Displays

The dissolution of carbonate rock ‘karstification’ creates pronounced surface and subsurface heterogeneity and results in complex flow and transport dynamics. Consequently, water resources managers face significant challenges keeping calm when dealing with karst water resources especially in times of environmental change. My lecture not only will provide an overview of the peculiarities of karst hydrology but it will also offer some approaches that facilitate the assessment of environmental changes on karst water resources. Using two case studies, one at the plot scale and the other at the scale of an entire continent, I will contrast the opportunities and challenges of dealing with karst across different scales and climatic regions. In particular, I will elaborate (1) how understanding on dominant karst processes can be obtained, (2) how this understanding can be incorporated into karst specific modelling approaches, and (3) how karst models developed at different scales can be used for water management and water governance. The presentation will conclude with some thoughts to facilitate less furious implementations of karst approaches for everyone.

How to cite: Hartmann, A.: The karst and the furious – ways to keep calm when dealing with karst hydrology, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6086, https://doi.org/10.5194/egusphere-egu2020-6086, 2020.

Continental-scale hydrological research is becoming more important as climate variability and change, and anthropogenic impacts on groundwater, are increasing over large spatial and temporal scales. Groundwater quantities and flows are usually difficult to observe due to sparse or spatially limited monitoring networks.  Thus, large-scale hydrological models are needed to provide continuous predictions of hydrological states and fluxes for water resource management. A large part of groundwater consumed comes from alluvial aquifers, which constitute valley fills of continental catchments. While the role of alluvial aquifers as a significant water store has been subject of many previous studies, the importance of the spatial extent and continuity of alluvial aquifers in the drainage characteristics of freshwater from the continental interior to the oceans is unclear. We present a high resolution (3km) hydrological model of continental Europe using ParFlow, a 3D, parallel groundwater and surface water flow model, which uses detailed hydrofacies information as input. We discuss the effect of spatial continuity and extent of alluvial aquifers on continental lateral groundwater flow and discharge to the oceans, water table depth, streamflow, and surface and subsurface storage. The results suggest that the alluvial valleys act as conduits that manage the drainage and retention of continental freshwater in sync with the atmospheric forcing. This dynamic equilibrium may be significantly disturbed by human interventions such as pumping and irrigation leading to a new equilibrium in terms of continental water quantity and also quality.

How to cite: Kollet, S., Sharples, W., and Naz, B.: Controls of alluvial aquifers on continental drainage, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8705, https://doi.org/10.5194/egusphere-egu2020-8705, 2020.

We present EMO-5, a Pan-European high-resolution (5 km), (sub-)daily, multi-variable meteorological data set especially developed to the needs of an operational, pan-European hydrological service (EFAS; European Flood Awareness System). The data set is built on historic and real-time observations coming from 18,964 meteorological in-situ stations, collected from 24 data providers, and 10,632 virtual stations from four high-resolution regional observational grids (CombiPrecip, ZAMG - INCA, EURO4M-APGD and CarpatClim) as well as one global reanalysis product (ERA-Interim-land). This multi-variable data set covers precipitation, temperature (average, min and max), wind speed, solar radiation and vapor pressure; all at daily resolution and in addition 6-hourly resolution for precipitation and average temperature. The original observations were thoroughly quality controlled before we used the Spheremap interpolation method to estimate the variable values for each of the 5 x 5 km grid cells and their affiliated uncertainty. EMO-5 v1 grids covering the time period from 1990 till 2019 will be released as a free and open Copernicus product mid-2020 (with a near real-time release of the latest gridded observations in future). We would like to present the great potential EMO-5 holds for the hydrological modelling community.

footnote: EMO = European Meteorological Observations

How to cite: Thiemig, V., Salamon, P., Gomes, G. N., Skøien, J. O., Ziese, M., Rauthe-Schöch, A., Rehfeldt, K., Pichon, D., and Schweim, C.: EMO-5: Copernicus pan-European high-resolution meteorological data set for large-scale hydrological modelling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21551, https://doi.org/10.5194/egusphere-egu2020-21551, 2020.

The release of the European Centre for Medium-Range Weather Forecasts (ECMWF)’s Re-Analysis 5 (ERA-5) global climate forcing dataset is expected to greatly improve the quality of hydrological modeling. Following this release there is great interest in assessing the improvements of ERA-5 relative to its predecessor ERA-Interim for hydrological modeling and predictions.

In this study we compare streamflow predictions when using ERA-interim vs ERA-5 as forcing data for a suite of hydrological models from different research groups that capture the variation in modelling strategies within the hydrological modelling community. We check whether physically based models, defined as those that do not require additional parameter calibration, would lead to different conclusions in comparison to conceptual models, defined as those that require calibration. Based on the hydrological model structure we expect that conceptual models that need calibration show less difference in predicting discharge (skill) between ERA-5 and ERA-Interim, where-as the physical based (non-calibrated) models most likely will benefit from the improved accuracy of the ERA-5 input. This assessment will provide the HEPEX community with answers on how the ERA-5 dataset will improve hydrological predictions based on different hydrological modelling concepts.

An additional key objective while conducting this study is compliance to the FAIR principles of data science. To achieve this we held a workshop in Leiden, the Netherlands, where multiple hydrological models were integrated into the eWatercycle II system. eWatercycle II is a hydrological model platform containing a growing number of hydrological models. The platform facilitates research and cohesivity within the hydrological community by providing an Open-Source platform built specifically to advance the state of FAIR and Open Science in Hydrological Modeling. We also use this study to demonstrate the feasibility of eWatercycle II as a platform for FAIR hydrological models.

Preliminairy results from this comparison study were presented at the AGU Fall Meeting 2019. Here we will present the full results of the comparison study.

How to cite: Hut, R., Drost, N., Aerts, J., Bouaziz, L., van Verseveld, W., Jagers, B., Baart, F., Sutanudjaja, E., Melsen, L., Bennett, A., Arnal, L., Fenicia, F., Santos, L., Gelati, E., Dal Molin, M., Knoben, W., Gharari, S., Hall, C., Hutton, E., and van de Giesen, N. and the the eWaterCycle comparison team from the Netherlands eSciencecenter.: Comparing the impact for hydrology of the new ERA5 reanalyses dataset over ERA-Interim for 8 hydrological models in 6 catchments using the eWaterCycle community modelling environment., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10219, https://doi.org/10.5194/egusphere-egu2020-10219, 2020.

Our understanding of the advantages and limitations of satellite derived precipitation datasets as a forcing to hydrological models has made tremendous progress over the past decade. However, most studies have only analysed the performance of one or few datasets, have used global precipitation datasets to force lumped models on regional/large-scale basins, or have adopted more complex distributed models but applied them to small basin scales.

We aimed at addressing these gaps in the literature: in particular, we compared the performance of 18 different precipitation datasets used as input in a grid-based distributed hydrological model to assess streamflow in large-scale river basins. These datasets are classified as Uncorrected Satellites, Corrected Satellites, and Reanalysis-Gauges based datasets. The hydrological model is applied to 8 large scale river basins (Amazon, Brahmaputra, Congo, Danube, Godavari, Mississippi, Rhine and Volga) with different sizes, presence of hydraulic structures, human footprint, hydrometeorological characteristics, and precipitation gauge network density were selected.

The results of this study showed that there is not a unique best performing precipitation dataset for all basins and results are very sensitive to the basin characteristics. However, there are few datasets which persistently outperform the others: SM2RAIN-ASCAT for Class 1, CHIRPS V2.0, MSWEP V2.1, and CMORPH-CRTV1.0 for Class 2, GPCC and WFEDEI GPCC for Class 3. The use of a distributed modelling approach rather than lumped is supported by the fact that precipitation datasets showing the highest model result at the basin outlet do not show the same high performance at internal locations of the basin. In addition, precipitation datasets belonging to Class 2 outperform the other datasets in basins with Tropical and Temperate-Arid climate (e.g. Congo, Mississippi and Godavari), while Class 3 datasets show the highest NSE values in Temperate and Temperate-Cold basins (e.g. Danube, Rhine and Volga).

How to cite: Brandimarte, L., Mazzoleni, M., and Amaranto, A.: Comparing 18 precipitation datasets for large scale distributed hydrological modelling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5443, https://doi.org/10.5194/egusphere-egu2020-5443, 2020.

