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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.
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!
Discover Useful Files: Explore Our Repository!
Interested in accessing the latest project outputs? Find out how to download them from this webpage. Interested in reviewing presentations from our last milestone meeting? Check out this repository.
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! 🎈
Who is in charge for ground/EO data in the projcet?
In the context of WP1, data preparation involves generating, consolidating, and cataloging a comprehensive reference Earth Observation (EO) dataset covering the project’s four study zones. This reference dataset comprises: – A high-resolution EO dataset, featuring products with resolutions below 1 km, encompassing various water cycle-related variables. – An additional products dataset containing other EO products at coarser resolutions. – A collection of in-situ datasets serving as references. The 4DHydro consortium proposes organizing the product collection into subtasks, each focusing on a specific variable or group of related variables (e.g., rivers and lakes products), led by the consortium partner with the most relevant expertise. Partners will host their own products whenever possible, while any remaining products (e.g., open data) will be referenced or hosted in a dedicated storage volume created for the project. Additionally, user manuals will be developed for each product by the leader of the corresponding subtask. Soil Moisture: TUW will supply high-resolution products from the Copernicus Global Land Service (CGLS), including SSM1km derived from Sentinel-1 and SWI1km derived from fused Sentinel-1 and ASCAT data (see webpage). Additionally, TUW will contribute a downscaled 1 km soil moisture (SM) dataset from the ESA CCI SM product (expected publication date: early 2023), while UFZ will provide a 1 km global surface soil moisture product based on a dual-channel algorithm using Sentinel-1 synthetic aperture radar observations (expected publication date: early 2023). Coarser resolution SM products, such as ESA CCI SM, will also be gathered in this work package. In-situ measurements from the International Soil Moisture Network will be collected, along with other site-specific measurements when available. Precipitation CNR-IRPI will build upon its experience from previous and ongoing ESA projects (SMOS + Rainfall, DTE Hydrology, 4DMED-Hydrology) to create a high-resolution (1 km, daily) precipitation product covering Europe. This product will merge two SM2RAIN-based (Soil Moisture to RAIN) products utilizing Sentinel-1 and ASCAT soil moisture data with GPM late Run satellite data. However, considering the limitations of satellite soil moisture data in mountainous areas and over snow/frozen soils, special attention will be given to these factors. Consequently, a high-resolution (1 km, 1 day) rainfall product derived from Earth Observation (EO) data will be developed and validated for hydrological applications. Evapotranspiration UFZ will collect the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) product, the MODIS global evapotranspiration product and other datasets generated for this project using the HOLAPS, ALEXI and DisALEXI models. Lower resolution products widely used in the literature, like the Global Land Evaporation Amsterdam Model (GLEAM) product, will be collected for comparison purposes. Additionally, evapotranspiration measurements from eddy covariance sites will be collected from different databases for the validation and evaluation of EO products. Lake, river water level change and river discharge Deltares will leverage on Global Water Watch and related ESA Surface2Storage project. Within these projects high-resolution EO data is used to quantify surface water extent, level and volume, by combining data from sensors that can capture these types of dynamics (e.g., Sentinel-2 for surface water extent, ICESat-2 for water levels), enhanced by in-situ measurements when available. The combination with hydrological models enables a detailed assessment of reservoir inflow and outflow, which in the case of large reservoirs is a critical component of the downstream flow regime. This data can additionally be used for calibration and/or validation of the models, which is also the case for the river levels and discharge data that are also part of this task. In-situ measurements of this kind will be collected for all study areas and supported by EO datasets. Snow cover and depth MobyGIS tracks snowpack evolution in selected mountain ranges, integrating physical models with EO data, particularly Sentinel constellation-derived snow-covered area data. The approach comprehensively describes domain characteristics, monitoring snow variables like snow-covered area, depth, water equivalent, and melt at high resolution for the Alps, Scandinavia, and mountainous regions of the Rhine and Po basins from 2000 to 2020. Data will be provided as 500 m resolution raster maps, aiding runoff assessment in various case studies. Meteo reanalysis data feeds the model, and in-situ snow depth observations, if available, enhance solid precipitation estimation and melting rate assessment during the melting season. Surface water dynamic mask CSGROUP has developed the Surfwater toolchain for the French Spatial Agency (CNES), generating surface water masks at 10m resolution from Sentinel 1 radar or Sentinel 2 optical images, or a combination of both. The toolchain utilizes the MAJA algorithm to mask or remove clouds in Sentinel 2 images. It can produce single masks or monthly mean water masks to reduce uncertainty. In 4DHydro, CSGROUP – France plans to generate dynamic water masks for the study regions using the Surfwater toolchain and other tools. They will merge products and produce corresponding uncertainty maps when feasible. Additionally, they will compile existing open datasets of dynamic surface water masks, such as Landsat Collection 2 (C2) Level-3 Dynamic Surface Water Extent (DSWE) or those from project partners. Irrigation area, time, and quantity In the ESA project Irrigation+, CNR, in collaboration with partners, is exploring, developing and validating advanced Earth Observation-based algorithms and techniques for irrigation mapping, quantification and detection of seasonal timing of irrigation from field to regional/global scale. The project capitalizes on the advent of the European Space Agency (ESA) Sentinel missions in synergy with other data types and models. In 4DHydro the results of Irrigation+, and particularly the regional products available at 1 km resolution for the Po and Ebro river basins. Indeed, the accuracy of the irrigation water product needs to be carefully checked before its use in large scale hydrological modelling. If successful, the integration of Irrigation+ and 4DHydro project results will constitute a ground-breaking result both in terms of scientific achievements and also for the operational management of water resources. Ground water storage and total water storage TUW will collect the satellite-based groundwater storage variations data generated within the H2020 project Global Gravity-based Groundwater Product (G3P, https://www.g3p.eu/). A preliminary groundwater product shall be released by the end 2022. Along with the EO groundwater dataset, we will collect in-situ