a long tradition as river-bed morphology is a crucial geomorphological variable that also has implications for river ecology and sediment management. In one sense, this is becoming more straightforward with the development of UAV platforms and SfM-MVS photogrammetry. Mapping inundated and exposed areas simultaneously has proved possible either by adopting two media refraction correction or by using some form of the Beer-Lambert Law. However, both of these approaches rely upon the bed being visible which becomes restricted to progressively shallower zones as stream turbidity increases. Traditional survey techniques to collect bathymetric data for inundated zones (e.g. total station or differential GPS systems) are time consuming and require a trade-off between point density and the spatial extent of survey. In this study we test a simple hypothesis: it is possible to generalize the likely depth of water in a shallow braided stream from basic planimetric information and use such statistical relationships to reconstruct the bathymetry of inundated zones. This is based upon the principle that a suite of planimetric variables (e.g. distance from stream banks, river channel width, local curvature magnitude and direction, streamline convergence and divergence) can be used to model the spatial distribution of water depths. We attempt to do this for a shallow braided river with high suspended sediment concentrations using orthoimages and DEMs derived from application of SfM-MVS photogrammetry to UAV-based imagery. We develop separate calibration and validation relationships to train and to assess the statistical models developed. These are then applied to the stream to produce bathymetric maps of flow depth for integration with SfM-MVS derived data from exposed areas. The method produces a point specific measure of uncertainty and tests suggest that the associated uncertainties are sufficiently low that after propagation into DEMs of difference reliable data on braided river dynamics and erosion and deposition volumes can be obtained.

How to cite: Mancini, D., Antoniazza, G., and Lane, S.: Bathymetric mapping in turbid braided mountain streams using SfM-MVS photogrammetry and statistical approaches, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5296,, 2020.

EGU2020-6483 | Displays | HS1.1.4

A study on turbulence flow and pressure due to hydraulic jump

Seo Hye Choi, Hyung Suk Kim, and Moonhyung Park

The hydraulic jump occurs depending on conditions of upstream and downstream and makes large vortexes in itself of which flow is complex and fluctuates. Recently, the abnormal climate and gain of the impervious area increase the variation in river discharge. It can result in exerting the pressure that is over the acceptable load at the bottom in the downstream of a weir and increasing the fluctuation of the pressure due to the hydraulic jump. Those can provoke damages because of negative pressure, erosion of materials, local scour, and excess of the design load. Thus, this study aims at making use of the design in river-bed maintenance structures such as riprap and an apron considering by the pressure fluctuations. We simulated the hydraulic jump phenomenon through a hydraulic model experiment and examined the relationship between hydraulic factors and the pressure in the range of the hydraulic jump. Specifically, the hydraulic jump is generated by installing a weir upstream in the channel and measured the velocity of the flow by using particle image velocimetry (PIV) and bubble image velocimetry (BIV) to identify the characteristics of turbulence in the section of the hydraulic jump. Also, this study measured the pressure at the bottom along to the flow. As a result, the main factors of the pressure fluctuations are derived by statistical analysis such as determining the correlation between the pressure and the factors. In the subsequent study, it will be suggested to expect the pressure fluctuations at the bottom by using surrounding hydraulic factors in hydraulic jump through an elaborate analysis.



"This work is supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 20AWMP-C140010-03)."

How to cite: Choi, S. H., Kim, H. S., and Park, M.: A study on turbulence flow and pressure due to hydraulic jump, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6483,, 2020.

EGU2020-8858 | Displays | HS1.1.4

ADCP with onboard GPS for streamflow velocity measurement usable for physical models calibration

Thomas Morlot, Pierre Oustriere, Franck Leclercq, and Hélène Scheepers

Human beings always wanted to protect themselves from hazards associated with rivers and streams. Wether we talk about low flow, pollution or flooding, streams very quickly interested scientists and engineers for their wealth and abilities.

EDF (Electricité de France) is a french company dealing with energy production. Dealer or owner operator of electricity production structures, the company is responsible for their operation in safe conditions. Thus, the knowledge of parameters such as streamflow discharge or streamflow velocities is one of its priorities to better respond to three key issues which are plant safety, compliance with reguatory requirements and optimization of the means of production.

The present work consists in showing how to use ADCP (Accoustic Doppler Current Profiler) to accurately measure streamflow volocities in complicated conditions (tide cycle, complex flow, bubbles, factory in operation…). Such device can be coupled with GPS to precisely geolocalize the measured velocities to make them usable for models calibration. By showing a case study, this work aims at underlining how field work using ADCP with onboard GPS can create input data for the adaptation and the calibration of physical models.

How to cite: Morlot, T., Oustriere, P., Leclercq, F., and Scheepers, H.: ADCP with onboard GPS for streamflow velocity measurement usable for physical models calibration, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8858,, 2020.

EGU2020-13153 | Displays | HS1.1.4

Poking holes in discharge time series with photographic evidence

Anthony Michelon, Gilles Antoniazza, Natalie Ceperley, Stuart Lane, and Bettina Schaefli

River discharge is a key variable for hydrological studies and water resource management, but acquiring high-quality measurement remains challenging in mountain environments and in particular for mountain torrents. Extreme discharge variations between summer and winter, negative temperatures and intense sediment transport are the main issues for sensors (that get easily clogged, frozen or stucked out of the water) as well as for cross-section stability (a pre-condition for using a rating curve approach). 
In this presentation, we discuss what we learned from streamflow observations in the experimental Vallon de Nant catchment (13,4 km²), located in the Swiss Alps, which serves as a field laboratory for environmental research, ranging from plant ecology to snow hydrology and sediment transport to stream-C02 exchange with the atmosphere. We discuss here 4 years of optical height gauge records at the outlet (1200 m a.s.l.), obtained from a single VEGA-PULS WL-61 sensor measuring the water height above a concrete trapezoidal shaped cross-section (base width 5.3 m), designed primarily for sediment transport observations (with 10 geophones mounted flush on the concrete weir). There was no low flow channel within the cross-section. At least four other similar gauging stations are currently in use for hydrologic research in Switzerland, with or without low flow channels. The relevance of a discharge quality study at this site is twofold: i) to understand the reliability of flow measurements during low flow and during sediment-influenced high flow events and ii) to compile recommendations for similar discharge observation settings. 

At the Vallon de Nant study site, the absence of a low-flow channel in the weir, combined with the limitation of having a single river stage measuring point resulted in significant over- and under-estimation of the river stage at low-flows, caused by the fluctuation of the river bed position relative to that of the measuring point. Even if the flow covers the entire width of the weir crest, single clast deposits near to the crest can significantly disturb stage observations. We performed a validation of the data using hourly pictures taken during daytime with a low-cost camera at the outlet, and used the photographic evidence to identify periods when the river was partially or totally frozen, sediments were distorting the river stage measurements, and river channelization was occurring below or next to the river height sensor. Concurrent monitoring of temperature, conductivity or turbidity failed to identify these distortions. Consequently, significant error in discharge calculation would arise without a concurrent photographic observation. The key conclusion is that despite the growth of automation in measurements at gauging stations, there remains a need for observation of those stations, and if humans are no longer doing these, other digital technologies such as imaging need to be used instead. Our approach could be extended to night-time situations and locations that will go for extremely long periods without access.