Accurate and timely information about soil moisture is critical for drought monitoring, irrigation scheduling, and prediction of agricultural yields. We comprehensively assessed the temporal dynamics of 15 state-of-the-art (sub-)daily global surface soil moisture products, including five based on satellite retrievals, five based on "open-loop'' models (i.e., without data assimilation), and five based on models that assimilate satellite observations. As reference, we used in-situ soil moisture measurements at approximately 5-cm depth from 949 probes globally. Among the three single-sensor satellite products (AMSR2, SMAPL3, and SMOS), the L-band-based SMAPL3 performed best overall by a significant margin. Among the two multi-sensor satellite products (ESACCI and TC), TC achieved superior performance and outperformed SMAPL3 as well. The performance ranking of the five open-loop models (GLDAS, HBV-ERA5, HBV-IMERG, HBV-MSWEP, and VIC-PGF) is consistent with previous precipitation dataset evaluations, with HBV forced with MSWEP precipitation achieving the best performance not just among the open-loop models, but among all 15~products. Overall, the open-loop models performed better than the satellit products, reflecting the precipitation data quality in the conterminous US where most soil moisture probes are situated. The five models that assimilate satellite observations (GLEAM, HBV-ERA5+SMAPL3, HBV-IMERG+SMAPL3, HBV-MSWEP+SMAPL3, and SMAPL4) generally outperformed the open-loop models and exhibited a smaller spread in performance. Data assimilation yielded significantly improved performance when using less accurate precipitation (IMERG), but slightly degraded performance when using more accurate precipitation (MSWEP), demonstrating the value of data assimilation in poorly gauged regions.

How to cite: Sheffield, J., Beck, H., Pan, M., Miralles, D., Reichle, R., Dorigo, W., Wagner, W., and Wood, E.: Global assessment of 15 satellite- and model-based soil moisture products for operational drought monitoring, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10972, https://doi.org/10.5194/egusphere-egu2020-10972, 2020.

Free-flowing rivers (FFRs) are the freshwater equivalent of wilderness areas and they support many of the most diverse, complex and dynamic ecosystems globally, providing important societal and economic services. We define FFRs as rivers where ecosystem functions and services are largely unaffected by changes to the fluvial connectivity, allowing unobstructed movement and exchange of water, energy, material and species within the river system and with surrounding landscapes. However, there is immense anthropogenic pressure on natural connectivity in rivers: river connectivity can be compromised by physical infrastructure in the river channel, along riparian zones or in adjacent floodplains; hydrological alterations of river flow due to water abstractions or regulation; and changes to water quality that lead to ecological barrier effects caused by pollution or alterations in water temperature.

We developed the Connectivity Status Index (CSI), a novel methodology to measure of the current state of connectivity at a river reach scale (river segment of ~2.5 km length). The CSI considers five ‘pressure factors’ that represent the main human interferences within the four dimensions of river connectivity: a) river fragmentation (longitudinal); b) flow regulation (lateral and temporal); c) sediment trapping (longitudinal, lateral, and vertical); d) water consumption (lateral, vertical, and temporal); and e) infrastructure development in riparian areas and floodplains (lateral and longitudinal). We developed proxy indicators for these components informed by available global data and numerical model outputs and combined these layers into the CSI using a weighted overlay model. We assessed the connectivity status of 12 million kilometres of rivers globally and identified rivers that remain free-flowing in their entire length.

We found that only a third of rivers longer than 1,000 kilometres remain free-flowing over their entire length and less than a quarter flow uninterrupted to the ocean. Very long FFRs are largely restricted to remote regions of the Arctic and of the Amazon and Congo basins. In densely populated areas only few very long rivers remain free-flowing, such as the Irrawaddy and Salween. Dams and reservoirs and their up- and downstream propagation of fragmentation and flow regulation are the leading contributors to the loss of river connectivity. Plans to rapidly develop new infrastructure in basins around the world threaten the loss of extensive kilometers of free-flowing rivers, including status changes of several iconic long free-flowing rivers in tropical regions, such as the Amazon, Salween, Irrawaddy and Karnali rivers.

Given the current status and future perspective of free-flowing rivers, we will discuss a range of opportunities for application of the Connectivity Status Index, including a) as a component in studies of ecosystem health; b) to play a role in prioritizing rivers with high conservation value for protection; c) in optimizing the informed selection of low-impact infrastructure developments; and d) as a tool for national and global monitoring.

How to cite: Grill, G., Lehner, B., Tieme, M., Ticker, D., and Geenen, B.: Mapping the world’s free-flowing rivers using the Connectivity Status Index (CSI), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22487, https://doi.org/10.5194/egusphere-egu2020-22487, 2020.

Land models are increasingly used as the backbone of the terrestrial hydrology as they cover a wide range of processes (from rainfall/runoff processes to carbon cycle). The recent improvements in high-resolution spatial data set including detailed digital elevation models, DEMs, and land cover and soil type maps are encouraging the modelers to set up the land surface models at the highest resolution possible. However, this high-resolution setup does not often coincide with rigorous model diagnostics and also the “optimal” spatial representation based on the context of modeling (e.g. streamflow). A model can be seen as a tool to interpolate or extrapolate our knowledge in time and space and therefore it remains an important aspect of land surface modeling to which level the spatial heterogeneity can be represented in a model so that the states and fluxes “improve” given the context of modeling. The representation of spatial data in our models has important implications including (1) removing the unnecessarily computational burden from model setups which in turn results in better assessment of uncertainty and sensitivity analysis of the parameters on a less computational expensive model. (2) Proper corresponding between the communications of spatial variability while avoiding overconfidence in the nature of model response on illogically smallest units.

In this study, in contrast to the often used grid-based model setup, we use the concept of vector-based group response units (GRUs) for setting up the Variable Infiltration Capacity, the VIC model, and vector-based MizuRoute routing scheme. We explore the added information by stepwise inclusion of more detailed spatial data and higher resolution forcing data while the vector-based routing setup remains identical for each of the configurations. Using this flexible workflow we explore three major questions:

• 1- How the performance of model changes in the calibration mode for various configuration of spatial heterogeneity representation and forcing resolution given the context of modeling, for example, streamflow simulations or snow water equivalent spatial pattern?
• 2- How well a simplified version of a more complex model in spatial representation can reproduce its own simulation? The answer to this question will provide us with iso-performing model setups, configurations of forcing distribution and spatial heterogeneity representation, and the possible loss in the performance metric given the context of modeling under the simplification decisions.
• 3- How the model performs across various configurations of spatial data and forcing resolutions with a given set of so-called physically parameters that are often considered to be identical for GRUs with the same physical characteristics, soil, vegetation type, elevation zone, slope and aspect, varies?

Our findings indicate that the optimal spatial representation in the context of modeling, streamflow, for example, may very well be much less computationally demanding than the model setup that contains all the details with the highest resolution of the data. In a complementary attempt, it is shown that the often good performing parameter sets are able to reproduce good performing simulation in comparison to the model setup with the highest model resolution.

How to cite: Gharari, S. and Clark, M.: On the exploration of alternative spatial representation for land models; a vector-based setup for the Variable Infiltration Capacity model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6524, https://doi.org/10.5194/egusphere-egu2020-6524, 2020.

PCR-GLOBWB ( (Van Beek et al., 2012; Sutanudjaja et al., 2018) is a global hydrology and water resources model that has been developed over the past two decades at the Department of Physical Geography, Utrecht University, The Netherlands. The latest version of the model has a spatial resolution of 5 arc minutes (approx. 10 km at the equator) and runs on a daily resolution covering several decades. Different initiatives have expressed the need for hyper-resolution global hydrological modelling (see e.g. Bierkens et al., 2015), and in compliance we aim to further refine the spatial resolution of the model to 30 arc seconds (approx. 1 km at the equator). As a starting point, we are currently developing a version for the African continent. In doing so, two major challenges need to be overcome. First, computation time constitutes a hurdle, in particular to model river water routing/flow using a time-explicit scheme. To reduce run time, we apply a river basin partitioning strategy decomposing the model domain into several groups of river basins such that each river basin, connecting from their most upstream to downstream cells, could be run as an independent process. We aim to further advance this with a Pfafstetter domain decomposition (de Jager and Vogt, 2010,) that capitalizes on the hierarchical structure of a drainage network in combination with massive parallel computing to make this possible.

Second, the parameterization of the model at 30 arc seconds poses a major challenge as this resolution approaches that of available global datasets. Preliminary, we have therefore derived the first version of the model parameters at 30 arcsec resolution for Africa using globally-available datasets and following our past experiences (see e.g. Sutanudjaja et al., 2011; van Beek and Bierkens, 2009). We have tested this version of the model with our own meteorological forcing (derived based on the CRU TS 3.21 and ERA-Interim). Results are promising (e.g., NSE = 0.63; KGE = 0.29  at Nawuni, a station on the White Volta in Ghana) and will be discussed in the presentation.

