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Science Case 5 (led by University of Trento): Water balance closure over all regions
Although high-resolution satellite, hydrological, and land surface models are advancing, accurately understanding the water cycle in catchments remains challenging due to uncertainties in data accuracy, spatial variability, and the complex interactions between surface and subsurface processes. This science case leverages multiple state-of-the-art satellite datasets and hydrological/land surface models. We evaluated the water cycle closure for the Po River Catchment using 84 different combinations of precipitation, actual evapotranspiration (ET), and runoff. This assessment incorporated Earth-observed precipitation (CNR-IRPI combined product) and evapotranspiration (MODIS Terra), selected based on the round-robin evaluation conducted in WP4, along with outputs from six models—mHM, PCR-GLOBWB, CLM, TETIS, Wflow, and GEOframe—within WP5-Experiment 2. For the Rhine River Catchment, the evaluation included 40 combinations, based on the outputs of four hydrological models: mHM, PCR-GLOBWB, CLM, and Wflow_sbm. Similarly, for the Tugela River Catchment, 40 combinations were evaluated using outputs from the models: mHM, PCR-GLOBWB, TETIS, and Wflow_sbm. Fig. 1 shows the scheme of different combination over this study. The heatmaps in Fig. 2 present the primary results, showing annual water cycle residuals for various combinations of precipitation, ET, and runoff across the different catchments. Lighter shades of red or blue indicate smaller residuals, meaning a better closure of the water budget in each catchment. Figure 1: Overview of different combinations of water cycle variables, integrating various hydrological models and Earth Observation (EO)-based data for Po, Rhine and Tugela Catchments. Figure 2: Mean annual water cycle residuals calculated for each combination over the Po (a1), Rhine (b1), and Tugela (c1) catchments, based on individual data availability periods. Panels a2, b2, and c2 show residuals for the common data period (2007–2021) using EMO precipitation. Panels a3, b3, and c3 present the corresponding residuals for the same period (2007–2021), but using precipitation from the CNR-IRPI product, for the Po, Rhine, and Tugela catchments, respectively.
Science Case 3 (led by Utrecht University): Investigating the added benefit of EO products for simulating reservoir operations
Although reservoir operations have strong impacts on local to regional surface water hydrology, many land-surface and hydrological models simply ignore reservoir operations altogether. For those land-surface and hydrological models that do include reservoir operations, operations often rely on generalized rules that may not be suitable for all reservoirs. Therefore, the aim of science case 3 is to investigate the added benefit of EO products for simulating reservoir operations. To investigate the added benefit of EO product, we compared EO-based reservoir storage estimates of GloLakes with discharge observations up and downstream of reservoirs in the Tugela river basin in South Africa, the primary region of interest. GloLakes provides valuable information on reservoir storage dynamics, which allows for estimating potential reservoir impacts on discharge. However, our results show that the reservoirs in the Tugela river basin have an insubstantial impact on the surface hydrology. No substantial discharge alternations were identified from the discharge observations, and the variability in reservoir capacity and storage was relatively small compared to the annual discharge. Our science case continued to the Italian Po river basin, the secondary region of interest. Unfortunately, no EO-based reservoir storage estimates are available in this region, as the spatial coverage of GloLakes is limited and does not cover the region’s major reservoir. Therefore, we relied on hydrological simulations, both with and without reservoir operations, of surface hydrology to estimate the impact of reservoir operation in the Po river basin. Our results indicate that larger reservoirs in the Po river basin have an insubstantial impact on discharge, whereas smaller reservoirs can strongly affect discharge locally. Due to the limited impacts of reservoirs in the Tugela basin and the lack of EO-based observations in the Po, our science case could not conclusively investigate the added benefit of EO products for simulating reservoir operations. Nevertheless, the potential of EO-based reservoir storage estimates are substantial. Not only will such EO-based products allow for correcting hydrological simulations without reservoirs, but they would also allow better approximation of reservoir operation rules, tailored to individual reservoirs. Therefore, further investment in EO-based reservoir storage estimates, especially in highly managed river basins, is needed to improve the state-of-the-art in hydrological modellin. Figure 1: Simulated multi-year monthly median discharge (m3 s-1) with and without reservoirs for the Miorina reservoir. Colors indicate the hydrological models whereas linetypes indicates simulations with and without reservoirs. The shaded area indicates the 25th to 75th percentile range.
Defining the Science Cases in WP6
Based on the outcomes of the Round Robin exercise and hydrological modeling activities in Work Package 5 (WP5), the project has identified five core science cases (CS), each addressing a key water-related challenge across different regions: CS1: Forecasting extreme streamflow in the Rhine River Basin – led by FZJ CS2: Simulating soil-moisture droughts in Europe – led by UFZ CS3: Assessing the added value of Earth Observation (EO) products for simulating reservoir operations and their impacts on hydropower potential and water resources in the Tugela River Basin – led by UU CS4: Improving water and irrigation management in the Po River Basin – led by UPV CS5: Achieving water balance closure across all regions – led by UT Stay tuned for upcoming posts, where we will present the results of each science case and highlight key publications will be emerging from this work.
