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, https://doi.org/10.5194/egusphere-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, https://doi.org/10.5194/egusphere-egu2020-21587, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-6102, 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, https://doi.org/10.5194/egusphere-egu2020-19810, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-18989, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-13711, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-8446, 2020.

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.

Acknowledgements

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, https://doi.org/10.5194/egusphere-egu2020-5584, 2020.

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, Arduino.cc, 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, https://doi.org/10.5194/egusphere-egu2020-5819, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-21929, 2020.

In the framework of the Small Reservoirs Project (www.smallreservoirs.org), 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, https://doi.org/10.5194/egusphere-egu2020-2953, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-22195, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-8285, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-16516, 2020.

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, https://doi.org/10.5194/egusphere-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, https://doi.org/10.5194/egusphere-egu2020-5295, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-4618, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-22317, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-9020, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-9522, 2020.

 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, https://doi.org/10.5194/egusphere-egu2020-1072, 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, https://doi.org/10.5194/egusphere-egu2020-11759, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-13832, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-324, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-6779, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-8890, 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., https://doi.org/10.5194/hess-2019-289, 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, https://doi.org/10.5194/egusphere-egu2020-17773, 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, https://doi.org/10.5194/egusphere-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, https://doi.org/10.5194/egusphere-egu2020-1760, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-4300, 2020.

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.

Acknowledgement

"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, https://doi.org/10.5194/egusphere-egu2020-6483, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-8858, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-13153, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-18930, 2020.

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, https://doi.org/10.5194/egusphere-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, https://doi.org/10.5194/egusphere-egu2020-21719, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-21212, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-22495, 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, https://doi.org/10.5194/egusphere-egu2020-10606, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-6126, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-1485, 2020.

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, https://doi.org/10.5194/egusphere-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, https://doi.org/10.5194/egusphere-egu2020-11178, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-20035, 2020.

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, https://doi.org/10.5194/egusphere-egu2020-14173, 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, https://doi.org/10.5194/egusphere-egu2020-9700, 2020.

Mediterranean agricultural systems often rely on irrigation, which can cause conflicts with domestic water demand due to limited water resources. Climate change could enhance these conflicts by bringing a drier climate, lowering water availability, while increasing irrigation demands, therefore creating a need for timely adaptation actions. However, the creation of adaptation plans requires the integration of local policy-makers and stakeholders, both to ensure that the plans are adjusted to local physical and social conditions, and to secure investment in the implementation phase. As many are not technical experts in water resources, this integration requires innovative methodologies to ensure that knowledge gained from advanced hydrological methods can be effectively transmitted for use.

These issues were addressed in the climate change adaptation plan for water resources in the Algarve region (southern Portugal), which was co-created between hydrologists and local stakeholders and policy-makers under project CLIMAAA, by using the Dynamic Adaptive Policy Pathways (DAAP) approach to synthetize the results from hydrological modelling of future scenarios.

Future scenarios were simulated from the present until 2100 using a hydrological model, with multiple realizations of climate scenarios RCP4.5and RCP8.5. The results show an increase in water stress conditions, mainly in the RCP8.5 scenario. Future scenarios and potential adaptation measures were discussed with the local policy-makers (regional and municipal water managers) and water users (water utilities, farmer associations). An agreed-upon set of measures was then simulated with the model to assess their effectiveness for adaptation. These results were used to design a DAAP specifically for the water sector in the Algarve.

Policy-makers were then presented with the DAPP, combined with a cost assessment, and selected the most suitable and politically reliable adaptation pathway until 2100. They did not consider socially desirable to decrease irrigation use, and showed a strong preference for measures such as promoting efficient water use and water retention landscapes, which are distributed and incremental, to measures such as wastewater recycling which require a large investment. However, they did consider desalination as a last resort despite the high investment, to be applied in case other measures fail to maintain water stress below an acceptable threshold. In the end, an adaptation plan for water resources was co-created between policy-makers and researchers which strongly reflected local desires and preferences, while ensuring that its effectiveness was assessed with the best available tools; this plan is now in in the review and implementation stage.

How to cite: Nunes, J. P., Dias, L. F., Aparício, B. A., Morais, I., Fonseca, A. L., Pastor, A. V., and Santos, F. D.: Using Dynamic Adaptive Policy Pathways and hydrological modelling to co-create water resource adaptation policies for climate change: a practical example for southern Portugal, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11015, https://doi.org/10.5194/egusphere-egu2020-11015, 2020.