How to cite: Michelon, A., Antoniazza, G., Ceperley, N., Lane, S., and Schaefli, B.: Poking holes in discharge time series with photographic evidence, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13153,, 2020.

EGU2020-18930 | Displays | HS1.1.4

Evidence of long-term improvements in the quality and completeness of UK river flow data

Katie Muchan, Isabella Tindall, Harry Dixon, Stephen Turner, Catherine Sefton, and Jamie Hannaford

Globally, access to hydrometric data of adequate record length, quality and geographical coverage to answer research questions and manage freshwater systems remains a major issue. The UK National River Flow Archive (NRFA) provides stewardship of river flow data from over 1,500 locations across the UK. Data are acquired and displayed as ‘provisional’ in real-time for 500 stations, however the NRFA also undertake a full update to the quality controlled dataset on an annual basis. Upon submission, river flow records are subject to both automated data screening and manual methods of quality control by a team of trained hydrologists to ensure the data disseminated by the Archive to its broad user community are of the highest quality and fit-for-purpose for a range of applications. In the 1990s, an increasing number of gaps in river flow records and emerging declines in data quality resulted in the introduction of a Service Level Agreement (SLA) in 2002 to protect the UK’s hydrometric network and resulting data. Here, we present the results from 15 years application of the SLA system through the use of a set of quantifiable indicators of data quality, completeness and provision. The improvements shown demonstrate the benefits of such a system to the overall utility of the nationally archived river flow data and an example of quality control and performance indicator systems that can be used as a best practice model for other monitoring networks around the world. They also demonstrate one method of helping to ensure hydrological databases provide information of high quality to meet pressing research and water management needs today and into the future.

How to cite: Muchan, K., Tindall, I., Dixon, H., Turner, S., Sefton, C., and Hannaford, J.: Evidence of long-term improvements in the quality and completeness of UK river flow data , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18930,, 2020.

EGU2020-19427 | Displays | HS1.1.4

Quantifying the uncertainty in riverbank erosion for risk-informed river engineering

Eddy Langendoen and Mick Ursic

Riverbank erosion is a ubiquitous, natural process. Typically, it occurs during larger flood events when the applied forces exerted by the flowing water on a bank exceed some erosion-resistance threshold. Riverbank protection may be needed when critical infrastructure is present or planned near eroding banks, which requires the quantification of the risk of infrastructure failure by bank erosion. Similarly, renaturalization of many European streams, for example through removal of bank protection measures, necessitates the quantification of expected river width adjustment. Unfortunately, we have been unable to accurately quantify bank erosion rates to date. Limitations exist in characterizing both the applied and resisting forces. For example, bank roughness co-evolves with erosion, which makes it difficult to adequately resolve the forces acting on the bank material. Bank material erosion-resistance of fine-grained soils varies significantly, that is over orders of magnitude, both spatially and temporally. Moreover, existing techniques to measure bank material erosion-resistance do not always produce repeatable results. As a consequence, existing bank erosion models, such as the widely used Bank Stability and Toe Erosion Model (BSTEM), require extensive calibration and validation. This is often unsatisfactory to river engineering professionals that have to make decisions on where to place bank protection measures and the level of protection required. The decision-making process could benefit from a risk-based analysis that quantifies the uncertainty in calculated bank retreat rate. Recent enhancements to the BSTEM model allow users to input probability density functions of (measured) bank roughness and bank material erosion-resistance properties. A Monte Carlo analysis then quantifies the effects of both variability and uncertainty in these parameters on bank retreat. We will present how the shape of different probability density functions affect the probability density function of bank retreat. Results will be further presented of application of the new model to assist in prioritizing riverbank restoration measures along the Lower American and Sacramento Rivers, CA, USA, to prevent failure of levees that protect the City of Sacramento from flooding.

How to cite: Langendoen, E. and Ursic, M.: Quantifying the uncertainty in riverbank erosion for risk-informed river engineering, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19427,, 2020.

In diverse developments such as hydropower potential assessment, flood mitigation studies, water supply, irrigation, bridge and culvert hydraulics, the magnitude of stream or river flows is a potential design input. Several methods of flow measurement exist; some basic and some more sophisticated. The sophisticated methods use equipment which, although they provide more accurate and reliable results, are invariably expensive and unaffordable by many institutions that depend greatly on flow records to plan and execute their projects. The need for skilled expertise in the use of these equipment and the associated maintenance problems preclude them from consideration in most projects developed and executed in developing regions such as Africa. For countries or institutions in these regions, there is a need for less expensive, but relatively reliable methods for stream or river flow measurement to be investigated; methods that require no equipment maintenance schemes. One such method is the float method in which the velocity of an object thrown in a river is measured by recording the time taken for the object to traverse a known distance and multiplying the velocity by the cross-sectional area of the river or stream. This method looks simplistic, but when flows obtained from it are correlated with those obtained from the more accurate and conventional methods, reliable results can be obtained. In this study, flow measurements were done at 42 different stream sections using the float method and a more reliable and generally accepted but expensive flow measurement method using a current meter. A statistical relationship was then developed between the flows obtained by the two methods by fitting a linear regression model to the set of data points obtained at the 42 locations on several reaches of selected streams in the western area of Freetown.  The study was conducted on streams with tranquil or laminar flow with flow magnitudes in the range of 0.39 m3/s to 4 m3/s in practically straight reaches with stable banks. The material of the stream beds was laterite soil. Thirty-two data sets were used to develop and calibrate the model and the remaining ten data sets were used to verify the model. The current meter method flows were regressed on the float method flows. For a significance level of 5%, the predicted flows of a current meter, given a float method flow, showed a high level of agreement with the observed current meter flows for the tested data set. 

How to cite: Kanu, I.: Stream Flow Measurement: Development of a Relationship between the Float Method and the Current Meter Method, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21719,, 2020.

EGU2020-21212 | Displays | HS1.1.4

Estimation of paleo-discharge of the lost Saraswati River, north west India

Zafar Beg, Kumar Gaurav, and Sampat Kumar Tandon

The lost Saraswati has been described as a large perennial river which was 'lost' in the desert towards the end of the 'Indus-Saraswati civilisation'. It has been suggested that this paleo river flowed in the Sutlej-Yamuna interfluve, parallel to the present-day Indus River. Today, in this interfluve an ephemeral river- the Ghaggar flows along the abandoned course of the ‘lost’ Saraswati River. We examine the hypothesis given by Yashpal et al. (1980) that two Himalayan-fed rivers Sutlej and Yamuna were the tributaries of the lost Saraswati River, and constituted the bulk of its paleo-discharge. Subsequently, the recognition of the occurrence of thick fluvial sand bodies in the subsurface and the presence of a large number of Harappan sites in the interfluve region have been used to suggest that the Saraswati River was a large perennial river. Further, the wider course of about 4-7 km recognised from satellite imagery of Ghaggar-Hakra belt in between Suratgarh and Anupgarh in the Thar strengthens this hypothesis.