Bierkens, M.F.P. et al. (2015). Hyper‐resolution global hydrological modelling: what is next? “Everywhere and locally relevant”. Hydrol. Process. 29, 310–320.

Van Beek et al. (2011). Global monthly water stress: 1. Water balance and water availability. Water Resour. Res., 47, W07517

Sutanudjaja, E.H et al. (2017). PCRGLOBWB 2: a 5 arc-minute global hydrological and water resources model. Geosc. Mod. Develop. 11, 2429-2453.

De Jager, A. L. and Vogt, J.V. (2010). Development and demonstration of a structured hydrological feature coding system for Europe, Hydrol. Scienc. J. 55, 661-675.

Sutanudjaja et al. (2011). Large-scale groundwater modeling using global datasets: a test case for the Rhine-Meuse basin. Hydrol. Earth Syst. Sci., 15, 2913–2935.

van Beek, L.P.H. and M.F.P. Bierkens (2009). The Global Hydrological Model PCR-GLOBWB: Conceptualization, Parameterization and Verification. https://vanbeek.geo.uu.nl/suppinfo/vanbeekbierkens2009.pdf

How to cite: van Beek, L. P. H. (., Sutanudjaja, E. H., Hoch, J. M., and Bierkens, M. F. P.: Implementing PCR-GLOBWB on a 1 km resolution for Africa, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8616, https://doi.org/10.5194/egusphere-egu2020-8616, 2020.

Land surface and hydrologic models (LSM/HMs) have been typically calibrated with streamflow for selected river basins. This procedure, although it is the current standard, it is highly disadvantageous because the resulting model 1) is not transferable to other locations and scales, 2) it underperforms against multivariate data not used during calibration, and 3) simulated fluxes do not fulfill the flux-matching closure condition [1] if compared across scales. These shortcomings lead to parameter fields exhibiting artifacts and sharp discontinuities over space (not seamless) [2] and thus, to a poor spatial representation of water fluxes and states. Existing terrestrial water cycle observations have spatial supports ranging from few hundred square meters to hundred square kilometers. Currently, most of the existing LSM/HMs are not able to assimilate simultaneously these observations because they do not have scale-invariant parameterizations. Preliminary tests at continental scale indicate that nested multiscale simulations are possible only if the model exhibits a scale-invariant parameterization [3]. In mHM [4], this capability is provided via the multiscale parameter regionalization (MPR) technique [1].

In this study, transfer-function parameters for mHM are estimated with 5500 GRDC streamflow time series, tens of FLUXNET evapotranspiration products, and the terrestrial total water storage anomaly (GRACE). This parameter estimation problem at global-scale requires a powerful supercomputer (JUWELS) [5] and the usage of recently implemented and extremely efficient parallelized algorithms [6]. The daily reconstructed high-resolution hydrologic simulations (0.25°) since 1950 reveal that the use of the MPR technique improves the overall model efficiency (compared to other global models [7]) and allows us to identify locations of consistent changes in hydrologic variables responding to long-term climate variability. The median of the NSE for the uncalibrated mHM model over the selected GRDC stations reaches a value of 0.40 for daily streamflow. Models reported in Beck et al. [7] exhibit a mean value of -0.09! This indicates the great potential of the proposed method. Comparison of terrestrial water storage (TWS) of GRACE against mHM simulations reveals hotspots of weaker model performance in regions where the water balance closure error is large. 

References

[1] https://doi.org/10.1029/2008WR007327
[2] https://doi.org/10.5194/hess-21-4323-2017
[3] https://doi.org/10.1175/JHM-D-15-0054.1
[4] www.ufz.de/mhm
[5] http://www.fz-juelich.de/ias/jsc/juwels
[6] https://meetingorganizer.copernicus.org/EGU2019/EGU2019-8129-1.pdf
[7] https://doi.org/10.1002/2015WR018247

How to cite: Samaniego, L., Kaluza, M., Thober, S., and Rakovec, O.: Multi-scale global reconstruction of water fluxes and states with mHM, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4221, https://doi.org/10.5194/egusphere-egu2020-4221, 2020.

Over the past decade there has been important progress towards modeling the water, energy, and carbon cycles at field scales (10-100 meter) over continental extents. One such approach, named HydroBlocks, accomplishes this task while maintaining computational efficiency via sub-grid hydrologic response units (HRUs); these HRUs are defined via cluster analysis of available field-scale environmental datasets (e.g., elevation). However, until now, there has yet to be complementary advances in river routing schemes that are able to fully harness HydroBlocks’ approach to sub-grid heterogeneity, thus limiting the added value of field-scale resolving land surface models (e.g., riparian zone dynamics, irrigation from surface water, and interactive floodplains). In this presentation, we will introduce a novel large scale river routing scheme that leverages the modeled field-scale heterogeneity in HydroBlocks through more realistic sub-grid stream network topologies, reach-based river routing, and the simulation of floodplain dynamics.

The primary features of the novel river routing scheme include: 1) each macroscale grid cell is assigned its own river network delineated from field-scale DEMs; 2) similar sub-grid reaches (e.g., Shreve order) are grouped/clustered to ensure computational tractability; 3) the fine-scale inlet/outlet reaches of the macroscale grid cells are linked to assemble the continental river networks; 4) river dynamics are solved at the reach-level via an implicit solution of the Kinematic wave with floodplain dynamics; 5) two way connectivity is established between each cell’s sub-grid HRUs and the river network. The resulting routing scheme is able to effectively represent sub-100 meter-delineated stream networks within Earth system models with relatively minor increases in computation with respect to existing approaches. To illustrate the scheme’s novelty when coupled to the HydroBlocks land surface model, we will present simulation results over the Yellowstone river in the United States between 2002 and 2018. We will show the added value of the scheme when compared to existing approaches with regards to floodplain dynamics, water management, and riparian corridors. Furthermore, we will present results regarding the scheme’s computational tractability to ensure the feasibility of its use within Earth system models. Finally, we will discuss the potential of this approach to enhance flood and drought monitoring tools, numerical weather prediction, and climate models.

How to cite: Chaney, N., Vergopolan, N., and Fisher, C.: Rethinking large scale river routing by leveraging a field-scale resolving land surface model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17335, https://doi.org/10.5194/egusphere-egu2020-17335, 2020.

Managing water resources and basin reclamation requires hydrological data across a set of scales.  Unfortunately, in many areas the in-situ data is sparse, or not made available to water managers.  With NASA, ESA and Chinese satellites, their data can potentially be merged with in-situ gauge data.  Doing so results in a number of research challenges: 1. Satellite data based on microwave sensors (e.g. L-band sensors from SMAP or SMOS) results in coarse resolution (~35-50 km) making the data difficult for management; (ii) Satellite data from instruments like LandSat (~90m) suffers from cloud contamination.  New satellites improve resolution but still suffer cloud contamination; (iii) Precipitation (along with radiation) falls between these two spectrums, and its fast dynamics can impact water management decision making; (iv) Topographic and soil characteristics, which govern the runoff from the land to rivers; and (v) river flows that are a water source for drought and a site for reservoirs.

In this talk I will present a new land surface model (HydroBlocks) that we run at a 30m resolution at regional to continental scales.  The water is transmitted to hyper-resolution streams for which we have extracted ~2,900,000 reaches.  Visualization of the models will offer the listener the impact of moving to these scales; and the data needed for water resources management of river basins.

How to cite: Wood, E., Vergopolan, N., Lin, P., and Pan, M.: Application of hyper-resolution hydrological modeling for water resources decision making, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2766, https://doi.org/10.5194/egusphere-egu2020-2766, 2020.

The explosion in the number of hydrologic models and technological advances in cloud infrastructure have combined to create new opportunities in operationalization of hydrologic science and models over the past decade. Colloquially, operationalization has been used to refer to deployments of previously existing model codes, themselves realizations of existing hydrologic science and conceptualizations, run in an unsupervised manner (e.g., automatically) driven by climate input variables that are contemporary (now-casting) or projected (forecasting). With advances in computational infrastructure and power, it has become possible to read, run, and visualize output from automated, operational models across continental domains. In the United States, recent endeavors include U.S. Geological Survey’s integrated water availability assessments, an operational configuration of the Precipitation Runoff Modeling System in the National Hydrologic Model Infrastructure; the National Water Model, an operational configuration of WRF-Hydro for flood forecasting; and several more nascent efforts. While these efforts show significant technological advances in the communication of results of hydrologic models, we ask how they have contributed to advances towards expanding knowledge of the hydrologic sciences more generally. Operational configurations of continental-domain models build upon advances of catchment-scale hydrology generally focused on addressing a single management scenario. The extent to which these model configurations have the fidelity to address a wider range of management scenarios and the translation across spatial and temporal scales is not straightforward. In addition, continental-domain operational deployments allow for the visualization of large-scale hydrologic events (e.g., droughts and floods), but perpetuate problems with communication of accuracy and uncertainty at management-relevant scales. Here we explore how these technological advances can be leveraged to advance the hydrologic science that underlies our models.