Increasing water scarcity and water-related disasters are key challenges of climate change that every continent is facing today. Southeast Asia and Africa where many developing countries are concentrated in are highly vulnerable to the impact of climate change. Especially, countries sharing river basins and located in coastal regions have been experiencing high levels of water stress mainly due to population growth and climate change. According to a recent UN report, it is estimated that more than five billion people could suffer from water shortages by 2050 because of increased water demand and climate change. In most cases, however, these people who live in least developed countries (LDCs), which have high population densities and high dependence on primary industry such as agriculture, forestry and fishing required for continuous water supply and efficient water management systems, have been already suffering from extreme levels of water stress but have less capacity and fewer resources to adapt or cope with this extreme condition. Therefore, in this study, impacts of climate change on the global water resources and water-related disasters were reviewed and analyzed in the context of the UN Climate Change Conference COP25, which was held in Spain from 2 to 13 December 2019 and discussed the most important and sensitive issues with regards to climate change adaptation and greenhouse gas mitigation among invited delegates and participants representing 197 countries.

Acknowledgements

This research was carried out as a part of “Development of the Global Water Atlas for responding to climate change project (grant number 20190404-001)” funded by the Ministry of Science and ICT, South Korea.

How to cite: Kim, Y.: Review and analysis of the global water issues in the context of COP25, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1693, https://doi.org/10.5194/egusphere-egu2020-1693, 2020.

Hydrologic research generates massive volumes of peer-reviewed literature across a plethora of evolving topics and sub-topics. It’s becoming increasingly difficult for scientists and practitioners to synthesize and leverage the full body of scientific literature. Recent advancement of computational linguistics, machine learning, including a variety of toolboxes for Natural Language Processing (NLP), help facilitate analysis of vast electronic corpuses for a multitude of objectives. Research papers published as electronic text files in different journals offer windows into trending topics and developments, and NLP allows us to extract information and insight about these trends. 

This project applies Latent Dirichlet Allocation (LDA) Topic Modeling for bibliometric analyses of all peer-reviewed articles in selected high-impact (Impact Factor > 0.9) journals in hydrology (Water Resources Research, Hydrology and Earth System Sciences, Journal of Hydrology,  Hydrological Processes, Advances in Water Resources, Hydrological Sciences Journal, Journal of Hydrometeorology). Topic modeling uses statistical algorithms to extract semantic information from a collection of texts and has become an emerging quantitative method to assess substantial textual data. After acquiring all the papers published in the aforementioned journals and applying multiple pre-processing routines including removing punctuations, nonsensical texts, stopwords, and tokenizing, stemming, lemmatization etc., the resultant corpus was fed to the LDA model for ‘learning’ latent intellectual topics. We achieved this using Gensim, an open-source Python library widely used for unsupervised semantic modeling with LDA. The optimal number of topics (k) and model hyperparameters were decided using coherence and perplexity values for multiple LDA models with varying k.  The resulting generated topics are interpretable based on our prior knowledge of hydrology and related sub-disciplines. Comparative topic trend, term, and document level cluster analyses based on different time periods, journals and authors were performed. These analyses revealed topics such as climate change research gaining popularity in Hydrology over the last decade. 

We aim to use these results combined with probability distribution between topics, journals and authors to create an interactive ontology map that is useful for research scientists and environmental consultants for exploring relevant literature based on topics and topic relationships. The primary objective of this work is to allow science practitioners to explore new branches and connections in the Hydrology literature, and to facilitate comprehensive and inclusive literature reviews. Second-order beneficiaries are decision and policy makers: the proposed project will provide insights into current research trends and help identify transitions and argumentative viewpoints in hydrologic research. The outcomes of this project will also serve as tools to facilitate effective science communication and aid in bridging gaps between scientists and stakeholders of their research.

How to cite: Rahman, M., Nearing, G., and Frame, J.: Hidden Stories in Hydrologic Literature: An Interactive Topic-Based Ontology, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-882, https://doi.org/10.5194/egusphere-egu2020-882, 2020.

Despite billions of dollars of investments in disaster risk reduction (DRR), data over the period 1994- 2013 show natural disasters caused 1.35 million lives. Science respond with more timely and accurate information on the dynamics of risk and vulnerability of natural hazards, such as floods. This information is essential for designing and implementing effective climate change adaptation and DRR policies. However, how much do we really know about how the main agents in DRR (individuals, businesses, government, NGO) use this data? How do agents behave before, during, and after a disaster, since this can dramatically affect the impact and recovery time. Since existing risk assessment methods rarely include this critical ‘behavioral adaptation’ factor, significant progress has been made in the scientific community to address human adaptation activities (development of flood protection, reservoir operations, land management practices) in physically based risk models.