            In this study, we have developed a methodology to estimate the paleo-discharge and paleo-width of the lost Saraswati River. In doing so, we rely on the hypothesis which suggests that the ancient Saraswati River used to carry the combined flow or some part thereof of the Yamuna, Sutlej and Ghaggar River catchments. The paleo-discharge of the river would compare with that of some of the large river of the Himalayan Foreland. These alluvial rivers are often called self-formed rivers, as they flow on the loose sediment and are subjected to erosion and deposition of channel bed and banks. The geometry of rivers such as width (W), depth (D) and slope (S) are primarily controlled by water discharge (Q) and catchment area (A). Various functional relationships have been developed to scale the alluvial rivers, which we have used to obtain the first-order estimate of the river discharge of the ‘lost’ Saraswati. A scaling relationship was established between the catchment area-channel width for 31 rivers and catchment area-discharge at 26 different locations on the rivers presently flowing on the Himalayan Foreland from Indus in the west to the Brahmaputra in the East. We found the width and discharge of all the Himalayan rivers scale in a similar way when they are plotted against their corresponding catchment area. Using these regime curves, we calculate the width and discharge of paleochannels of the Sutlej, Yamuna and Ghaggar rivers by measuring their corresponding catchment area from satellite images. Finally, we add the discharge and width obtained from each of the contributions of individual catchments (Yamuna, Sutlej and Ghaggar River) to estimate the paleo width and paleo discharge respectively of the Saraswati River. Our regime curves provide a first-order estimate of the paleo-discharge and paleo-width of the lost Saraswati ~2500 cumec and ~1000 m respectively. We also suggest that the 4-7 km channel width observed earlier on the satellite image corresponds to the channel belt width of the lost Saraswati River.

How to cite: Beg, Z., Gaurav, K., and Kumar Tandon, S.: Estimation of paleo-discharge of the lost Saraswati River, north west India, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21212,, 2020.

The development of new image-based techniques is allowing a radical change in the environmental monitoring field. The fundamental characteristics of these methods are related to the possibility of obtaining non-intrusive measurements even in adverse circumstances, such as high flow conditions, which may seriously threaten the operators’ safety conditions in traditional approaches.

Optical techniques, based on the acquisition, analysis and elaboration of sequences of images acquired by digital cameras, are aimed at a complete characterization of the river instantaneous surface velocity field, through the analysis of a floating tracer, which may be naturally present or artificially introduced. The growing availability of a new generation of both low-cost optical sensors and high-performing free software programs for image processing, is a key aspect explaining the rapid development of such techniques in recent years. The best known optical techniques are the large scale particle velocimetry (LSPIV) and the large scale particle tracking velocimetry (LSPTV).

This work is aimed to analyze and compare the performance of the two most common free software packages based on LSPIV (i.e. the PIVlab and the FUDAA-LSPIV), which use different cross-correlation algorithms. The test is carried out by analyzing several sequences of both synthetic images and real frames acquired on natural rivers under different environmental conditions (with tracers artificially introduced). An image sequences generator has been implemented ad-hoc with the aim to create, under fixed configurations, synthetic sequences of images, simulating uniformly distributed tracers moving under controlled conditions. The various configurations are characterized by different parameterization in terms of: (i) flow velocity (S=slow or F=fast flow conditions, according to a logarithmic transverse flow profile); (ii) tracer particles size (CON= disks of constant diameter; VAR=disks of variable size with given mean diameter); (iii) seeding density per frame (density: low -LD, medium -MD, high -HD).

The synthetic sequences are processed by the two software packages together with the real sequences, analyzing the errors in terms of mean value of the surface velocity field and velocity along a transverse transect, with respect to a benchmark velocity (i.e. that imposed in the image sequence generator for the synthetic sequences and that deriving from the use of traditional sensors, i.e. ADCP, for the real sequences).

How to cite: Pumo, D., Alongi, F., Ciraolo, G., and Noto, L.: On the use of LSPIV-based free software programs for the monitoring of river: testing the PIVlab and the FUDAA-LSPIV with synthetic and real image sequences, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10155,, 2020.

EGU2020-22495 | Displays | HS1.1.4

Conceptualization of an anti-erosion sensing revetment for levee monitoring: experimental tests and numerical modelling

Manuel Bertulessi, Paolo Bianchini, Ilaria Boschini, Andrea Chiarini, Maddalena Ferrario, Nicola Mazzon, Giovanni Menduni, Jacopo Morosi, and Federica Zambrini

Smart levees represent a revolution in the field of embankment monitoring and safety during flood events. A smart levee, intended as the native (or “from scratch”) integration of an engineering structure with sensors and connection systems, provides detailed information on its past, current and future conditions Viz. integrity stress/strain conditions, maintenance state. This gives decision support to the figures in charge for maintenance and surveillance of the embankments, increasing efficiency and, particularly, the degree of protection from flood eventsSensor information can also be mashed up with other information, such as water stage, rainfall, soil wetness offering an useful integrated view of the river context. 

We present here first results of a research project concerning the conceptualization of a sensing anti-erosion revetment for embankments, through the integration of a double-twisted steel wire mesh with an optic fiber cable. The fiber is woven  into the double-twisted sections and is capable to detect the nearly continuous deformation of the meshes caused by stresses exerted in its plane. The sensor sensitivity is enough to record deformation due to (small) shear stresses exerted by eventual overtopping flows, though it can bear (and report) huge deformations typical of quite higher stresses up to thousands of microstrain. 

Several cycles of experiments, jointly with numerical modelling, clearly show the feasibility of such a product line, also showing a good linearity of the smart revetment behavior.

How to cite: Bertulessi, M., Bianchini, P., Boschini, I., Chiarini, A., Ferrario, M., Mazzon, N., Menduni, G., Morosi, J., and Zambrini, F.: Conceptualization of an anti-erosion sensing revetment for levee monitoring: experimental tests and numerical modelling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22495,, 2020.

HS1.2.1 – Pathways & society transdisciplinary approaches towards solving the Unsolved Problems in Hydrology (UPH)

EGU2020-364 | Displays | HS1.2.1 | Highlight

Solving the 23 Major Mysteries in Hydrology: Who Cares and Why?

Daniel Loucks

A recent paper (Bloeschl, et al. 2019) reported on the outcome of a multi-year effort involving over 200 scientists identifying the 23 most unsolved scientific issues facing the hydrologic community today.  The purpose of this exercise was to motivate the hydrologic research community to focus their work on these issues to better understand the major causes of how water behaves in our catchments, watersheds and river basins, often in different ways at various space and time scales, and under the influence of various degrees of human interactions. Aside from the scientific value that this increased understanding might bring, this presentation focuses on two questions: Why and how might this increased understanding be beneficial and who would benefit? In other words, who should care and why? This interactive presentation attempts to provide some answers to these two questions for each of the 23 identified unsolved scientific problems. But in general it is clear much of the impact that humans are having on our environment is driven by how the hydrologic cycle fits in with the needs of humans and our supporting ecosystems. Water in our environment affects the spread of contaminants and pathogens, the energy and food and industrial goods we produce, the ecosystem services we enjoy, and the duration and extent of floods and droughts some endure. Understanding these links and their economic, health, and social consequences will allow us to manage our water resources and their use more effectively, and perhaps even reduce the risks of reaching tipping points that could forever change how we all will live and survive in the future.    

How to cite: Loucks, D.: Solving the 23 Major Mysteries in Hydrology: Who Cares and Why? , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-364,, 2020.

EGU2020-11302 | Displays | HS1.2.1

The community consultation process leading to the compilation of the 23 Unsolved Problems in Hydrology (UPH)

Christophe Cudennec, Berit Arheimer, Günter Blöschl, Maria Helena Ramos, and Elena Toth

This contribution summarizes the steps of, and experiences with, a wide consultation process, led by the International Association of Hydrological Sciences (IAHS) that resulted in a list of 23 major unsolved scientific problems (UPH) in hydrology.

