The water in Earth’s rivers propagates as waves through space and time across hydrographic networks. A detailed understanding of river dynamics globally is essential for achieving the accurate knowledge of surface water storage and fluxes to support water resources management and water-related disaster forecasting and mitigation. Global in situ information on river flows are crucial to support such an investigation but remain difficult to obtain at adequate spatiotemporal scales, if they even exist. Many expectations are placed on remote sensing techniques as key contributors. Despite a rapid expansion of satellite capabilities, however, it remains unclear what temporal revisit, spatial coverage, footprint size, spatial resolution, observation accuracy, latency time, and variables of interest from satellites are best suited to capture the space-time propagation of water in rivers. Additionally, the ability of numerical models to compensate for data sparsity through model-data fusion remains elusive. We review recent efforts to identify the type of remote sensing observations that could enhance understanding and representation of river dynamics. Key priorities include: (a) resolving narrow water bodies (finer than 50-100 m), (b) further analysis of signal accuracy versus hydrologic variability and relevant technologies (optical/SAR imagery, altimetry, microwave radiometry), (c) achieving 1-3 days observation intervals, (d) leveraging data assimilation and multi-satellite approaches using existing constellations, and (e) new variable measurement for accurate water flux and discharge estimates. We recommend a hydrology-focused, multi-mission observing system comprising: (1) a cutting-edge single or dual-satellite mission for advanced surface water measurements, and (2) a constellation of cost-effective satellites targeting dynamic processes.

Satellite altimetry has successfully monitored inland waters for more than 30 years and is increasingly important as the demand for freshwater grows and climate change accelerates. Launched in December 2022, the Surface Water and Ocean Topography (SWOT) satellite is the first to provide 2D spatially distributed elevation measurements, with a nominal 21-day revisit time and better coverage depending on latitude. Here, we evaluate the SWOT L2 HR PIXC 2.0 data product for constructing water surface elevation (WSE) time series at 40 Danish lakes with a surface area above 0.25km2 via the summary measures RMSE and Pearson Correlation Coefficient (PCC). Two methods to derive the bias between the SWOT-based WSE and the gauge water level were tested; a constant bias and a newly proposed acquisition-specific bias. Based on the 40 gauged lakes we find a median RMSE of 5.76cm and 8.87cm and PCC of 0.93 and 0.76, for the acquisition-specific bias and constant bias, respectively.   Additionally, we examined the spatial variations of the water surface elevations in the L2 HR PIXC 2.0 data product. Compared with ICESat-2, we found that the spatially distributed variations in SWOT data were unlikely to represent real physical phenomena. Our findings highlight the potential of SWOT for generating high-accuracy WSE time series, for small lakes. SWOT’s broad spatial coverage offers far greater temporal frequency (for Danish lakes: usually 3 to 4 acquisitions per 21-day orbit) compared to traditional satellite altimeters, enabling new insights into water level dynamics that were previously unattainable.

Geodetic altimeters provide unique observations of the river surface longitudinal profile due to their long repeat periods and densely spaced ground tracks. This information is valuable for calibrating hydraulic model parameters, and thus for producing reliable simulations of water level for flood forecasting and river management, particularly in poorly instrumented catchments. In this study, we present an efficient calibration approach for hydraulic models based on a steady-state hydraulic solver and CryoSat-2 observations. In order to ensure that only coherent forcing/observation pairs are considered in the calibration, we first propose an outlier filtering approach for CryoSat-2 observations in data-scarce regions using simulated runoff produced by a hydrologic model. In the hydraulic calibration, a steady-state solver computes the WSE profile along the river for selected discharges corresponding to the days of CryoSat-2 overpass. In synthetic calibration experiments, the global search algorithm generally recovers the true parameter values in portions of the river where observations are available, illustrating the benefit of dense spatial sampling from geodetic altimetry. The most sensitive parameters are the bed elevations. In calibration experiments with real CryoSat-2 data, validation performance against both Sentinel-3 WSE and in-situ records is similar to previous studies, with RMSD ranging from 0.43 to 1.14 m against Sentinel-3 and 0.60 to 0.73 against in-situ WSE observations. Performance remains similar when transferring parameters to a one-dimensional hydrodynamic model. Because the approach is computationally efficient, model parameters can be inverted at high spatial resolution to fully exploit the information contained in geodetic CryoSat-2 altimetry.

Introduction HYDROCOASTAL is a two year project funded by ESA, with the objective to maximise exploitation of SAR and SARin altimeter measurements in the coastal zone and inland waters, by evaluating and implementing new approaches to process SAR and SARin data from CryoSat-2, and SAR altimeter data from Sentinel-3A and Sentinel-3B. Optical data from Sentinel-2 MSI and Sentinel-3 OLCI instruments will also be used in generating River Discharge products. New SAR and SARin processing algorithms for the coastal zone and inland waters will be developed and implemented and evaluated through an initial Test Data Set for selected regions. From the results of this evaluation a processing scheme will be implemented to generate global coastal zone and river discharge data sets. A series of case studies will assess these products in terms of their scientific impacts. All the produced data sets will be available on request to external researchers, and full descriptions of the processing algorithms will be provided Objectives The scientific objectives of HYDROCOASTAL are to enhance our understanding of interactions between the inland water and coastal zone, between the coastal zone and the open ocean, and the small scale processes that govern these interactions. Also the project aims to improve our capability to characterize the variation at different time scales of inland water storage, exchanges with the ocean and the impact on regional sea-level changes The technical objectives are to develop and evaluate new SAR and SARin altimetry processing techniques in support of the scientific objectives, including stack processing, and filtering, and retracking. Also an improved Wet Troposphere Correction will be developed and evaluated. Presentation The presentation will describe the different SAR altimeter processing algorithms that are being evaluated in the first phase of the project, and present results from the evaluation of the initial test data set. It will focus particularly on the performance of the new algorithms over inland water.

Introduction HYDROCOASTAL is a two year project funded by ESA, with the objective to maximise exploitation of SAR and SARin altimeter measurements in the coastal zone and inland waters, by evaluating and implementing new approaches to process SAR and SARin data from CryoSat-2, and SAR altimeter data from Sentinel-3A and Sentinel-3B. Optical data from Sentinel-2 MSI and Sentinel-3 OLCI instruments will also be used in generating River Discharge products. New SAR and SARin processing algorithms for the coastal zone and inland waters will be developed and implemented and evaluated through an initial Test Data Set for selected regions. From the results of this evaluation a processing scheme will be implemented to generate global coastal zone and river discharge data sets. A series of case studies will assess these products in terms of their scientific impacts. All the produced data sets will be available on request to external researchers, and full descriptions of the processing algorithms will be provided Objectives The scientific objectives of HYDROCOASTAL are to enhance our understanding of interactions between the inland water and coastal zone, between the coastal zone and the open ocean, and the small scale processes that govern these interactions. Also the project aims to improve our capability to characterize the variation at different time scales of inland water storage, exchanges with the ocean and the impact on regional sea-level changes The technical objectives are to develop and evaluate new SAR and SARin altimetry processing techniques in support of the scientific objectives, including stack processing, and filtering, and retracking. Also an improved Wet Troposphere Correction will be developed and evaluated. Presentation The presentation will describe the different SAR altimeter processing algorithms that are being evaluated in the first phase of the project, and present results from the evaluation of the initial test data set focusing on performance at the coast. It will also present the results of a study assessing regional tidal models.