This presentation gives an historic overview of the most important developments in DRR science for flood risk. Traditional risk methods integrate vulnerability and adaptation using a ‘top- down’ scenario approach, where climate change, socio economic trends and adaptation are treated as external forcing to a physically based risk model (e.g. hydrological or storm surge model). Vulnerability research has made significant steps in identifying the relevant vulnerability indicators, but has not yet provided the necessary tools to dynamically integrate vulnerability in flood risk models.

However, recent research show novel methods to integrate human adaptive behavior with flood risk models. By integrating behavioral adaptation dynamics in Agent Based Risk Models, may lead to a more realistic characterization of the risks and improved assessment of the effectiveness of risk management strategies and investments. With these improved methods, it is also shown that in the coming decades, human behavior is an important driver to flood risk projections as compared to other drivers, such as climate change. This presentation shows how these recent innovations for flood risk assessment provides novel insight for flood risk management policies.

How to cite: Aerts, J.: Limits to natural disasters management: the influence of human behavior, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5551, https://doi.org/10.5194/egusphere-egu2020-5551, 2020.

Floods are one of the costliest natural hazards worldwide, affecting millions of people every year. To plan flood risk reduction strategies, there is a need to understand how risk changes over time. In traditional flood risk assessment, vulnerability is often unrealistically considered constant in time, which does not reflect patterns observed in the real world. The coupled human and natural flood system is complex and determined by two-way interactions between the two subsystems. Floodplain dynamics may affect human behavior (e.g. by triggering the implementation of protection measures at different scales) which changes exposure and vulnerability, while they are also in turn influenced by human activities (e.g. land-use changes or flood protection structures). Here we explore how these two-way interactions influence changes in flood risk over time, with a focus on the role of individual and governmental decision-making, by developing a coupled agent-based and hydraulic modelling framework.

In our framework, household agents are located in a floodplain protected by a levee system. Individual behavior is based on Protection Motivation Theory and it comprises (as a response to floods) the options to do nothing, invest in private flood protection measures, or file a complaint to the government. The governmental decision making process about the implementation of technical flood protection measures, i.e. reinforcing the levee system, is a compromise between a Cost-Benefit-Analysis and relative number of filed complaints from the households. The agents take decisions at every time step of a long time series of annual maximum water levels: in case of levee breach, the floodplain water level is estimated by the LISFLOOD 2D hydraulic model, which is dynamically coupled into the agent-based model.

We show that this coupled model is capable of replicating adaptation and levee effects, which have been empirically observed by several scholars in numerous floodplains around the world. Thus, our framework provides a useful explanatory tool for assessing different spatial and temporal dynamics of flood risk in a socio-hydrological system. Moreover, the new modelling approach can explicitly simulate the spatial distribution of flood risk which allows for the analysis of conflicting interests in neighbouring communities. First, efforts have been made to include farmer agents into the model to simulate conflicts between urban and rural areas. Further, we exploit data from the real word in order to assess the credibility of our model and, lastly, use the model to investigate the effects of different climate scenarios on these types of conflicts.

How to cite: Michaelis, T., Brandimarte, L., Di Baldassarre, G., and Mazzoleni, M.: Capturing flood risk dynamics with a coupled agent-based and hydraulic modelling framework, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2659, https://doi.org/10.5194/egusphere-egu2020-2659, 2020.