Step 1) Launch of a YouTube video, outlining the purpose of the initiative and its vision.

Step 2) Discussion via a LinkedIn group leading to a total of about 200 contributions and responses.

Steps 3-4) Two ‘in-person’ meetings organised in April 2019 in Vienna: one (Step 3) at the EGU General Assembly (attended by about 60 scientists), in order to solicit additional questions, at the end of which about 260 candidate problems had been compiled; the second one (Step 4) at the Vienna Catchment Science Symposium (VCSS) at the Vienna University of Technology (attended by about 110 scientists), to sort, merge, split, reword and prioritise the proposed questions. Through an iteration of parallel sessions (repeated twice, mixing the participants) and a final plenary voting session, a list of 16 ‘gold‘ and 29 ‘silver‘ questions was identified.

Step 5) Synthesis carried out by a small working group, involving representatives and members of IAHS, IAH, EGU and AGU, to consolidate, interpret and synthesise the questions, as well as to address potential biases in their selection that might have arisen from the composition of the participants at the meetings. The working group also pooled the questions into seven themes for clarity and communication. As a result of the synthesis process, the working group finally listed a set of 23 questions, presented in a community paper with over 200 authors (Blöschl et al., 2019,

The UPH initiative is a proof of concept that this kind of broad consultation process is actually feasible, and is well received by the hydrological scientific community. Thus, equally important as the final list, is the community-level learning process of such a consultation, involving a large number of hydrologists and the four main learned societies in the field.

Consultations such as this could and should be repeated in the future for the benefit of our discipline, since providing common research subjects will increase the coherence of the scientific process in hydrology and promote the co-building of scientific strategies and synergy towards accelerated progress in hydrological sciences and applications.

This PICO presentation gives a short overview of the consultation process and of each of the 23 questions, shares the experiences from the process and proposes some possible future steps.

How to cite: Cudennec, C., Arheimer, B., Blöschl, G., Ramos, M. H., and Toth, E.: The community consultation process leading to the compilation of the 23 Unsolved Problems in Hydrology (UPH), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11302,, 2020.

This work could contribute to solve UPH #1: is the hydrological cycle regionally accelerating/decelerating under climate and environmental change, and are there tipping points (irreversible changes)?

This fundamental question hinges upon the Nature of the hydrologic cycle itself, and for which a geological perspective is needed.  To begin to solve this problem, we thus must have a clear picture of how the water cycle has changed throughout Earth’s History.  However, current narratives of the history of Earth's water cycle lack a coherent description of how life altered water cycling on land. Here I review a body of evidence of plant evolution events in Earth's history and propose how rainfall runoff mechanisms evolved through five key evolutionary phases.  This review reveals that for most of Earth's history, water cycling on land was likely very different from today, with fewer mechanisms available to store water between rainfall events in the critical surface zone, with implications for water availability and surface climate.  A key tipping point occurred during the Silurian-Devonian periods with the greening of the planet. This deep-time perspective illustrates the step-by-step process through which plants optimized the water cycle in which it increased the distribution in space and time, culminating in the development of forests in the late Devonian. Lastly, I review how the past may serve as a key to the future, discussing how the historical perspective illustrates key areas needed to improve our current conceptualization of water availability so that we may better understand and predict changes of water availability during the Anthropocene.

How to cite: Sterling, S.: A new deep-time historical perspective of the terrestrial water cycle that is needed to solve UPH #1: , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10606,, 2020.

EGU2020-19397 | Displays | HS1.2.1

Exploring the existence of hydrological tipping points at the catchment-scale

Fernando Jaramillo, Stefano Manzoni, Anne-Sophie Crepin, Juan Rocha, Lan Wang-Erlandson, Sam Zipper, Tom Gleeson, and Paolo D’Odorico

The identification of tipping points in the water cycle has been recently ranked Nr. 1 in the list of the top 23 unresolved problems in Hydrology by the International Association of Hydrological Sciences (IAHS) and as a priority in the field of hydrology and water resources by several studies. Such daunting task is mainly attributed to the concerns that greenhouse gas emission climate change may tip the water cycle into an unfavorable new state. Up to date, tipping points occurring in complex dynamical systems have been identified across a large set of disciplines. In most proven tipping points, hydrologic variables are always taken as the control variables, as changes in water fluxes and stocks are known to act as stressors of socioecological systems, and the affected aquatic and terrestrial ecosystems as the response variables. The main objective of this study is to explore the existence of tipping points in catchment-scale freshwater availability, that is, the tipping points were the response variable is catchment water storage. We first review the existence of reported tipping points in the field of hydrology and water resources, to establish a coherent framework for the identification of hydrological tipping points. We explore their mathematical existence at the catchment scale by Linear Stability Analysis, illustrating cases with potential functions and bifurcation diagrams. We then explore any possible contribution to the existence of hydrological tipping points by adding complexity to the hydrological dynamic system through the inclusion of sociological feedbacks. We find that even with the inclusion of the moisture feedback of evapotranspiration to precipitation, constant socioecological conditions will most likely not present tipping points of water storage in the catchment. However, the inclusion of socioecological feedbacks does generate tipping points under certain assumptions, even without assuming a moisture feedback between evapotranspiration and precipitation. We hope that this study sheds some light on the existence, conditions, assumptions and characteristics of large-scale hydrological tipping points with long-term implications.

How to cite: Jaramillo, F., Manzoni, S., Crepin, A.-S., Rocha, J., Wang-Erlandson, L., Zipper, S., Gleeson, T., and D’Odorico, P.: Exploring the existence of hydrological tipping points at the catchment-scale , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19397,, 2020.

Long period annual rainfall data series from nine raingauge stations throughout eastern India were analysed. Those data series were for the years 1901 to 1965 for Aijal (Mizoram); 1901 to 1984 for Imphal (Manipur); 1901 to 1986 for Guwahati (Assam), Shillong, Cherrapunji (Meghalaya); 1901 to 1987 for Cuttack (Odisha), Patna (Bihar), Agartala (Tripura), Krishnanagar (West Bengal). Incomplete annual rainfall data were found out by taking average of data of preceding and following years. Each annual rainfall series was divided into modelled period (1901 to 1980 for eight stations except Aijal with 1901 to 1960) and predicted period (data for years left in the series after modelled period for evaluation of the model for prediction of future rainfalls). Each annual rainfall series in the modelled period was first converted into percentage values of the mean annual rainfall and then plotted against year, which showed the oscillations of the historigram about the mean line (Tomlinson, 1987 for New Zealand rainfalls). Such type of characteristic historigrams for all stations showed periodic nature of annual rainfalls throughout eastern India. So, autoregressive integrated moving average (ARIMA) model (Clarke, 1973) was used to evolve a useful model for prediction of future rainfalls. As the ARIMA model was biased for periodicity due to inclusion of both the ‘sin’ and ‘cos’ functions and period length as 12, modelled data series were analysed for polynomial regression. The accepted degrees of polynomials were decided on the basis of analysis of variance (ANOVA). Acceptance of either ARIMA model or polynomial regression was done on the basis of -test. In most of the cases in the observed historigrams the lengths of periods were less than eight years and in some cases those were eight to 12 years and from polynomial regressions in most cases the period lengths varied in between 8 to 12 years, 13 to 22 years and 23 to 37 years; and in rare cases those lengths were 38 years and more. Considering all the limitations in the observed data and 95% confidence interval for ARIMA model, a particular amount of annual rainfall occurred at about 12 years (i.e. almost resembling a Solar Cycle) and that might be concluded after minute analysis of more observed data. Recurrence of flood and drought years can be predicted from such analysis and also by following probability analysis of excess and deficit runs of annual rainfalls (Panda et al., 1996).