How to cite: Farmer, W. and Driscoll, J.: Operationalizing Continental-Domain Hydrologic Models: What can we learn?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6072, https://doi.org/10.5194/egusphere-egu2020-6072, 2020.

Various studies investigated the fate of evaporation and the origin of precipitation. The more recent studies among them were often carried out with the help of numerical moisture tracking. Many research questions could be answered within this context such as dependencies of atmospheric moisture transfers between different regions, impacts of land cover changes on the hydrological cycle, sustainability related questions as well as questions regarding the seasonal and inter-annual variability of precipitation. In order to facilitate future applications, global datasets on the fate of evaporation and the sources of precipitation are needed. Since most studies are on a regional level and focus more on the sources of precipitation, the goal of this study is to provide a readily available global dataset on the fate of evaporation for a fine-meshed grid of source and receptor cells. The dataset was created through a global run of the numerical moisture tracking model WAM-2layers and focused on the fate of land evaporation. The tracking was conducted on a 1.5° × 1.5° grid and was based on reanalysis data from the ERA-Interim database. Climatic input data were incorporated in 3- respectively 6-hourly time steps and represent the time period from 2001 to 2018. Atmospheric moisture was tracked forward in time and the geographical borders of the model were located at +/- 79.5° latitude. As a result of the model run, the annual and monthly average as well as the inter-annual average fate of evaporation was determined for 8684 land grid cells (all land cells except those located within Greenland and Antarctica) and provided via source-receptor matrices. The gained dataset was complemented via an aggregation to country and basin scales in order to highlight possible usages for areas of interest larger than grid cells. This resulted in data for 265 countries and 8223 basins. Finally, five types of source-receptor matrices for average moisture transfers were chosen to build the core of the dataset: land grid cell to grid cell, country to grid cell, basin to grid cell, country to country, basin to basin. The dataset is, to our knowledge, the first ready-to-download dataset providing the overall fate of evaporation for land cells of a global fine-meshed grid in monthly resolution. At the same time, information on the sources of precipitation can be extracted from it. It could be used for investigations into average annual, seasonal and inter-annual sink and source regions of atmospheric moisture from land masses for most of the regions in the world and shows various application possibilities for studying interactions between people and water such as land cover changes or human water consumption patterns. The dataset is accessible under  and comes along with example scripts for reading and plotting.   

How to cite: Link, A., van der Ent, R., Berger, M., Eisner, S., and Finkbeiner, M.: The fate of land evaporation - A global dataset, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3674, https://doi.org/10.5194/egusphere-egu2020-3674, 2020.

How to cite: Liu, Z.: Vegetation-Climate-Water coupling in a changing environment, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1439, https://doi.org/10.5194/egusphere-egu2020-1439, 2020.

Several authors in the literature, such as Khan (2014) and Loritz (2017), have previously suggested that 3D catchment hydrology can be predicted from 2D hillslope simulations. Following this idea, we propose an upscaling methodology for runoff and evapotranspiration fluxes. The first step consists of a geomorphic analysis of the studied watershed. The average mean slope and hillslope length are then used to build a 2D equivalent-hillslope model. The validity of the methodology is tested by comparing the resulting water balance with a 3D physically-based distributed model. 2D fluxes of the equivalent hillslope are converted into 3D by using the drainage density. This upscaling methodology is applied to the Little Washita (LW) watershed (Oklahoma, USA). Both the 3D reference model and the 2D equivalent model are built with the physically-based distributed code HydroGeoSphere, which is forced by LW reanalysis climatic data. Two decades are simulated. Regarding the evapotranspiration, the upscaling methodology with only one equivalent hillslope gives a good prediction of 3D fluxes. However, a combination of several hillslopes is needed for simulating the 3D flow rate at the basin’s outlet. This work on the decrease of model dimensionality is a first step in the upscaling process from 3D physically-based models to 1D column models used in global Land Surface Models.

How to cite: Picourlat, F., Mouche, E., and Mugler, C.: Upscaling runoff and evapotranspiration fluxes in the Little Washita watershed using physically-based hillslope models, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8227, https://doi.org/10.5194/egusphere-egu2020-8227, 2020.

Watershed modelling is one of the most important assessment tools in watershed planning and management. Nonetheless, the classic calibration of watershed models, in which a few discharge gauges near the outlet of a catchment are used to compare measured and simulated streamflow, is often criticized by not assuring that relevant processes such as evapotranspiration, soil moisture, crop growth, and groundwater recharge are well represented in the catchment area. This study aimed to simulate streamflow in two Mediterranean catchments, Orba (778km²) in Italy and Segre (1286km²) in Spain, using the physically-based, fully distributed MOHID-Land model. Model calibration/validation of streamflow was first performed following a classical approach. Different products derived from remote sensing platforms were then used to evaluate the adequacy of model simulations of crop growth and soil moisture in the catchment area.

The MOHID-Land model considers four compartments or mediums (atmosphere, porous media, soil surface and river network), computing water dynamics through the different mediums using mass and momentum conservation equations. The model was implemented in the two simulated catchments with a resolution of 1 km. Data inputs included the Digital Elevation Model over Europe (EU-DEM) with a resolution of 30 m; the soil hydraulic properties map from EU-SoilHydroGrids ver1.0 with a resolution of 250 m; the CORINE land cover map from 2012 with a resolution of 100 m; the hourly weather data (precipitation, wind velocity, relative air humidity, solar radiation and surface air temperature) from local weather stations; and the reservoir discharge data from governmental and/or regional agencies. Simulations were run from 2006-2014 for Orba and from 2008-2018 for Segre, and included a model warm-up, a calibration, and a validation period. Comparison between simulated and measured flows were performed in 2 and 10 hydrometric stations located in the Orba and Segre catchments, respectively. Four statistical parameters (R², RMSE, PBIAS and NSE) were used to evaluate model performance, confirming the good fitting of model simulations to measured data.

Model simulations of leaf area index (LAI) were then compared with LAI maps at 30 m resolution derived from ATCOR and Landsat 8 imagery data using the Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI). Furthermore, model simulation of soil moisture were also compared at the surface depth (0-5 cm) with soil moisture maps at 1 km resolution created with the DISaggregation based on a Physical And Theoretical scale CHange (DISPATCH) algorithm for the downscaling of the 40 km SMOS (Soil Moisture and Ocean Salinity) soil moisture data using land surface temperature (LST) and NDVI data. Results showed the fundamental differences between the MOHID-Land and remote sensing outputs, with major differences being analyzed by soil units and land use classes.

How to cite: Ramos, T., Simionesei, L., Basso, M., Stefan, V., Oliveira, A., Escorihuela, M. J., Bagagiolo, G., Biddoccu, M., Rabino, D., Grosso, N., and Neves, R.: Simulation of streamflow in two Mediterranean catchments using a process-based model and remote sensing products, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10378, https://doi.org/10.5194/egusphere-egu2020-10378, 2020.

Estimating how much water is flowing through rivers at the global scale is challenging due to a lack of observations in space and time. A way forward is to optimally combine the global network of Earth system observations with advanced Numerical Weather Prediction (NWP) models to generate consistent spatio-temporal maps of land, ocean, and atmospheric variables of interest, known as a reanalysis. While the current generation of NWP output runoff at each grid cell, they currently do not produce river discharge at catchment scales directly, and thus have limited utility in hydrological applications such as flood and drought monitoring and forecasting. This is overcome in the Global Flood Awareness System (GloFAS; http://www.globalfloods.eu/) by coupling surface and sub-surface runoff from the HTESSEL land surface model used within ECMWF’s latest global atmospheric reanalysis (ERA5) with the LISFLOOD hydrological and channel routing model.

This work presents the new GloFAS-ERA5 global river discharge reanalysis dataset launched on 5 November 2019 (version 2.1 release). The river discharge reanalysis is a global gridded dataset with a horizontal resolution of 0.1° at a daily time step. An innovative feature is that it is produced in an operational environment so is available to users from 1 January 1979 until near real time (2 to 5 days behind real time). The reanalysis was evaluated against a global network of 1801 river discharge observation stations. Results found that the GloFAS-ERA5 reanalysis was skilful against a mean flow benchmark in 86 % of catchments according to the modified Kling-Gupta Efficiency Skill Score, although the strength of skill varied considerably with location. The global median Pearson correlation coefficient was 0.61 with an interquartile range of 0.44 to 0.74. The long-term and operational nature of the GloFAS-ERA5 reanalysis dataset provides a valuable dataset to the user community for large scale hydrology applications ranging from monitoring global flood and drought conditions, understanding hydroclimatic variability and change, initialising hydrological forecasts, and as raw input to post-processing and machine learning methods that can add further value.