Increased urbanization is causing evident negative consequences on the hydrological cycle. In particular, the increase of impervious surfaces is having a strong impact on the water cycle, amplifying the risk of urban floods. These impacts can get even worse for potential climate change impacts. The urban areas of the Simeto Valley, the largest river valley in Sicily (Italy), has been repeatedly hit by heavy rains in the last decades that caused urban flooding causing several problems and, in some instances, threats to population. The threats seem to derive also from a low awareness of the population on the correct behavior to have in potentially dangerous situations. Hence, it seems of key importance that residents develop and internalize a “culture of risk awareness”. The Life SimetoRES Project represents an opportunity to stimulate the development of a responsible and resilient community and at the implementation of best practices for storm water management. In the Simeto River Valley community has started in the recent decades to formally have an identity (for instance, by signing a River Agreement) and has already supported initiatives in the responsible and participatory co-management of the territory. Thus, this Valley represents an excellent context to investigate this problem and to understand the involvement of the citizens in solving climate change and urban floods. In order to maximize the effectiveness of the communication campaigns and the actions to safeguard the community, a study through a survey on the climate change and risk perception in 11 municipalities has been carried out, collecting 1143 answers. Starting from the current hydrogeological risk, quantified by the Flood Risk Management Plan, the goal was to identify the perception and the awareness of the citizens. A section of the questionnaire involved the direct experience of the residents during rain events, their relationship with the alert system and their knowledge of the correct behavior in case of flood. Finally, the survey investigated the willingness of citizens to implement adaptation actions in their own municipality and in their homes. The results show that over 52% of citizens is not aware of the real use of the infrastructures devised for urban drainage and only the 30% feels responsible about mitigation of flooding risk. Inaccurate weather warnings can endanger more inhabitants who don't trust the alert system. The results show that it is necessary to make incisive actions to educate people, especially in school age, on the correct behavior to take in case of urban flooding, and encourage citizens to acknowledge themselves as an active part of the mechanism of their own and community safety.

How to cite: Nanni, P., Musumeci, R. E., Peres, D. J., and Cancelliere, A.: Community awareness of climate change and urban flood risk: the case of the Simeto River Basin, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5764, https://doi.org/10.5194/egusphere-egu2020-5764, 2020.

Flooding is globally one of the most damaging natural hazards. Flood risk will most likely increase in the near future due to increases in flood frequency attributed to climate change and growth in population and wealth in flood prone areas. This growth in wealth and population is increasingly considered as a major driver for the increase in flood losses in the last decades. Floodplains are susceptible to floods, but historically people have always been settling in floodplains. The growth of population in floodplains, which is a substantial cause for increased flood risk, is essential to consider for decision making in floodplain development, as improper development increases flood exposure and aggravates flood risk. The science of socio-hydrology tries to capture the interaction between humans and floods in the floodplain, but it is necessary to identify these mechanisms on a broader scale. A way of doing this, is to look at the development of floodplain population density over the years, but population data is not available on a long temporal scale. Therefore, Nighttime light data was used to model the gaps in the availability of population data. Nighttime light data captures the illumination on earth and is available on a large temporal and spatial scale. It also has a high correlation with population data. However, the relationship between Nighttime light data and population data is not straightforward. This study tries to model a population proxy using Nighttime light data and explains when and why it does or does not work. Validation of the model shows that in some regions the predicted data is relatively precise, but ultimately, due to the lack of data, the accuracy is unknown. This study shows that understanding the behavior of NTL is valuable, because it has the potential to map Socio-Economic variables in data-scarce areas.

How to cite: Verschuren, L., Nardi, F., Bricker, J., Hoes, O., Ceola, S., and Pande, S.: Explaining the pitfalls of quantifying population in riverine floodplains using Nighttime Light, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21382, https://doi.org/10.5194/egusphere-egu2020-21382, 2020.

As one of the major weather-driven natural disasters, droughts exhibit as the most frequent and widespread natural disasters in China. It is reported that the agriculture losses show continuously grown by following the increasingly severe droughts for the whole country. In order to investigate the impacts of drought on agricultural, we rechecked the functional relationship between the crop yield and climatic variables. Based on the meta-analysis from previous literature, we found a more stable statistical relationship between the yield and the precipitation and evapotranspiration. These results introduce a new drought index, indicated as Crop Water-Related Index for Drought (CWRID), which can be used as a reference index to approximate the drought impact on the loss of yield. Based on the climatic data in China during 1982-2015, several other drought indices (SPI, SPEI, CI, and SEDI) were compared with CWRID to identify the most appropriate agricultural drought index. The data of historical drought damaged area and drought damaged crop yield reduction were used to validate the performances of different indices. The CWRID reasonably predicted the drought damaged area as well as the drought damaged yield reduction during the past 30 years in China. As a contrast, the SEDI is proved to be no suit for quantifying drought. Also, the calculated values are stored in the dataset and can be shared with researchers by request. As a simple index, results indicated that CWRID can be used to quantify the impacts of drought on agricultural as it can reflect the variation of crop yields.

How to cite: sun, H. and Chen, J.: An index to quantifying the impacts of agricultural drought and its application in China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1041, https://doi.org/10.5194/egusphere-egu2020-1041, 2020.