Clarke, R.T.1973. Mathematical models in hydrology. FAO Irrigation and Drainage Paper No. 19. FAO of the United Nations, Rome. pp.101-108.

Panda, S.; Datta, D.K. and Das, M.N. (1996). Prediction of drought and flood years in Eastern India using length of runs of annual rainfall. J. Soil Wat. Conserv. India. 40(3&4):184-191.

Tomlinson, A.I. (1987). Wet and dry years – seven years on. Soil & Water. Winter 1987: 8-9. ISSN 0038-0695    

How to cite: Panda, D. S.: Periodic occurrences of annual rainfalls in Eastern India [UPH No. 9 (theme: Variability of extremes) and UPH No.19 (theme: Modelling methods)], EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4004,, 2020.

EGU2020-6126 | Displays | HS1.2.1

Can Continental Models Convey Useful Seasonal Hydrologic Information at the Catchment Scale?

Louise Crochemore, Maria-Helena Ramos, and Ilias Pechlivanidis

Climatic variations can have a significant impact on a number of water-related sectors. Managing such variations through accurate predictions is thus crucial. Continental hydro-climate services have recently received attention to address various user needs. However, predictions for months ahead can be limited at catchment scale, highlighting the need for data tailoring. Here, we address how seasonal forecasts from continental services can be used to address user needs at the catchment scale. We compare a continentally-calibrated process-based model (E-HYPE) and a catchment-specific parsimonious model (GR6J) to forecast streamflow in a set of French catchments.

This work provides insights into UPH 20 (How can we disentangle and reduce model structural/parameter/input uncertainty in hydrological prediction?) by proposing a skill assessment framework that isolates gains from hydrological model forcings and forecast initialisation. Our results show that a good estimation of the hydrologic states, such as soil moisture or lake levels, prior to the prediction is the most important factor in obtaining accurate streamflow predictions in both setups. We also show that the spread in internal model states varies largely between the two systems, reflecting the differences in their setups and calibration strategies, and highlighting that caution is needed before extracting hydrologic variables other than streamflow.

This work also provides insights into UPH 21 (How can the (un)certainty in hydrological predictions be communicated to decision makers and the general public?). Despite the expected high performance from the catchment setup against observed streamflow, the continental setup can, in some catchments, match the catchment-specific setup for 3-month aggregations and when looking at statistics relative to model climatology, such as anomalies. Nevertheless, differences in the setups can result in different uncertainties for variables such as soil water content.

How to cite: Crochemore, L., Ramos, M.-H., and Pechlivanidis, I.: Can Continental Models Convey Useful Seasonal Hydrologic Information at the Catchment Scale?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6126,, 2020.

EGU2020-6111 | Displays | HS1.2.1

Machine Learning is Central to the Future of Hydrological Modeling

Grey Nearing, Frederik Kratzert, Craig Pelissier, Daniel Klotz, Jonathan Frame, and Hoshin Gupta

This talk addresses aspects of three of the seven UPH themes: (i) time variability and change, (ii) space variability and scaling, and (iii) modeling methods. 

During the community contribution phase of the 23 Unsolved Problems effort, one of the suggested questions was “Does Machine Learning have a real role in hydrological modeling?” The final UPH paper claimed that “Most hydrologists would probably agree that [extrapolating to changing conditions] will require a more process-based rather than calibration-based approach as calibrated conceptual models do not usually extrapolate well.” In this talk we will present a collection of recent experiments that demonstrate how catchment models based on deep learning can account for both temporal nonstationarity and spatial information transfer (e.g., from gauged to ungauged catchments), often achieving significantly superior predictive performance compared to other state-of-the-art (process-based) modeling strategies, while also providing interpretable results. This is due to the fact that deep learning can learn, exploit, and explain catchment and hydrologic similarity in ways and with accuracies that the community has not been able to achieve using traditional methods. 

We argue that the results we have obtained motivate a path forward for hydrological modeling that centers around ‘physics-informed machine learning.’ Future model development might focus on building hybrid (AI + process-informed) models with three objectives: (i) integrating known catchment behaviors into models that are also able to learn directly from data, (ii)  building explainable deep learning models that allow us to extract scientific insights, and (iii) building hybrid models that are also able to simulate unobserved or sparsely observed variables. We argue further that while the sentiments expressed in the UPH paper about process-based modeling are common, the community currently lacks an evidence-based understanding of where and when process-based understanding is important for future predictions, and that addressing this question in a meaningful way will require true hybrids between different modeling approaches.

We will conclude by providing two fundamentally novel examples of physics-informed machine learning applied to catchment-scale and point-scale modeling: (i) conservation-constrained neural network architectures applied to rainfall-runoff processes, and (ii) integrating machine learning into existing process-based models to learn unmodeled hydrologic behaviors. We will show results from applying these strategies to the CAMELS dataset in a rainfall-runoff context, and also to FluxNet soil moisture data sets.

How to cite: Nearing, G., Kratzert, F., Pelissier, C., Klotz, D., Frame, J., and Gupta, H.: Machine Learning is Central to the Future of Hydrological Modeling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6111,, 2020.

EGU2020-10001 | Displays | HS1.2.1

Panta Rhei Benchmark Dataset

Heidi Kreibich, Giuliano di Baldassarre, Anne van Loon, Kai Schröter, Philip Ward, Fuqiang Tian, Alberto Viglione, Murugesu Sivapalan, and Günter Blöschl

We tackle the unsolved problem in hydrology “How can we extract information from available data on human and water systems in order to inform the building process of socio-hydrological models and conceptualisations?”

In the framework of the Panta Rhei initiative we compile and analyse a benchmark dataset, which shall be used to calibrate and apply socio-hydrological models. The compilation and analyses of the benchmark dataset will be undertaken as follows: 1) selection of suitable socio-hydrological models; 2) identification of the variables necessary to calibrate and apply the selected models; 3) collection of time series data of the selected variables for as many catchments as possible; 4) calibration and application of the socio-hydrological models; 5) comparative analyses across different models and catchments.

A minimum of two, preferably more socio-hydrological models for floods and droughts shall be selected. Data collection will be undertaken with the support of the Panta Rhei community, particularly the members of the Panta Rhei working groups “Changes in flood risk” and “Droughts in the Anthropocene”. For the socio-hydrological model calibration we plan to follow the example of Barendrecht et al. (2019). This PICO presentation shall be used to discuss and finalise the concept for data compilation and analyses, to promote this initiative and to motivate as many colleague as possible to contribute to the data collection and comparative analyses.