Data availibility: The dataset is openly available from the Copernicus Climate Change Service (C3S) Climate Data Store (C3S): https://cds.climate.copernicus.eu/cdsapp#!/dataset/cems-glofas-historical?tab=overview and further details and the evaluation of the dataset can be found in the accompanying data description paper: 

Data paper: Harrigan, S., Zsoter, E., Alfieri, L., Prudhomme, C., Salamon, P., Wetterhall, F., Barnard, C., Cloke, H., and Pappenberger, F.: GloFAS-ERA5 operational global river discharge reanalysis 1979–present, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2019-232, 2020.

How to cite: Harrigan, S., Zsoter, E., Alfieri, L., Prudhomme, C., Salamon, P., Wetterhall, F., Barnard, C., Cloke, H., and Pappenberger, F.: GloFAS-ERA5 operational global river discharge reanalysis 1979-present, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15755, https://doi.org/10.5194/egusphere-egu2020-15755, 2020.

This work is a continuation of our previous investigations performed within the framework of the International Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) on a regional scale when hydrological projections and their uncertainties were obtained for 11 large-scale river basins using the physically based land surface model Soil Water – Atmosphere – Plants (SWAP) driven by meteorological projections from five Global Climate Models (GCMs). In the present work, we decided to spread our investigations to continental and global scales. The main goals are as follows: (i) projecting changes in terrestrial water balance components in the 21^st century due to possible climate change for different continents and for the whole globe, (ii) evaluation of uncertainties in the obtained projections sourced from application of different GCMs and different climatic scenarios, (iii) studying the patterns of spatial distribution of changes in the water balance components and their uncertainties.

Simulations of the water balance components (evapotranspiration and runoff) for the entire land surface of the globe (with the exception of Antarctica) were performed by the SWAP model with a spatial resolution of 0.5^o×0.5^o for the period of 1961-2099. The model was driven by daily meteorological outputs from five GCMs (including GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, and NorESM1-M) obtained for each of four Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5). As a result, 20 variants of daily values of evapotranspiration, runoff, and precipitation were obtained for each calculational grid cell. Then, the climatic annual values of the water balance components for four periods (historical and three prognostic ones: 2006-2036, 2037-2067, 2068-2099) were obtained and their changes for different prognostic periods compared to historical values were calculated. Besides, uncertainties in the projected changes of the water balance components resulted from application of different GCMs and RCP scenarios were estimated. The obtained results were mapped and averaged over the continents, latitudinal zones, and the globe that allowed us to identify spatio-temporal patterns of changes in the water balance components and their uncertainties due to possible climate changes.

How to cite: Nasonova, O., Gusev, Y., and Kovalev, E.: Climate change impact on terrestrial water balance components at continental and global scales, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5968, https://doi.org/10.5194/egusphere-egu2020-5968, 2020.

Hydrological models have been developed in response to the need to understand the complex water cycle of the Earth and to assess its interaction with historical and future climate scenarios. In the global water sector of the Inter-Sectoral Impact Model Intercomparison Project phase 2b (ISIMIP2b), six land surface models (LSMs), eight hydrological models (GHMs), and one dynamic vegetation model (DGVM) are contributing with transient simulations spanning from 1660 to 2300. The model simulations follow a common protocol and are driven by common bias adjusted climate model outputs combined with plausible socio-economic scenarios and representative concentration pathways. The main goal of this study is to highlight similarities and differences among these models in simulating the vertical water balance. The main similarity of these models consists in the water cycle simulation, even if the models have been developed for different purposes such as energy cycle (LSMs), water cycle (GHMs), or vegetation cycle (DGVM) simulation. In particular, we address the following research question: 1) what equations are used to compute water storages and water fluxes; 2) how different are the equations among the models; 3) how the equations were adjusted; 4) how many parameters are used by the models; 5) how often the parameters are used; 6) how similar or different are the parameters among the models. To this end, we apply a standard writing style of the water storages and water fluxes included in the models, to easily identify the similarities and differences among them. Most of the models include in their structure the canopy, soil, and snow storages, and almost half of them include the groundwater storage. Furthermore, we find that: 1) a model needs a very good documentation, this would help to easily identify and understand the equations in the code; 2) some modelers teams use common approaches resulting in similar equations of water storages or water fluxes, but different models structures still lead to different models results; 3) collaboration and communication among the modelers are necessary, on the one hand, for the realization of the models standard writing style, and on the other hand, for a better understanding of the models themselves, especially their strengths, limitations and results. Overall, our results (i) help to better explain the different models results and to attribute these to the differences in simulating specific processes; (ii) contribute to the remarkable efforts in creating a common protocol and a common input datasets for well-defined simulations; (iii) foster a better understanding of how the models work and finding new ways of improvement and development.

How to cite: Telteu, C.-E., Müller Schmied, H., Thiery, W., Leng, G., Burek, P., Liu, X., Boulange, J. E. S., Seaby, L. P., Grillakis, M., Satoh, Y., Rakovec, O., Stacke, T., Chang, J., Wanders, N., Tao, F., Zhai, R., Shah, H. L., Trautmann, T., Mao, G., Koutroulis, A., Pokhrel, Y., Samaniego, L., Wada, Y., Mishra, V., Liu, J., Newland Gosling, S., Schewe, J., and Zhao, F.: Similarities and differences among fifteen global water models in simulating the vertical water balance, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7549, https://doi.org/10.5194/egusphere-egu2020-7549, 2020.

In this contribution we present the wflow_sbm hydrologic model concept, which is a conceptual bucket-style hydrologic model based on simplified physical relationships including kinematic wave routing for surface and subsurface lateral flow. The model maximizes the use of global data for local applications and allows us to automatically setup a high resolution (~1km²) wflow_sbm model for any basin in the world. For most discharge gauging stations in selected basins from different climate zones, wflow_sbm showed promising results without further calibration. Depending on the geographical area of interest two model parameters, besides anthropogenic interference like reservoir and lake management, show most sensitivity: rooting depth and horizontal saturated hydraulic conductivity.

We extended the parameter estimation of the wflow_sbm hydrological model for the Rhine basin (Imhoff et al, 2019) with point-scale (pedo)transfer-functions (PTFs) in conjunction with scaling operators as applied in Multiscale Parameter Regionalization (MPR) to the global scale at high resolution (~1km²). The state-of-the-art hydro-MERIT dataset at 3 arcsec resolution (Yamazaki et al. (2019)) is scaled to model resolution whilst conserving the drainage network using a newly developed extended Effective Area Method (EAM) for flow direction scaling which builds on the original EAM (Yamazaki et al. 2009). Compared to EAM and the double maximum method, the extended EAM method shows improved skill. The automated model setup derives subgrid information about land slope, river slope and length. River widths are derived from power law relationships between hydro-MERIT river widths and global discharge estimates through multiple linear regression based on GRDC data, precipitation and upstream area with clustering on climate zones. Soil hydraulic parameters are derived from the 250m ISRIC SoilGrids product using PTFs. Furthermore, parameters for interception and rooting depth are derived and upscaled using global or regional land cover maps. Monthly LAI profiles are derived from MODIS (500m) and upscaled. Lake and reservoir parameters are derived from HydroLAKES and GRanD, respectively. The models are run using forcing from globally available data sets like ERA5 and CHIRPS.

Imhoff, R., van Verseveld, W., Osnabrugge, B., A. Weerts, Scaling point-scale pedotransfer functions to seamless large-domain parameter estimates for high-resolution distributed hydrological modelling: An example for the Rhine river, submitted to WRR, 2019.

Yamazaki D., D. Ikeshima, J. Sosa, P.D. Bates, G.H. Allen, T.M. Pavelsky, MERIT Hydro: A high-resolution global hydrography map based on latest topography datasets, Water Resources Research, 2019, doi: 10.1029/2019WR024873.

Yamazaki, D., T. Oki., and S. Kanae, Deriving a global river network map and its sub‐grid topographic characteristics from a fine‐resolution flow direction map, Hydrol. Earth Syst. Sci., 13, 2241– 2251, 2009.

