Enhancing regional Flood Early Warning Systems using High-Resolution GRACE/GRACE-FO total water storage (TWS) and wetness index data
High resolution gravity field data sets provide valuable information about the wetness state of a catchment, which is a useful indicator in flood early warning systems.
The HiGrav Project aims to increase the temporal and spatial resolution of GRACE/GRACE-FO data and derived TWS and wetness index data. Further, the project will assess the utility of this enhanced information basis for flood forecasting in terms of forecast accuracy and flood early warning reliability.
HydRiv explores if downscaled GRACE/GRACE-FO data sets are useful to improve flood forecasting and warning at a regional scale (areas of around 10.000 km²). For this purpose, the semi-distributed, process-based hydrological model PANTA-RHEI developed by HydRiv, will be used. The model is implemented and used operationally by the Flood Forecasting and Warning Centre in Lower Saxony (NLWKN - HWVZ). In this study, an extended PANTA RHEI model will be developed to dynamically assimilate GRACE/GRACE-FO derived data for regional flood forecasting. The performance of the extended model will be tested in several river basins in Lower Saxony with catchments areas between 3.000 and 15.000 km². The performance of the extended process-based PANTA RHEI model will be compared to both established and novel data-driven flood forecasting models.
September 2025 to August 2028