Reference: Barendrecht, M. H., Viglione, A., Kreibich, H., Merz, B., Vorogushyn, S., Blöschl, G. (2019): The value of empirical data for estimating the parameters of a socio-hydrological flood risk model. WRR, 55, 2, 1312-1336. DOI:

How to cite: Kreibich, H., di Baldassarre, G., van Loon, A., Schröter, K., Ward, P., Tian, F., Viglione, A., Sivapalan, M., and Blöschl, G.: Panta Rhei Benchmark Dataset, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10001,, 2020.

EGU2020-7431 | Displays | HS1.2.1

Unsolved problems in hydrology: societal responses to unprecedented events

Maria Rusca, Giuliano Di Baldassarre, and Gabriele Messori

Understanding how different societal groups respond to drought or flood events is one of the unsolved problems in hydrology (UPH), concerning the interfaces with society. More specifically, there is a need to decipher the relationship between potential impacts of unprecedented events, distribution of sociohydrological risk as well as future adaptation and recovery trajectories. In this presentation, we introduce a new analytical approach to answer the question of how contemporary societies might adapt to and recover from unprecedented drought and flood events in an inclusive and sustainable fashion. In doing so, this presentation deepens our understandings of the interface between hydrological extremes and society. Addressing this question requires creating new forms of knowledge that integrate analyses of the past, i.e. historical and political processes of risk and adaptation and the underlying power relations, with hydroclimatic projections of unprecedented events. We thus combine three aspects which have been studied individually, but never integrated: a. scenarios based on social science theories on disaster management; b. case studies of past hydroclimatic events which were unprecedented at the time of their occurrence; c. conceptual transfer across case studies - that is, learning something about potential future unprecedented events at one location by leveraging events which occurred elsewhere. Some of the scenarios developed may already be emerging in current times, whilst others are plausible hypotheses in humanity’s future space. This approach, at the nexus between social and hydrological sciences, has the concrete advantage of providing an impacts-focussed vision of future risk, beyond what is achievable within conventional disciplinary boundaries. 

How to cite: Rusca, M., Di Baldassarre, G., and Messori, G.: Unsolved problems in hydrology: societal responses to unprecedented events, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7431,, 2020.

EGU2020-5221 | Displays | HS1.2.1

Social science for hydrologists: considerations when doing fieldwork with human participants

Sally Rangecroft, Eddie Banks, Rosie Day, Guiliano Di Baldassarre, Theresa Frommen, Yasunori Hayashi, Britta Höllermann, Karen Lebek, Elena Mondino, Melanie Rohse, Maria Rusca, Marthe Wens, and Anne Van Loon

Water is at the core of many current and future global challenges, which involve hydrological, technical and social processes. Therefore, successful interdisciplinary research on how water-related issues interact with human activities, actions and responses is increasingly important. Qualitative data and diverse perspectives provide much-needed information to improve our understanding and management of water-related issues. To collect this information, hydrologists are increasingly conducting fieldwork with human participants (e.g. individuals, policy-makers, community leaders, government representatives, etc.) themselves, and collaboratively with others. Although collaboration between hydrologists and social scientists in interdisciplinary projects is becoming more common, several barriers, including lack of understanding and experience, can result in hydrologists and social scientists remaining somewhat separate during research, leading to suboptimal research outcomes. Hydrologists who are planning and undertaking fieldwork involving human participants may be underprepared because they are unfamiliar with key social science approaches and concepts. Therefore, here, we help guide hydrologists to better understand some important issues to consider when working with human participants, to facilitate more collaborative research.

As a group of social, natural, and interdisciplinary scientists, we discuss a number of important elements of fieldwork involving human participants that hydrologists might be unfamiliar with, or might have different approaches to than social scientists. These elements include good ethical practice, research question frameworks, power dynamics, communication of science (e.g. participatory mapping, photovoice, videography, and interactive graphs), and post-fieldwork reflections. There are also issues to consider when working collaboratively with social scientists, such as vocabulary differences and different methodologies and data collection approaches (e.g. interviews, focus groups, questionnaires, workshops, ethnography).

We believe that by introducing hydrologists (and natural scientists in general) to some of the key considerations when working with human participants in the field, more holistic, ethical, and successful research outcomes can be achieved. We also want to stress that collaboration with social scientists stays important and research ethics, design, participant involvement, and results, may be compromised without the input and experience of social scientists themselves. Facilitating these collaborations between the natural and social sciences will improve interdisciplinary water research, resulting in a better understanding of the interactions between water and society.

How to cite: Rangecroft, S., Banks, E., Day, R., Di Baldassarre, G., Frommen, T., Hayashi, Y., Höllermann, B., Lebek, K., Mondino, E., Rohse, M., Rusca, M., Wens, M., and Van Loon, A.: Social science for hydrologists: considerations when doing fieldwork with human participants, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5221,, 2020.

EGU2020-1485 * | Displays | HS1.2.1 | Highlight

Learning from the past for strategic decision-making in climate risk management: Connecting historic and future adaptation pathways

Thomas Thaler, Philipp Babcicky, Christoph Clar, Thomas Schinko, and Sebastian Seebauer

Hydro-metrological events cause substantial economic damage and social disruption in our society to date. These climate-related risks will become even more severe in the future, driven by changes in the frequency and magnitude of natural hazard events, an increasing exposure of buildings or infrastructure, as well as vulnerability and resilience developments of residents and businesses. Although these long-term developments are of major social and economic relevance, decisions in disaster risk management and their (potential) impacts are typically assessed as singular events and potential alternative solutions, which have not been considered, are out of scope. Recent research therefore suggests to employ the concept of iterative climate risk management (CRM), in order to align disaster risk management and climate change adaptation policy and practice. This is supposed to increase the awareness of how complex and dynamic the challenge of comprehensively tackling climate-related risks is.

Pathways aims to fill this gap by analysing the long-term development of past and future decisions. The arenas in which these decisions are made are characterised by (1) competing interests from various policy areas, (2) ad-hoc decisions often taking precedence over strategic planning for long-term CRM, and (3) previous decisions providing carry-over, follow-up or creating even lock-in effects for later decisions. Focusing on two climate-adaptation regions in Austria (so-called KLAR!-regions), Pathways paints a comprehensive picture of how local adaptation pathways were developed in the past, how these pathways led to specific decisions at specific points in time, and which impacts these choices had on community development with respect to the choices and pathways not taken. Pathways learns from the past to inform the future with the aim to provide capacity building at the local level. By understanding how earlier decisions enabled or constrained the later decisions, pathways offers policy guidance for making robust decisions in local CRM.

Pathways applies a mixed-method approach to integrate quantitative and qualitative social science research methods and to triangulate the research objectives from different perspectives. Semi-structured interviews with key CRM actors at various levels of government, geo-spatial analysis, secondary analysis of census data and archival research jointly inform the reconstruction of past decision points and related pathways. This approach allows to test, compare, confirm, and control the collected data and the interpreted results from different perspectives, while avoiding narrow, oversimplifying explanations. Building on the lessons learnt from the past, future pathways are co-designed with local stakeholders in Formative Scenario workshops. Pathways restricts its scope to climate-related risks from extreme hydro-meteorological events and geological mass movements, such as riverine floods and pluvial torrents, mud and debris flow, landslides or avalanches. This risk domain requires governance structures for immediate response to the disaster as well as for prevention and relief/reconstruction. Pathways aims to improve the knowledge base for respective governance efforts.

How to cite: Thaler, T., Babcicky, P., Clar, C., Schinko, T., and Seebauer, S.: Learning from the past for strategic decision-making in climate risk management: Connecting historic and future adaptation pathways , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1485,, 2020.