How to cite: van Verseveld, W., Boisgontier, H., Bouaziz, L., Eilander, D., Haag, A., Hazenberg, P., Hegnauer, M., Imhoff, R., van Osnabrugge, B., Schellekens, J., Sperna Weiland, F., ten Velden, C., Visser, M., Wannasin, C., and Weerts, A.: Wflow_sbm, a spatially distributed hydrologic model: from global data to local applications, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14837, https://doi.org/10.5194/egusphere-egu2020-14837, 2020.

The increased flood occurrence in the lower reaches of Chao Phraya River Basin, a major river system of Thailand, has caused tremendous economic as well as agricultural losses in the past. Reservoir operation is one of the most influential factors that can alleviate flood damage by controlling the natural flow. Hence, this study examines the effect of reservoir operation on the flood peak reduction for the baseline (1990-1999) as well as future (2090-2099) scenarios under representative concentration pathway (RCP) 6 emission scenario using the H08 global hydrological model with reservoir operation module. The main objectives of the study are; (i) analyze the effect of two largest existing reservoirs of Bhumibol and Sirikit at Nakhon Sawan (catchment area: 109973 km²), where major tributaries of the Chao Phraya River join together, and (ii) analyze the effect of a hypothetical dam, located in the upper reaches of Yom River (one of the tributaries of Chao Phraya River), at Sukhothai (catchment area: 12769 km²) and Nakhon Sawan for the baseline and future scenarios. For this purpose, the H08 model was calibrated at Nakhon Sawan and validated at 26 gauging stations within the catchment with an average daily and monthly Nash-Sutcliffe efficiency values of 50 and 66% respectively. The results of baseline scenario simulation revealed that the two major reservoirs cause an enormous reduction in the daily peak discharge by 21-52% at Nakhon Sawan, whereas the impact of the hypothetical dam was negligible (3-14%) due to its reduced storage capacity compared with the major reservoirs. On the other hand, the proposed hypothetical dam exhibited significant potential for the flood peak reduction by 15-53% at Sukhothai. Therefore, it can be envisaged that the hypothetical dam could reduce flood damage at the lower reaches of Yom River where flooding is regular due to gentle slope. Further, the simulated change in daily peak discharge without the reservoir effect for the future scenario was -0.55 to 5.78 and -0.72 to 7.68 times higher at Nakhon Sawan and Sukhothai respectively compared with the baseline scenario. The impact of two existing as well the hypothetical reservoirs on flood peak reduction was similar compared with the baseline scenario at Nakhon Sawan as well as at Sukhothai. This further indicates that the changes in discharge due to climate change are larger than those achieved by the reservoir operations for the future scenario even though the simulated discharge highly depends on which general circulation model was used as input.

How to cite: Padiyedath Gopalan, S. and Hanasaki, N.: Impact assessment of reservoir operation for potential adaptation in the upper Chao Phraya River basin, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4466, https://doi.org/10.5194/egusphere-egu2020-4466, 2020.

The Australian Water Resources Assessment Landscape (AWRA-L) model is a continental hydrological model developed by the Commonwealth Scientific and Industrial Research Organization (CSIRO) and Bureau of Meteorology (BoM) of Australia which is essential in providing consistent and reliable water resources assessments and accounts across continental Australia. The operational version of the AWRA-L model provides estimates of landscape runoff, evapotranspiration, soil moisture, and groundwater recharge/storage at a spatial resolution of 5km grids. Each 5km grid is assumed to have two hydrological response units (HRUs) – shallow-rooted vegetation and deep-rooted vegetation. To improve the landscape dynamics within the model, CSIRO and BoM increased the number of HRUs from two to five by representing the hydrological processes of the following: irrigated agricultural areas, perennial large water bodies, and impervious areas. The spatial resolution of the model was also increased to 1km grids to improve its applicability for management purposes in local areas.

In this presentation, a summary of the results of the improved model using the Murrumbidgee River as a test basin will be discussed. Overall, the results suggest that the incorporation of the extra HRUs enabled the explicit representation of hydrological processes in irrigated areas, large water bodies, and impervious areas. Particularly, significant improvement was seen in the comparison of the simulated soil moisture with the observed. With the implementation of the model at a finer 1km spatial resolution, the improved model can now provide more realistic estimates of the water balance which are more suitable for use in catchment and local scale applications.

To implement the improved model in other catchments within Australia as well as for the entire continent, numerous spatial data inputs to the model must be prepared. To ensure the reliability and consistency of the spatial data layers, the most recent and best available data were used to derive and regenerate the AWRA-L spatial input layers for the Australian continent. The 48 input spatial layers to the improved 5 HRU AWRA-L model have been updated and made available both at 5km and 1km spatial grids. The climatological inputs from 1970-2012 have also been prepared to match with the spatial grids of the AWRA-L model. The updated spatial layers will be shown in this presentation.  The updated input spatial layers are essential for implementing the improved AWRA-L model at any catchment within continental Australia. Local catchments with a high fraction of irrigated agricultural areas, impervious areas, or large water bodies will benefit the most from these updates. While the spatial layers were prepared for use in the AWRA-L model, they may also be useful for the development of large-scale hydrological models as well as to the hydrological community, in general.

How to cite: Mateo, C. M., Vaze, J., and Wang, B.: Improving a continental hydrological model by enhancing its hydrological representation and implementing at 1km spatial resolution, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3237, https://doi.org/10.5194/egusphere-egu2020-3237, 2020.

High-resolution large-scale predictions of hydrologic states and fluxes are important for many regional-scale applications and water resource management. However, because of uncertainties related to forcing data, model structural errors arising from simplified representations of hydrological processes or uncertain model parameters, model simulations remain uncertain. To quantify this uncertainty, multi-model simulations were performed at 3km resolution over the European continent using the Community Land Model (CLM3.5) and the ParFlow hydrologic model. While Parflow uses a similar approach as CLM in simulating the snow, vegetation and land-atmosphere exchange processes, it simulates three-dimensional variably saturated groundwater flow solving Richards equation and overland flow with a two-dimensional kinematic wave approximation. The CLM3.5 uses a simple groundwater model to account for groundwater recharge and discharge processes. Both models were driven with the COSMO-REA6 reanalysis dataset at 6km resolution for the time period from 2000 to 2006 at an hourly time step, and both used the same datasets for the static input variables (such as topography, vegetation and soil properties). The performance of both models was analyzed through comparisons with independent observations including satellite-derived and in-situ soil moisture, evapotranspiration, river discharge, water table depth and total water storage datasets. Overall, both models capture the interannual variability in the hydrologic states and fluxes well, however differences in performance between models showed the uncertainty associated with the representation of hydrological processes, such as groundwater flow and soil moisture and its control on latent and sensible heat fluxes at the surface.

How to cite: Naz, B. S., Sharples, W., Goergen, K., and Kollet, S.: High-resolution pan-European multi-model simulations of hydrologic states and fluxes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10652, https://doi.org/10.5194/egusphere-egu2020-10652, 2020.

Freshwater availability is of vital importance for humans, freshwater biota and ecosystem functions. In the past decades, global hydrological models (GHMs) were developed to improve understanding of the global freshwater situation in a globalized word, by filling gaps in observational coverage and assessing scenarios of the future under consideration of different socioeconomic developments and climate change. The Water Global Assessment and Prognosis (WaterGAP) model was one of the first GHMs developed to evaluate freshwater resources and their use for both historical and future conditions. It consists of five water use models (for irrigation, domestic, cooling of thermal power plants, manufacturing, and livestock sectors) and the WaterGAP Global Hydrology Model (WGHM). Recently, the latest model version, WaterGAP 2.2d, was finalized, containing a number of enhancements and revisions such as a river storage-based flow velocity approach, improvements in modelling groundwater recharge in dry environments and integration of historical development of irrigated areas.

This presentation provides an overview about the WaterGAP 2.2d scheme and features, assesses global freshwater resources (runoff and streamflow) and water balance components, and provides insights to evaluation results against observed streamflow, GRACE total water storage and the AQUASTAT database.

How to cite: Müller Schmied, H., Cáceres, D., Eisner, S., Flörke, M., Niemann, C., Peiris, T. A., Popat, E., Portmann, F. T., Reinecke, R., Schumacher, M., Shadkam, S., Telteu, C. E., Trautmann, T., and Döll, P.: The global freshwater availability and water use model WaterGAP 2.2d, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11434, https://doi.org/10.5194/egusphere-egu2020-11434, 2020.