There are evidences that climate change as a result of both natural and anthropogenic processes has exacerbated the frequency and the severity of flood hazards over past decades across the world. Moreover, changes in the pattern of precipitation and temperature during the 21^st century are expected to induce region-specific impacts on floods, especially increase in local floods in some catchments. However, the future is hard to predict as there are strong discrepancies in how climate change is expected to affect runoff and river discharge at different places. Many studies have proven that not only climate, socio-economic and physical factors such as elevation and soil type are determinant for flood risk characterisation. Anthropogenic activities and impacts through land use and land cover degradation have substantial implication for hydrological processes. Moreover, catchment management play an important role in sustainable flood management which is generally based on technical knowledge. But it must also be socially and politically meaningful. This is especially relevant for transboundary catchments where riparian countries might offer different economic, social and political environment, and hence have distinct approaches of flood risk reduction and management. An effective cooperation between states sharing transboundary water resources must include a continuum comprised of data exchange, information sharing, collaboration and joint action. It is a search for cooperative management while respecting the sovereignty of each state. There is a variety of methods used for assessing transboundary management and identifying cooperative strategies. Among others, the following ones can be mentioned: the Water Cooperation Quotient, the multiobjective analysis, hydropolicy simulation models, the Multiobjective Evolutionary Algorithms (MOEAs) and a combination of the two later. Hence this study aims at exploring various approaches of transboundary management and analyses experienced over the world. Lessons will afterward be drawn in the context of climate and land use change in the transboundary Mono River catchment shared by the Republics of Benin and Togo.

How to cite: Houngue, R., Evers, M., and Almoradie, A.: Impacts of Climate and Land Use Change in the Management of a Transboundary Basin- Case Study of Mono River catchment, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1145, https://doi.org/10.5194/egusphere-egu2020-1145, 2020.

The presented paper examines current dilemmas in transboundary water interaction and debates about the reconceptualization of the Transboundary Water Interaction Nexus (TWINS). The new TWINS framework provides a theoretical alternative how to (1) evaluate the interstate relations between two or more actors regardless their legal status; (2) calculate the transboundary water interaction based on process tracing analysis rather than milestone analysis; (3) distinguish more intensities of cooperation and conflict, (4) clarify broader hydropolitical context in transboundary water interaction, and (5) debate about dual water event phenomenon where one event may possess both cooperation and conflict features. Currently, the new TWINS model serves as an indicator for evaluating cooperation and conflict intensity of water-related events in the Lancang-Mekong River Basin. The data are then recorded in the Lancang-Mekong Cooperation and Conflict Database (LMCCD) designed by authors which already comprise more than 1600 water-related events in the last 30 years (1990-2020). To proof the viability of the presented concept, we will illustrate the new TWINS model on a case study related to the Xayaburi hydropower dam. Although there are still several methodological limitations, the new TWINS model can be adapted to any interstate water-related issue and be able to fill the information gaps about the interdisciplinary understanding of the transboundary water interaction.

How to cite: Grünwald, R., Feng, Y., and Wang, W.: Lost in the waters: contemporary dilemmas in examining transboundary water interaction, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7040, https://doi.org/10.5194/egusphere-egu2020-7040, 2020.

The river Maltsch / Malše is an interesting waterbody from a historical, hydrological and ecological perspective. As a border river between Austria and the Czech Republic, it has had an eventful history. With the political separation into “East” and “West” in the middle of the 20th century, a region that initially had a similar land use structure was completely changed. On the Czech side, villages and settlements were removed and the land expropriated. In the course of the fall of the Iron Curtain, the land was mostly sold to large landowners. Changes also took place on the Austrian side. Agriculture and forestry have been intensified over decades.

This leads to the situation that on both sides of the river, under very similar geological and hydrological conditions, the effects of very different land use developments and changes on the water household and erosion can be documented. Thus, a transboundary, mainly EU-funded INTERREG project was launched to investigate this variability in general and to address the implications for the sediment regime in such river systems (concerning e.g. flood protection control, sedimentation of reservoirs) in specific. Moreover, it is examined how mitigation measures for water retention, erosion control and climate change adaption can be planned under these variable boundary conditions. Especially droughts and heavy rainfall events must be considered as threats in the region in the future.

In addition to the changes described above, the political situation in the border region has left a refuge for nature. The Maltsch is part of the so-called Green Belt that stretches across the whole of Europe. A key species of the region is the Freshwater Pearl Mussel (Margaritifera margaritifera), which is characterised by its very high demands on the environment. It, therefore, serves very well as an indicator / umbrella species and thus also as a condensation nucleus of the different topics of the project.