The U.S. Geological Survey, through the National Water Census, has produced a near real-time, operational concept map of water availability for the conterminous United States. Currently, this map aggregates “natural” landscape-dimension storage volumes (e.g. soil moisture, snowpack, and surface depression storage) and relates these values to historic averages for a given spatial unit for the given time of year. The purpose of this operational concept map is to improve communication of current water availability to the general public using the best available knowledge and technology. Current operational model deployment is an application of nationally-consistent methods; however, the degree to which regionalization and local knowledge might be applied and interwoven into the national product are current topics of exploration. In addition, future development for this model and visualization process will include adding water quality and water use as variables that contribute to the overall availability of water. Adding these transdisciplinary components to the existing physical model is not straightforward; the differences in model structure and data types needed for specific disciplines will need to be overcome to present a truly integrated water availability estimate that can provide useful information for the public as well as the technical research community. In this presentation, we explore the successes and challenges of the existing operational model used for the National Water Census, including transdisciplinary model integration, calibration, and uncertainty, with the goal of improving communication of water availability.

How to cite: Driscoll, J. M. and Farmer, W. H.: Integrated, operational water availability estimates for the conterminous United States: transdisciplinary data and modeling successes and challenges, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10811,, 2020.

EGU2020-11432 | Displays | HS1.2.1

Co-creation processes of nature based solutions in hydrological modelling – case studies in the UK, Belgium and the Netherlands

Borjana Bogatinoska, Angelique Lansu, Judith Floor, Dave Huitema, and Stefan Dekker

Climate adaptation of brook catchments is much needed in the studied regions of England, Belgium and the Netherlands. With the continuous rise of global temperatures and global change, these regions suffer from the impacts of extreme weather events such as drought and flooding. Extreme weather and climate change impacts are spatially non-uniform, uncertain and can have different strengths at local and regional level. Therefore, cities and regions need to adapt to climate change in an ambiguous way. Accordingly, there is no uniformity in the adaptive capacity of individuals, groups within society, organisations and governments or how they can respond to current and future climate change impacts.

To better understand the interlinkages in nature-based climate adaptation between the socio-economic and climate change drivers, we studied these drivers in the hydrological modelling in 3 pilot studies in the UK, the Netherlands and Belgium. Focus is on how co-creation, defined as active participation is incorporated in the hydrological modelling process, (1) within each brook catchment and (2) between the professionals, as cross border knowledge transfer. Data on the co-creation process was collected with workshops on each of the semi-annual partner meetings of each catchment. Data on the modelling process was collected by semi-structured interviews of the professionals and by using assessment of professional learning in the network (field trips). Findings on co-creation processes of nature based solutions in hydrological modelling will be compared in the UK, the Netherlands and Belgium. In the end, existing co-creation processes will be joined to a framework for co-creation which can be improved and adapted based on the gathered data. This would include: identification of stakeholder groups and their needs, the level of intended participation, the identified climate problem by the stakeholders and by the policy-makers, the planned modelling approach, the NbS etc.

Keywords: climate change, hydrology, nature-based solutions, stakeholders, climate adaptation, framework.

How to cite: Bogatinoska, B., Lansu, A., Floor, J., Huitema, D., and Dekker, S.: Co-creation processes of nature based solutions in hydrological modelling – case studies in the UK, Belgium and the Netherlands, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11432,, 2020.

New and unconventional sources of data that enhance our understanding of internal interactions between socio-economic and hydrological processes is central to sociohydrological modelling. Participatory modelling (PM) departs from conventional modelling tools by informing and conceptualizing sociohydrological models through stakeholder engagement. However, the implementation of most PM processes remains biased, particularly in regions where marginalized communities are present. Most PM processes are not cognizant of differentiation and diversity within a society and tend to treat communities as homogeneous units with similar capabilities, needs, and interests. This undifferentiation leads to the exclusion of key actors, many of whom are associated with marginalized communities. In this study, a participatory model-building framework (PMBF), aiming to ensure the inclusiveness of marginalized stakeholders - who (1) have low literacy, (2) are comparatively powerless, and/or (3) are associated with a minoritized language - in participatory sociohydrological modelling is proposed. The adopted approach employs interdisciplinary storylines to inform and conceptualize system dynamics-based sociohydrological models.The suggested method is underpinned by the Multi-level Perspective (MLP) framework, which was developed by Geels et al. (2002) to conceptualize socio-technical transitions and modified in this study to accommodate the development of interdisciplinary storylines. A case study was conducted in Atitlán Basin, Guatemala, to understand the relationships that govern the lake’s cultural eutrophication problem. This research integrated key stakeholders from the indigenous Mayan community, associated with diverse literacy ranges, and emerging from three different minoritized linguistic backgrounds (Kaqchikel, Tz’utujil, and K’iche’), in the PM activity. The generated model serves as a decision support system for managing nutrient discharge into Lake Atitlán, allowing stakeholders to investigate trends of different policy and management scenarios. The participatory model-building activity helped eliminate the impact of power imbalances in water resources management and empower community-based decision-making.

How to cite: Bou Nassar, J., Malard, J., Adamowski, J., Ramírez Ramírez, M., and Tuy, H.: The use of interdisciplinary storylines to ensure the inclusiveness of marginalized stakeholders in participatory sociohydrological modelling: A case study in Tz’olöj Ya’, Mayan Guatemala, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11178,, 2020.

EGU2020-20035 | Displays | HS1.2.1

Cooperation under conflict: a framework for participatory modeling under severe social and climate change pressures

Anahi Ocampo-Melgar, Pilar Barria, and Cristian Chadwick

Hydrological modeling tools are usually used to obtain broad scale understandings of ecological and hydrological interconnections in a basin. They have also been presented as useful to support collaborative decision processes by visually displaying hydrological systems connections, uncertainties and gaps, as well conflicting preferences over water management strategies. However, many challenges remain at capturing and communicating the complexity of couple human-hydrological systems. The Aculeo basin in Chile is an internationally publicized case due to the disappearance of a 12 km2 lake that leaded to increasing conflicts over water scarcity and the cause of the catastrophe. A traditional hydrological model study and a separate collaborative agreement process were implemented in parallel to find answers and discuss solutions to the water scarcity crisis. The model initially designed to answer a single water balance question, was finally turned in a question-driven socio-hydrological modeling process used to explore a diversity of uncertainties emanating from the collaborative agreement process. Model development and some results of this integration are presented, displaying how science-policy process forces adjusting model structure, challenging official information and searching for alternatives sources and approaches to find answers. This research presents how a hydrological model can be used as a dynamic framework to address poor knowledge on the system behavior, disagreements on the water crisis causes and contradictions on the management options proposed. However, it also shows that participation can be an instance used by stakeholders to question and challenge the rigidity, scope and accuracy of the model information being presented. Therefore, flexible approaches and research agendas should support the exploration of this type of synergies towards more collaboration and production of useful and legitimate socio-hydrological models. 

How to cite: Ocampo-Melgar, A., Barria, P., and Chadwick, C.: Cooperation under conflict: a framework for participatory modeling under severe social and climate change pressures, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20035,, 2020.