Large-scale hydrological models have been widely used for water resources management, such as studying human impacts (e.g., pumping and irrigation) on groundwater. Currently, most of these models do not explicitly include karst features for the recharge and groundwater simulations. However, the geological properties in karst regions substantially differ from non-karst areas, which makes recharge and groundwater flow behaviors distinctly different between the two types of systems. Due to challenges of combining karstic and non-karstic processes, of simulating inter-catchment groundwater flow, and of parameterizing karstification over large areas in karst regions, global karst groundwater flow models currently do not exist. In this study, we propose a general approach to integrate karstic and non-karstic processes and a hierarchical approach to confine the karstic groundwater flow parameters over large domains. First, we selected six karstic catchments (with different catchment sizes and climates) with adequate observations to test the combination of karstic and non-karstic simulations at the aquifer and catchment scale. We show that using system signatures helps to identify the necessary model structures and to integrate karstic and non-karstic processes. Second, we defined an Inter-catchment Groundwater Flow index (IGF) to quantitatively address groundwater flow crossing topographic boundaries. Third, we classify the level of karstification based on spring and catchment properties and evaluate different strategies for parameterization of karstic groundwater flow processes at varying degrees of karstification. Overall, our study provides a solid basis for a continental-scale karstic groundwater flow model, complementary to current global scale hydrologic modeling efforts where this process is still missing.

How to cite: Liu, Y., Wagener, T., and Hartmann, A.: Flow simulation in karst regions from the scale of single aquifers to entire continents, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-653, https://doi.org/10.5194/egusphere-egu2020-653, 2020.

West Africa has been classified as one of the most vulnerable regions in the world for water resources to face global changes, both climatic and demographic. The population is expected to double by 2050 leading to increased pressure on the use of water resources. In this context, it is necessary to understand the dynamics of major African hydrosystems as large rivers (Niger river, Senegal river...) and transboundary aquifers in order to predict the fate of water resources for the next decades. The ParFlow-CLM physical-based model was chosen for its ability to simulate surface water and groundwater dynamics in a coupled manner. This type of modelling makes it possible to represent the main hydrological processes observed over the whole West Africa region. It operates at a relatively fine spatial resolution (1 km²). The main challenge is to determine the hydrodynamic parameters of the soil for the entire region and on a 100 m thickness (i.e. 3.5 million pixels times 11 layers).

As a first step, the model was implemented on two catchments monitored by the AMMA-CATCH observatory. These two watersheds are representative of the major and contrasted processes found in WA : being respectively representative of Sudanian and Sahelian climates. In order to assess the relevance of the regional databases (SoilGrids and GLHYMPS), simulations were carried out with original and adjusted (based on observations) soil parameters and results were evaluated with local measurements. It appears that the deep weathered lithology is not considered in databases for most of hard-rock areas in intertropical areas with no tectonic uplift. Aquifer thicknesses, permeabilities and porosities have to be significantly enhanced for the model to represent the correct flow paths. Furthermore, in the Sahel where most of the annual precipitation falls during a dozen events only, a crust layer (consistent with observations) has been added to represent the large runoff coefficients which lead to the early season floods.

In a second step, the model was implemented at the West Africa scale using the adjusted soil parameters. These parameters were obtained using a simple linear law that have been applied uniformly over the entire domain and a mask over a part of the Sahel representative of the crusting zones. Results will be compared with both remotely sensed and in situ data : GRACE provides water stock variations at a very large scale, MERRA and ERA reanalysis provide evapotranspiration data. Altimeters and in situ measurements provide river flow data. In the near future the launch of the SWOT satellite will bring new observations to complete the current one. The evaluation of the different compartments of the hydrological cycle should reveal spatial discrepancies in the model's ability to represent processes, highlighting the points on which further work should focus.

How to cite: Depeyre, A., Cohard, J.-M., Hector, B., Maxwell, R., and Pellarin, T.: Large scale high resolution modelling of the West African rivers and aquifers, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21545, https://doi.org/10.5194/egusphere-egu2020-21545, 2020.

Offshore freshened groundwater (OFG) is an important component of the global water cycle. Bodies of fresh and moderately brackish groundwater have been documented up to 100 km from modern shorelines. Their global volumetric estimates are on the order of 500,000 cubic kilometres, which is two orders of magnitude greater than the volume of groundwater extracted globally from continental aquifers since 1900. The potential use of OFG systems as a source of potable water is a main driving force for their improved understanding. OFG systems also play a fundamental role in biogeochemical fluxes to the ocean and in benthic and sub-seafloor ecology.

The majority of OFG systems were emplaced by groundwater migration across topographic gradients via permeable connections between offshore and onshore aquifers. The characteristics and dynamics of the offshore aquifers remain poorly constrained, however. There are many first order questions waiting to be addressed, mainly related to the geometry, distribution and dimensions of these aquifers, as well as their flow and emplacement dynamics.

In this study we integrate hydrological modelling with borehole data and offshore geophysical observations from the Canterbury margin (New Zealand) to quantitatively characterise an onshore-offshore groundwater system. Onshore, the main aquifers are hosted in gravels down to at least 150 m depth, with unconnected sand and silt/clay layers forming aquitards. The regional flow of groundwater in the Canterbury aquifers is from the foothills of the Southern Alps towards the sea. Offshore, the groundwater system consists of one main, and two smaller, low salinity groundwater bodies. The main OFG body extends up to a distance of 60 km from the coast to a water depth of 110 m, has a maximum thickness of at least 250 m, and an estimated volume that ranges between 56 and 213 cubic kilometres. It exhibits along-shelf variability in salinity, which we attribute to permeability heterogeneity due to permeable conduits and normal faults, and recharge from rivers during sea level lowstands. A meteoric origin of the OFG and active groundwater migration from onshore are inferred. However, the majority of the OFG was emplaced via topographically-driven flow during sea level lowstands in the last 300 ka.

This study demonstrates that the integration of hydrological modelling, borehole and geophysical data is a powerful approach to quantitatively characterise groundwater systems across continental margins. Applying this approach globally is likely to result in a significant revision of global volumetric estimates of OFG.

How to cite: Micallef, A., Person, M., Haroon, A., Weymer, B., Jegen, M., Schwalenberg, K., Faghih, Z., Duan, S., Cohen, D., Mountjoy, J., Woelz, S., Gable, C., Averes, T., and Tiwari, A.: Onshore-offshore hydrological characterisation of the Canterbury margin (New Zealand) based on geophysical and modelling techniques, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5927, https://doi.org/10.5194/egusphere-egu2020-5927, 2020.

Large-scale groundwater models are needed for assessing impacts of global changes, such as the “Global Warming”, and adapt the groundwater management strategies to ensure its availability. However, the construction of these models presents numerous difficulties, among which the lack of data concerning the properties (hydraulic parameters and geometries) of the subsurface is the most problematic. Although it is possible to find data concerning the hydraulic parameters of the soil (hydraulic conductivity and porosity), there is no realistic information about the saturated aquifer thickness which contributes to the active part of the flow regime. This thickness, which can be named “effective thickness”, is of paramount importance to improve the representativeness of large-scale groundwater models.

Commonly, a constant “effective thickness” is assumed for global models, which provides not a realistic boundary condition. Here, we propose a new approach based on spectral analyses of the baseflow in combination with hydraulic conductivity values to derive the spatial distribution of “effective thickness”. The calculated “effective thickness” can be used to build 2D groundwater models using a transmissivity field or to constrain the thickness in 3D models. The effectiveness of this approach is tested here by constructing Europe-wide groundwater. The representativeness of the model is improved by coupling off-line a mesoscale hydrological model (mHM), which computes near-surface water processes, and the deep groundwater simulation using the numerical model of OpenGeoSys.We demonstrate the implications of our study in conducting large-scale groundwater simulations across Europe for providing continental scale assessment of the impacts of global changes on groundwater system and discussing about the adaptation of different water management strategies affecting the regional groundwater system.

How to cite: Pujades, E., Houben, T., Di Dato, M., Kumar, R., and Attinger, S.: A European groundwater model with variable aquifer thickness derived from spectral analyses of baseflow, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11140, https://doi.org/10.5194/egusphere-egu2020-11140, 2020.

  Groundwater is one of the important water resources in the world and Groundwater flow is linked with surface water strongly. Many studies on groundwater are conducted in a local scale or focused on affect-ing surface water in a global scale. In current Earth System Model, fixed and constant one-dimensional vertical grid is used in unsaturated zone. In real world, the thickness of unsatu-rated zone depends on the climate and it is considered that there are limitations of runoff process expression especially in humid mountainous area. In this study, we developed three-dimensional groundwater flow model as ESM which can represent the variably saturated flow and groundwa-ter storativity. Since, this model is eventually coupled with Land Surface Model, it is possible to track the underground water flow using boundary conditions of recharge and surface water level.