In summary, the following aspects will be presented: (1) documentation of historic, political driven land use changes and land use differences on GIS basis, (2) effects on soil erosion by means of modelling via USLE, (3) estimation of the effects on the landscape hydrology and (4) effects on the aquatic fauna, especially the key species Freshwater Pearl Mussel.

How to cite: Höfler, S., Ringler, G., Gumpinger, C., and Hauer, C.: Land use changes at the former “Iron curtain” and their implications for catchment hydrology, erosion and ecology – a transboundary project between Austria and Czech Republic, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9012, https://doi.org/10.5194/egusphere-egu2020-9012, 2020.

Extreme dry conditions occurred over the summer of 2018 in the Netherlands. This severe drought event led to very low groundwater  and surface water levels. These impacted several sectors like navigation, agriculture, nature and drinking water supply. Especially in the Pleistocene uplands of the Netherlands, the low groundwater levels had a large impact on crop yields and biodiversity in nature areas. Projections show that droughts with this severity will occur more often in the future due to changes in climate. To mitigate the impact of these drought events, water management needs to be altered.

In this study, we evaluated the 2018 drought event in the sandy regions of the Netherlands and studied which measures could be most effective to mitigate drought impact. We have included meteorological, soil moisture and hydrological drought and the propagation of the drought through these types. Droughts were determined with standardized indices (e.g. Standardized Precipitation Index) and the variable threshold level method. Investigated measures were, for example, higher water levels in ditches, reduced irrigation from groundwater, and increased water conservation in winter. We also studied the timing of these measures to determine the potential for mitigating effects during a drought versus the effectiveness of long term adaptation. The measures were simulated with the agro-hydrological Soil–Water–Atmosphere–Plant (SWAP) model for several areas across the Netherlands for both agricultural fields and nature sites.

As expected, decreasing irrigation from groundwater reduced the severity of the hydrological drought in the region. Severity of the soil moisture drought also decreased in fields that were never irrigated due to the effects of capillary rise from the groundwater, but, as expected, increased in currently irrigated fields. Increasing the level of a weir in ditches had a relatively small effect on the hydrological drought, provided water was available to sustain higher water levels. This measure is, therefore, better suited as a long term change than as ad hoc measure during a drought. The effectiveness of the measures depended on the characteristics of the regions; for some regions small changes led to increases in groundwater levels for several months, whereas in other regions effects were lost after a few weeks. This study gives insight into the most effective measures to mitigate drought impacts in low-lying sandy regions like the Netherlands.

How to cite: van Huijgevoort, M. H. J., de Wit, J. A., and Bartholomeus, R. P.: Evaluation of 2018 drought and effectiveness of adaptation measures in the Netherlands, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9166, https://doi.org/10.5194/egusphere-egu2020-9166, 2020.

It is widely recognized that urbanization has a significant impact on streamflow characteristics. However, the influences of economic development, increasing population and positioning of urban development on streamflow regimes is still not fully understood. This study aims to clarify these influences by analyzing 134 catchments in China and 1064 catchments in the United State. Urbanization metrics were derived from gridded GDP dataset, gridded population dataset and land use/land cover datasets, while the streamflow characteristics were calculated using annual streamflow and mean daily discharge data. The statistical analysis indicated that the rate of change in rainfall-runoff ratio is positively related to the growth rate of GDP and urban area both in China and the U.S., but this relationship was not found in population growth rate. Increasing the extent of urbanized area increased high and low flow frequency in Kansas metropolitan region as well as San Antonio metropolitan region, while reduced low flow frequency in Atlanta metropolitan region. In addition, urban expansion also enhanced streamflow flashiness. Compared to down-stream development, up-stream development increased high flow volume in Atlanta metropolitan region and Kansas metropolitan region, while decreased high flow volume in San Antonio metropolitan region and low flow volume in all study metropolitan regions. The findings in this study provide a sight for future researches in hydrological variation due to urbanization.

How to cite: Shen, Q. and Cong, Z.: Analyzing the Impacts of Urbanization on Watershed Streamflow Characteristics, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9245, https://doi.org/10.5194/egusphere-egu2020-9245, 2020.

Transboundary water problems are complex systems, which involve interdependence and interconnectedness between elements, uncertainty and feedbacks between processes, and emergence and adaptation through evolution of the systems. There is nearly no way to formulate transboundary water problems in an equation fitting-one-size-for-all. As nature-human coupled systems, transboundary water problems should consider actual stakeholders and parties in context-specific situations as well as natural conditions.