HS1.2.3 – The Science-policy interface in hydrology – essentials for more impactful science

This presentation discusses the issue of bridging science, policy, industry and practitioners communities as well as the citizen dimension for enhancing disaster resilience. It focuses on the development and consolidation of the Community of Users (CoU) on Secure, Safe and Resilient Societies, an exchange platform of the European Commission. The CoU is an initiative from DG Home and aims to create a platform to exchange information on research results and policy updates between policy-makers, researchers and end-users on a European, national and regional level. Its motivation lies on the fact that there is a large span of policies and research projects users, leading to fragmentation of information and lost opportunities regarding possible synergies. There is a strong need to boost awareness about research projects and policy developments. Besides, user’s needs are often insufficiently targeted and should be considered in the light of research programming. Links among scientific outputs and policy objectives are often lacking and there is a need to strengthen cooperation and dialogue among the different communities. This presentation will highlight current research programming and perspectives in Horizon Europe and policy implementation.

How to cite: Quevauviller, P.: Bridging science, policy, industry and practitioners communities and the citizen dimension for enhancing disaster resilience, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22290,, 2020.

EGU2020-14173 | Displays | HS1.2.3 | Highlight

Flood emergencies and hydrological science communication

Hannah Cloke

Flood emergencies are a cauldron of politics, media, operational agencies working hard on the ground and of course people’s lives, livelihoods, property and wellbeing put at risk by floodwaters.  Government and humanitarian agencies need to rapidly understand the gravity of a situation and their options to respond. To help them make decisions, and to ensure these decisions are based on evidence and not speculation, they often draft in advisory groups made of up experts in relevant fields. For floods this could include engineers, flood and weather forecasters, agricultural economists or land owners. For a hydrologist, being asked to advise governments in an emergency situation is scary and exciting, but also a wonderful opportunity to put your scientific expertise to use helping people. The key skill in these situations is understanding how and when to speak up. You must speak clearly, use simple language that non-scientists can understand, and you often only have a few seconds to convey your points. You may be faced with opposition, yet you must rely on your training and expertise to make rapid judgements and to point to the best evidence available.  Using real-life examples from flooding crises in the UK, Africa and elsewhere, we will see how it is possible to use scientific skill to directly help people by influencing decisions. By working with governments, emergency agencies and NGOs, scientists can help them to make best use of resources and even save lives.

How to cite: Cloke, H.: Flood emergencies and hydrological science communication, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14173,, 2020.

EGU2020-14093 | Displays | HS1.2.3

science-policy interface: the italian experience

corina angela

Over the last 15 years, in the framework of the Italian early warning system, managed directly by the civil protection authorities, the gap between science and policy have been positively bridged with the Knowledge Centres: a national strategy, with a formal architecture that has build a dialogue between scientific community and responsibility services.
The applied research, tailored on operational user needs, has been funded and supported leading to the development of advanced applications in coupled meteo-hydrological modelling, satellite rapid damage analysis, hydraulic modelling, levees vulnerability estimation etc.
Similar interface models are being created in the European institutions (DRMKC, European Commission) or in the international expert Agencies ( Research Panel, WMO).
The general positive dialogue among science and policy, in a mutual enrichment, is presented in this paper. 

How to cite: angela, C.: science-policy interface: the italian experience, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14093,, 2020.

EGU2020-13929 | Displays | HS1.2.3

Existential crises of riverine eco-systems: an echoing environmental epidemic in Europe and India

Sasi Varadharajan and Gabriela Adina Morosanu

Sand mining is a pressing environmental, ecological and economic problem that has now transcended national borders and regional boundaries. This ongoing challenge for rivers has been in the spotlight of policy makers but, it is yet to be locked under an adequate legislation. The presentation discusses the need for targeted legislation to ensure compliance with the spatial and volumetric limits imposed for sand mining activities, so that the conservation of water and sediment resources and the preservation of the hydro-morphological conditions of the watercourses and geo-morphology of adjacent farm lands and bank bunds can be achieved. In this regard, the analysis of existing regulations across countries is a necessity to arrive at a desirable combat cum conservation framework against the degrading dredging.

The analysis is attempted at an inter-continental level - between the European Union and India; regardless of their dimensionality within the Eurasian space and the extent of potential environmental threats on the entire population, the comparison of Indian and EU legal systems can be justified from various viewpoints. Firstly, it helps in studying the intended and implemented effects of environmental legislations within a Union of internal States (India) and a Union of Countries (EU); the underlying impact-wise distinctions between an innately centralized Domestic system and an International system with space for individuality and Sovereignty of independent States; Secondly, it helps in tracing the legislative progress and environmental reach of domestic statutes and regional agreements that stem from Constitutional mandate and International public morality respectively; Thirdly, it helps in mapping the reasons why a system with numerous sand mining legislations (like the TNMMC rules dating back to 1950s in India) and elaborate Environment Impact Assessment (EIA) guidelines has produced little impact on practical handles than the regional system with fewer soft laws (like the EU Water Framework Directive 60/EC/2000) and faint national innovations.

Since the common goal of both systems is the protection, restoration and enhancement of the health of ecologies, this comprehensive study will complement their efforts; it will stress on the science-policy interface in creating a more impactful legal regime by showcasing country-wise case studies; weighing the advantages and disadvantages of a regional system with greater space for international co-operation and a national system more dependent on internal regulation will benefit the policy makers in improvising and fail-proofing the existing standards and green practices; the consequential hydro-sedimentary and geo-morphological impacts of sand mining can only be avoided by finding the right balance through the study of different systems.

Keywords: Sand Mining, Environmental Impact Assessment, Ecology, Geomorphology, Legislative Practices, the European Union, India.

How to cite: Varadharajan, S. and Morosanu, G. A.: Existential crises of riverine eco-systems: an echoing environmental epidemic in Europe and India, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13929,, 2020.

Over the past 20 years, river water quality in Indonesia has deteriorated enormously. Water quality deterioration continues to increase socio-economic inequality, as it are the most poor communities who live on and along the river. Women are comparatively highly impacted by failing water resources management, but their involvement in decision making processes is limited. As such, the uneven water quality related disease burden in Brantas River Basin widens the socio-economic gap between societal groups. In the Brantas region, cooperation and intention between stakeholders to tackle these issues is growing, but is fragile as well due to overlapping institutional mandates, poor status of water quality monitoring networks, and limited commitment of industries to treat their waste water streams. Currently, an Indonesian-Dutch consortium develops a project which is built on the premise that water problems of our world do not necessarily have to be only a cause of tension, but can also be a catalyst for cooperation. Cooperation is a process that needs active input from all concerned. As such, this project seeks to support a twinned learning process in which science is used to build a trusted information system for policy and decision making in Brantas river basin management. The project focuses on the close links between research processes of data gathering and monitoring and its relevance for societal and institutional actors within river basin management organizations. This twinning between policies and science aims to facilitate learning processes of basin authorities, societal stakeholders, companies and knowledge institutions, as they can profit from each other’s achievements, knowledge and experiences. One of the important issues for this new cooperative partnership is how to develop procedures and routines to monitor water quality in the Brantas river. Participatory data monitoring is among the prime requirements for sustainable river management. An additional dimension of the already challenging issue of data gathering in river management is how to deal with transdisciplinary issues in monitoring, measurements and measures, including research procedures and institutional setup.

How to cite: Ertsen, M.: Water quality policies in the Brantas River Basin, Indonesia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9700,, 2020.