  We verified accuracy of the code using one & two-dimensional infiltration problem, three-dimensional groundwater pumping problem, and hillslope problem. Our model was com-pared with other researchers results, experimental data, analytical solutions. In consequence, our model was able to get accurate results. Subsequently, we conducted validation in Central valley, California, USA. The reason of chose this region is that this region is a semi-arid region, ground-water is used for irrigation and well pumping data is accessible. Over the world, groundwater use is more important in arid or semi-arid region than in humid area, and also highly utilized as agri-cultural water. Central valley has representativeness of groundwater use. In addition, the famous groundwater model, MODFLOW, was used to evaluate water resource management in this region. As well as MODFLOW, we calibrated hydraulic conductivity with 24 observation sites during 1961 - 2003 to validate. 156 observation points excluded 24 calibration points were used as vali-dation in same period. In the near future, we will confirm the difference between one-dimension and three dimensions setting of the unsaturated zone with respect to runoff process.

How to cite: Miura, Y. and Yoshimura, K.: Development, verification and validation of a three-dimensional groundwater flow model for ESM, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12117, https://doi.org/10.5194/egusphere-egu2020-12117, 2020.

The Mediterranean region is recognized as one of the most sensitive regions in the world to water scarcity, due to both climate change and consistently increasing anthropogenic pressures. Groundwater is considered as a strategic freshwater reserve in the Mediterranean region; however, its status remains poorly characterized and its total budget uncertain. In recent years, groundwater modelling has moved from local to regional/global scale, offering insights into the status of data-scarce regions. However, it remains unclear to what extent those models can be used to support management decisions. This study aims to compare and evaluate the performance of three groundwater models to represent the steady-state groundwater levels in the Mediterranean region. Thus, the groundwater models of Reinecke et al. (2019), de Graaf et al. (2017) and Fan et al. (2013) will be utilized in this study. The preliminary results indicate that, in the northern part of the Mediterranean region, the models of Reinecke et al. (2019) and de Graaf et al. (2017) predict similar water table patterns. However, both models simulate completely different groundwater regimes in the desert regions; the predicted groundwater table of de Graaf et al. (2017) model is significantly deeper than of Reinecke et al. (2019) model. This could be, probably, because of the calibration of de Graaf et al. (2017) model compared to Reinecke et al. (2019) model, which is not yet calibrated. A detailed comparison between simulated and measured water table depth of different Mediterranean aquifers having different climatic, geologic and anthropogenic conditions will be presented.

References

Reinecke, R. et al. Challenges in developing a global gradient-based groundwater model (G3M v1.0) for the integration into a global hydrological model. Geosci. Model Dev 12, 2401-2418 (2019).

de Graaf, I. et al. A global-scale two-layer transient groundwater model: Development and application to groundwater depletion. Adv. Water Resour 102, 53-67 (2017).

Fan, Y. et al. Global patterns of groundwater table depth. Science 339, 940-943 (2013).

How to cite: Ben-Salem, N., Wachholz, A., Rode, M., Borchardt, D., and Jomaa, S.: Evaluation of three global gradient-based groundwater models in the Mediterranean region , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8237, https://doi.org/10.5194/egusphere-egu2020-8237, 2020.

Saltwater intrusion into estuaries is a natural phenomenon which impacts freshwater availability for irrigation and human consumption. The intrusion length is dependent on the river discharge, sea level fluctuation and deltaic shape. As climate change impacts the sea level fluctuations and river discharge in many areas in the world it is expected that the intrusion length of rivers will change in the coming decades. However, global scale assessments are currently lacking, since estimates of the intrusion length are usually done for individual rivers, with complex models requiring extensive spatio-temporal data.
In this study, we provide a first global estimate of saltwater intrusion in estuaries. To do this, we first evaluate an existing predictive model for the salt water intrusion length on a local scale, before transitioning to global input data of river discharge, deltaic shapes and sea level. We assess the predictive quality of the model and its sensitivity in regard to uncertainties in (global) input data before giving an estimate of salt intrusion globally.
By using large ensemble-simulations of discharge on a global scale in a warmer climate (+2 °C), we further project impacts of climate change on the saltwater intrusion length and identify highly affected delta systems. The ensemble-simulations allow extreme events and respective estimations of frequency and magnitude. This is especially relevant since high salinity levels usually occur during droughts when river discharge is low and freshwater resources are diminished.

How to cite: Götte, J., Thorslund, J., and Wanders, N.: Saltwater intrusion in delta regions around the globe, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20402, https://doi.org/10.5194/egusphere-egu2020-20402, 2020.

The currently ongoing CMIP6 simulations feature Earth System Models with interactively coupled components for atmosphere, ocean and land surface. Water, energy and momentum between these components are exchanged conservatively. This is crucial to compute climate interactions and their feedbacks consistently. Currently, the representation of biogeochemical cycles in land surface and ocean models is advancing including not only a carbon cycle but also processes based on nutrients like nitrogen or phosphorus. Some land surface models (LSM) already compute leaching of such constituents from the soil, and some ocean models (OM) consider nutrient influx from the land for a number of processes, e.g. biological activity. However, the OMs usually use observed data as input instead of the nutrient loads computed by the LSMs. This setup cannot represent the effects of climate or land use change on nutrient availability and therefore limits the applications of ESMs in respect to climate change impacts.

For this reason, we are extending our hydrological discharge model, the HDM, to not only transport water but also other constituents. The HDM is an established component of regional (GCOAST, ESM ROM, Reg-CM-ES) as well as global (MPI-ESM) climate models but also applicable as stand-alone model. In a first step, only inert transport is simulated without considering any chemical reactions or biological transformation during river flow. The transport is realized using the same linear cascade infrastructure as used for water transport. However, a successful offline validation of these new features does not only require a realistic routing scheme and consequently the representation of the most important reactions during transport, but also the generation of sensible input data either from large scale models or from observations. In our presentation, we will outline the state of this work together with the compiled input dataset.

How to cite: Stacke, T., Hagemann, S., Romero-Mujalli, G., Hartmann, J., and Thomas, H.: Simulating riverine nutrient transport on global scale, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8167, https://doi.org/10.5194/egusphere-egu2020-8167, 2020.

Annual runoff is important information on water balance in the catchment and large river basin scale. It forms the boundary conditions for mathematical modelling of hydrological balance on a finer temporal and spatial scale. It is important for the assessment of climate change on water resources. Currently, there are several datasets on global gridded runoff fields available. GRUN and E-RUN provide monthly estimates of runoff rate with the spatial resolution of 0.5 degree. The GRUN is global dataset and E-RUN is covering Europe ^1,2.In this study, we evaluate the capability of paleoclimate reconstructions on precipitation, PDSI, and temperature, which are available in the form of gridded fields, to estimate annual surface runoff using selected machine learning techniques. For this purpose, we use as a benchmark runoff information GRUN and E-RUN data sets. Both data are aggregated on the annual time scale for the period 1902 – 2014 (GRUN) and 1952-2015 (E-RUN). Following machine learning algorithms were tested: Random forests, SVM, MLP, LDA and Extra Trees. Reconstructed precipitation, temperature, PDSI³ and runoff estimated using selected Budyko models with different spatial aggregation served as inputs^4–7 . Different combinations of inputs were analysed.Our results show that the estimated surface runoff is in good agreement with E-RUN and GRUN datasets for analysed periods. The result and newly tested approach based on derived machine learning models can be further applied to the estimation of paleoclimatic reconstructions of runoff fields.

References:

How to cite: singh, U., Pradhan, R. K., Pratap, S., Hanel, M., Markonis, I., Nasreen, S., and Maca, P.: Estimation of annual runoff using selected data machine learning algorithm, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18223, https://doi.org/10.5194/egusphere-egu2020-18223, 2020.

Indian rivers are an inevitable part of the nation’s economy and society due to which it is necessary to understand the water budget for Indian sub-continental river basins. The available water and energy both play a prominent role in the runoff generation. However, the sensitivity of precipitation and temperature in runoff estimates are not well-explored. Here, we estimate the total runoff using  Budyko’s original water balance model for 220 sub-basins that are selected based on the major discharge stations in India. The Budyko’s total runoff is well correlated with the Variable Infiltration Capacity (VIC) simulated total runoff. Further, we estimate the precipitation elasticity and potential evaporation (PET) sensitivity of total annual runoff using the second-degree linear relation. We find that runoff is more sensitive towards the change in precipitation rather than the change in temperature in Cauvery, South Coast, Pennar, East Coast and Krishna basins. However, Indus and Brahmaputra basins show the contrasting pattern.  

How to cite: Bharat, S. and Mishra, V.: Budyko’s framework to estimate Runoff sensitivity for the Indian sub-continental river basins , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10444, https://doi.org/10.5194/egusphere-egu2020-10444, 2020.