News media are good recorders for us to have an insight into the transboundary water problems down-to-earth. Local news media are the first-hand and direct reflections of societal values among the riparian countries and stakeholders, and are documentaries of what is going on in transboundary river basins. International news media are also good sources to know about how people in the world perceive transboundary river issues from the perspectives as “outsiders”. Therefore, text analysis of news articles concerning conflict and cooperation on transboundary river basins can tell us a whole story about the past history and on-going “real” life in the basins.

To uncover the patterns and dynamics of conflictive and cooperative events on a global scale, people usually read news articles, extract information manually in the past, which is tedious and time-commanding. In the era of big data, we collect large news media datasets automatically, and employ machine learning techniques to do data mining out of those news media data. The aim of our research is to minimize manual labor in searching, filtering, reading and understanding the related news media articles by computer, and to provide potent tools for researchers to retrieve useful information  in the related areas. To validate our methodology, we look Mekong River Basin and Brahmaputra River Basin as case studies into details. To apply our methodology in a global scale, we intend to draw a world map with a timeline to show how water conflict, and cooperation occurs, grows, and transforms. By capturing characteristics of the life cycles of water conflict and cooperation, we aim to throw light upon water management in transboundary river basins, provide some hints for water resources decision-makers, and enhance global water security.

How to cite: Guo, L., Tian, F., Wei, J., and Lu, Y.: Conflict and Cooperation Analysis on Transboundary River Basins Using News Media Text Mining Approach , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13100, https://doi.org/10.5194/egusphere-egu2020-13100, 2020.

In many regions of the world, water supply is threatened by natural hazards such as floods and droughts, as well as by shocks induced by anthropogenic changes to water use. Lack of anticipation and/or preparation for these events can lead to delayed or insufficient responses to sudden or developing water crises, that sometimes can produce irrecoverable damage to the environment. In this work, a socio-hydrological approach to sustainable water resources management of the Alcantara River Basin in Sicily (Italy) is adopted that explicitly takes into account feedbacks between the natural and the human components that might arise from shocks to the water management system, including possible evolution of policy responses. The Alcantara River Basin is a groundwater-fed catchment which supplies many villages on the Ionian coast up to Messina city, mainly through the Alcantara aqueduct, but also agricultural areas and industries, including hydropower plants. It also hosts the Alcantara Fluvial Park, an important natural reserve. The Alcantara aqueduct also supplied the city of Messina during a temporary failure of its main aqueduct caused by a landslide in October 2015. The main purpose of the work is to use the socio-hydrological model as a “screening tool” to frame water resource management issues in a broad way and provide guidance to the community to identify aspects of societal behavior that need to evolve towards sustainable water resource management in order to withstand future shocks. This has been done by scenario simulations in conditions of a natural shock affecting the system (i.e. drought) and of a human-induced one (i.e. increase in groundwater extraction). Sensitivity analysis of the model social parameters revealed how the value attributed by the society to the environment and water resources use, its capacity to remember previous water crises and, in particular, its previous responses to shocks, can affect the system in a way that can produce paradoxical effects. Results show how a rapid decision-making strategy that may work in the short term, can be counter-productive when viewed over the long term and how a do-nothing decision during a water crisis could be highly damaging to the environment. For the above-mentioned reasons, this socio-hydrological approach can be considered as a useful tool to understand human-water dynamics and to support decision-makers in water resource management policies with a broad and long-term perspective.

How to cite: Borzì, I., Sivapalan, M., Bonaccorso, B., and Viglione, A.: Effects of Interactions Between Society and Environment on Policy in Water Resources Management: Exploring Scenarios of Natural and Human-Induced Shocks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17936, https://doi.org/10.5194/egusphere-egu2020-17936, 2020.

Improving water use efficiency in agriculture is a key strategy in reducing water scarcity, especially during drought seasons. However, the benefits of these water saving strategies can be reduced if farmers switch to more profitable and water consuming crops or increasing irrigable area, i.e. rebound effects. These feedbacks will likely offset the water savings benefits and subsequently intensify agricultural water use. Here we propose a new system dynamic model that represents the interactions and feedback loops between hydrological and social processes to explore rebound effects by analysing competing water needs for both urban and agricultural allocation. The model is then used to explore the dynamics of different mitigation policy options to alleviate the phenomenon: (i) Restricting water allocation (ii) Limiting size of agricultural land (iii) Changing cropping patterns (iv) Deficit irrigation.