Session HS2.2.1 in EGU25: Advancing Process Representation for Hydrological Modelling Across Spatio-Temporal Scales
Don’t miss this exciting session at the upcoming EGU Conference! Connect with leading experts and engage in meaningful and interesting discussions. Stay tuned for updates on the exact time and location!
What happened in the third milestone meeting?
The third milestone meeting took place in November 2024, featuring insightful discussions between the EO and modeling communities, alongside presentations of project results. Below are some general conclusions related to the project: The EO team should join the science cases, We need to translate the scientific results from the Science Cases to a story line that can be follow by non-scientists, Time is not an issue, and we can delay the end date of the project, but no extra money is available for that, In 2026, there would be some ESA money for opening a new call where 4DHydro could apply for an extension of the Science Cases. You can find the interesting results of the project and some other presentations here in this link.
New Paper Released: Multi-model hydrological reference dataset over continental Europe and an African basin
We are excited to announce the publication of a new paper under the European Space Agency’s 4DHydro project: Hyper-resolution Earth Observations And Land-surface Modeling For A Better Understanding Of The Water Cycle Here is a summary of the paper: Although Essential Climate Variables (ECVs) have been widely adopted as important metrics for guiding scientific and policy decisions, the Earth Observation (EO) and Land Surface and Hydrologic Model (LSM/HM) communities have yet to treat terrestrial ECVs in an integrated manner. To develop consistent terrestrial ECVs at regional and continental scales, greater collaboration between EO and LSM/HM communities is needed. An essential first step is assessing the LSM/HM simulation uncertainty. To that end, we introduce a new hydrological reference dataset that comprises a range of 19 existing LSM/HM simulations that represent the current state-of-the-art of our LSM/HMs. Simulations are provided on a daily time step, covering Europe, notably the Rhine and Po river basins, alongside the Tugela river basin in Africa, and are uniformly formatted to allow comparisons across simulations. Furthermore, simulations are comprehensively validated with discharge, evapotranspiration, soil moisture and total water storage anomaly observations. Our dataset provides valuable information to support policy development and serves as a benchmark for generating consistent terrestrial ECVs through the integration of EO products. 📥 Explore the full dataset and results her
Workshop Announcement
We are excited to invite you to a workshop focused on the latest developments and findings from the 4DHydro project, taking place from November 25-27 in Frascati, Italy. The project has reached its midpoint and is progressing toward maturity. We eagerly await your participation to discuss the exciting results and achievements of this project. Location: Frascati, Italy Dates: November 25-27, 2024 We look forward to your participation!
EGU General Assembly 2024
📅 Mark your EGU calendars for Monday, April 15th (10:45–12:30): Oral AND Tuesday 16th (08:30–12:30): poster! 📅 🏢 Join us in Room 2.17 for the oral presentations! 🏢 🏢 Join us in Hall A for the poster presentations on site! 🏢 🔍 See the abstracts 🔍 🎈 See you there for a fruitful discussion! 🎈
Which step are we at (updated in September 2024)?
Work Package 0 Management and Synthesis Activities (Status: In progress): WP0 is in charge of the coordination of the project and the communication of between project partners and with ESA delegates. Work Package 1 Consolidation of a Reference EO dataset (Status: Done ): Water cycle variables studied during the project and the hosting partner ( sources of figure extraction) The first step of the project is to catalogue, retrieve and prepare a set of reference Earth Observations (EO) dataset. This dataset gathers remotely-sensed products monitoring essential variables from the continental water cycle at high-resolution that are soil moisture, evapotranspiration, precipitation, snow, surface water, ground and total water storage, irrigation. This Work Package (WP) is a group effort as several partners from the consortium implemented on this dataset, each partner being leader of a given variable from the above list while CSGROUP managed the overall WP. The purpose was then to organize a collection of EO products and also extract and prepare them for each of the study regions and the study period. This EO reference dataset will then be studied and compared through the Round Robin study in WP4. Work Package 2 Consolidation of a Reference LSM dataset (Status: Done ): 4dHydro working package 2 aims to deliver and benchmark a (tier 1) hydrological reference dataset. This dataset comprises of existing LSM/HM simulations from previous studies and covers a wide range of LSM/HM models and simulations. Despite this diversity, simulations in the reference dataset are uniformly formatted following our storage protocol (see the working package 2 User Manual under 4dhydro.eu/outputs). This uniformity allows for seamless comparisons across simulations in our benchmark. The benchmark comprehensively validates the dataset’s simulations using observations from discharge gauges, evapotranspiration