How to cite: Odongo, V., Di Baldassarre, G., and Mazzoleni, M.: Conceptualizing trade-offs of water conservation strategies and unintended consequences using a system dynamics approach, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19092, https://doi.org/10.5194/egusphere-egu2020-19092, 2020.

Catchments are complex dynamical systems exposed to highly-variable inputs (rainfall). Despite this complexity, it is uncommon to model these systems as stochastic ones. Previous works offer a large number of examples where deterministic (conceptual or physics-based) models are used to describe hydrological basins in spite of the fact that, in some cases, the output of the model shows substantial deviations from the observed data even after meticulous calibration.
There are different ways to include stochasticity in the hydrological modeling of catchments. With this contribution we explore a systematic way to improve our knowledge of the system at hand by using time-dependent parameters, which are driven by suited stochastic processes. The fundamental idea, which dates back to seminal works carried out about ten years ago, is to correlate the evolution of the selected time-dependent parameters to catchment features, input variables, or possible changes over time within the catchment area, to improve the structure of the model in a data-driven fashion, rather than to merely resort to including a bias term on the output of the model.
In doing so for different catchments, we make use of a newly-developed inference framework called SPUX, which is particularly suited to deal with non-linear stochastic models as it enables the usage of high-performance computing clusters for (Bayesian) inference coupled with the particle filter method. This allows us to explore and show our approach at work on different settings, such as models of different complexity and data-sets of different resolutions, lengths, and relevant to catchments with different characteristics, which have (or not) changed over time.

How to cite: Bacci, M., Fenicia, F., and Sukys, J.: Stochastic time-dependent parameters to improve the modeling and characterization of catchments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10073, https://doi.org/10.5194/egusphere-egu2020-10073, 2020.

The authors explore uncertainty associated with the quantitative precipitation forecasts (QPF) and its implication to the predictability of real-time streamflow forecasts. Including rainfall forecasts into real-time streamflow forecasting system extends the forecast lead time. As rainfall is a key driver of rainfall-runoff models both past and future rainfall estimates should be used in streamflow and flood forecasting. Since both QPE and QPF are subject to substantial uncertainties, questions arise on the trade-off between the time horizon of the QPF and the accuracy of the streamflow forecasts. Particularly QPF is notorious for its significant uncertainty with respect to location, timing and magnitude. Operational hydrologic services often limit their use of the QPF to one or two days into the future. The authors study this problem systematically using operational models and QPF. Their focus is on scale-dependence of the trade-off between the QPF time horizon and streamflow accuracy. To address this question, the authors first perform comprehensive independent evaluation of QPF at about 140 basins with wide range of spatial scales (10 - 40000 km2) corresponding to U.S Geological Survey (USGS) streamflow monitoring stations over the state of Iowa in Midwestern United States. High Resolution Rapid Refresh (HRRR) is an hourly short-medium range rainfall forecast of up to 18 hours updated every hour with spatial resolution of about 3 km by 3 km. Six-hourly rainfall forecasts are available for up to seven days ahead. Since basins are hydrologically relevant, the authors perform HRRR skill verification for the years 2016-2019 using conventional verification techniques and mean areal precipitation (basin scale rainfall volume) with respect to multi-radar

multi-sensor (MRMS) QPE (gauge-corrected) rainfall. The authors show that the QPF errors/uncertainties are scale-dependent. The QPF skills show increase as the basin scale and lead time of the forecast increases at short-medium range. In the second part of the study, both QPE and QPFs are forced separately to the hydrologic model called hillslope-link model (HLM) used at the Iowa Flood Center for real-time streamflow forecasting for Iowa. The objective is to understand the contribution of QPF uncertainty structure on the skill of streamflow forecasts. Since real-time streamflow observations (15 minutes resolution) are available at USGS sites, the authors incorporate them using a simple data assimilation framework. Several scenarios of forecasts, such as open-loop combined with QPF, persistence-based approach (using streamflow observations) combined with QPF, and open-loop combined with QPF for more than 18 hours horizon is explored. The authors report the contribution of QPF errors on hydrologic predictions across scales and suggest a forecasting scenario that shows the most enhanced predictability of streamflows.

How to cite: Krajewski, W. and Ghimire, G.: Scale-Dependent Worth of QPF for Real-Time Streamflow Forecasting, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10958, https://doi.org/10.5194/egusphere-egu2020-10958, 2020.