towers, soil moisture stations, and satellite-based total water storage anomaly measurements. comparison of simulated and observed discharge Work Package 3 Community Open Science Data & Code sharing Tool (Status: In progress): WP3 is developing an Open Science Data and Code sharing Tool offering easy access to the EO and non EO datasets, code and model results. This team is responsible for managing the Open Science Catalogue. Work Package 4 Round Robin Experiment (Status: In progress): Revision date: March 14, 2024 WP4 has the goal of cross-comparing state-of-art, high resolution Earth Observation datasets in the domains of: soil moisture, precipitation, evapotranspiration, and snow depth and extent. The output of the activity feeds into the subsequent EO-model integration project phase by defining strengths and weaknesses of the observational products with respect to the most comprehensive available reference data. Advanced statistical methods are employed to provide uncertainty information and objective skill criteria for the candidate datasets, as well as defining their spatial scale representativeness (figure below). Overview of the multi-scale analysis of the SMAP NSIDC 1km soil moisture product (Lakshmi & Fang, 2023) over the various domains, against the 0.1° resolution ERA5 Land (E5L, Muñoz-Sabater et al., 2021), the 0.0125° mesoscale Hydrologic Model (mHM, Samaniego et al., 2010), and the ISMN point measurements (Dorigo et al., 2021). The coloured points show the temporal correlation against ISMN. Dorigo, W., Himmelbauer, I., Aberer, D., Schremmer, L., Petrakovic, I., Zappa, L., Preimesberger, W., Xaver, A., Annor, F., Ardö, J., Baldocchi, D., Bitelli, M., Blöschl, G., Bogena, H., Brocca, L., Calvet, J.-C., Camarero, J. J., Capello, G., Choi, M., Cosh, M. C., van de Giesen, N., Hajdu, I., Ikonen, J., Jensen, K. H., Kanniah, K. D., de Kat, I., Kirchengast, G., Kumar Rai, P., Kyrouac, J., Larson, K., Liu, S., Loew, A., Moghaddam, M., Martínez Fernández, J., Mattar Bader, C., Morbidelli, R., Musial, J. P., Osenga, E., Palecki, M. A., Pellarin, T., Petropoulos, G. P., Pfeil, I., Powers, J., Robock, A., Rüdiger, C., Rummel, U., Strobel, M., Su, Z., Sullivan, R., Tagesson, T., Varlagin, A., Vreugdenhil, M., Walker, J., Wen, J., Wenger, F., Wigneron, J. P., Woods, M., Yang, K., Zeng, Y., Zhang, X., Zreda, M., Dietrich, S., Gruber, A., van Oevelen, P., Wagner, W., Scipal, K., Drusch, M., and Sabia, R.: The International Soil Moisture Network: serving Earth system science for over a decade, Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, 2021. Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., and Thépaut, J.-N.: ERA5-Land: a state-of-the-art global reanalysis dataset for land applications, Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, 2021. Lakshmi, V. and B. Fang. 2023. SMAP-Derived 1-km Downscaled Surface Soil Moisture Product, Version 1. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/U8QZ2AXE5V7B. Accessed: 09-09-2023. Samaniego, L., Kumar, R. & Attinger, S. Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale. Water Resour. Res. 46, https://doi.org/10.1029/2008WR007327 (2010). Revision date: September 28, 2024 Currently working on Deliverable M4.2, which is the community round-robin paper. Work Package 5 Benchmarking and Data-assimilation experiment (Status: In progress): Revision date: March 14, 2024 4DHydro working package 5 builds on earlier simulations analysed in WP2, and it further aims at adjusting the source code of the LSMs and HMs to be able to run multiple high-resolution simulations. Compared with earlier WP2 simulations, we will employ unified meteorological forcing data sets here. The hydrological simulations will be performed at different spatial resolutions (i.e. 1km and 5km, as shown here) and evaluated over multivariate characteristics with hierarchically increasing complexity. Different spatial scales and EO scenarios with and without in-situ observations will be tested across three domains of interest and ultimately evaluated in the European domain at 1km. The discharge simulation using mHM model at high spatial resolution (0.015625 degree) The discharge simulation using mHM model at low spatial resolution (0.125 degree). Summary of the Current Status of WP5: Revision date: September 28, 2024 The fifth work package (WP5) of the 4DHydro project focuses on conducting benchmarking exercises to evaluate model performance before and after integrating high-resolution Earth Observation (EO) data. The ultimate goal is to generate improved terrestrial Essential Climate
How reference data into STAC Catalog
Description 4DHydro is a project funded by ESA which aims to provide a study of selected geospatial and climate data to improve the understanding, observation and monitoring of the availability of water resources planet earth. This GitHub project has been created to collect the metadata of the EO, LSM or Insitu data involved in this study, Features Centralizing the collection of metadata from all consortium partners Possibly open up the metadata contribution to other contributors at the end of the project. Verify the validity and consistency of metadata according to project specifications. Create a STAC catalog from this metadata, which will be automatically updated when new metadata is added. You can find the full tutorial on the following links https://github.com/4dhydro/4dhydro-open-science-catalog-metadata