2026-10-14T11:37:51Zhttps://www.radar-service.eu/oai/OAIHandler

10.35097/6002026-10-09T10:43:19ZIMKradar4kit

https://dx.doi.org/10.35097/600 Borne, Maurus Ensemble Kalman-Filter-based seasonal runoff predictions for the Rio São Francisco River Basin Karlsruhe Institute of Technology (KIT) 2023 Geological Science dataset Dataset European Center for Medium Range Weather Forecasts (ECMWF), Copernicus, Brazilian National Water Agency (ANA) Other info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode Lorenz, Christof Portele, Tanja Christina Kunstmann, Harald Martins, Eduardo Sávio Passos Rodrigues das Chagas Vasconcelos Júnior, Francisco In semi-arid regions, interannual variability of seasonal rainfall and climate change is expected to stress water availability and increase the recurrence and intensity of extreme events such as droughts or floods. Local decision makers therefore need reliable long-term hydro-meteorological forecasts to support the seasonal management of water resources, reservoir operations and agriculture. In this context, an Ensemble Kalman Filter (EnKF) framework is applied to predict sub-basin-scale runoff employing global freely available datasets of reanalysis precipitation (ERA5-Land) as well as Bias-Corrected and Spatially Disaggregated seasonal forecasts (SEAS5-BCSD). Runoff is estimated using least squares predictions, exploiting the covariance structures between runoff and precipitation. This repository contains the runoff observations, the final EnKF-based runoff predictions, reference precipitation from ERA5-Land, bias-corrected and spatially disaggregated seasonal precipitation forecats from SEAS5-BCSD as well as shapefiles delineating the sub-basin-boundaries within the Rio São Francisco River Basin. Hydrometeorology Seasonal runoff prediction River basin management Data assimilation Rio São Francisco Lorenz, Christof Portele, Tanja Christina Kunstmann, Harald Martins, Eduardo Sávio Passos Rodrigues das Chagas Vasconcelos Júnior, Francisco eng 10.26050/WDCC/SaWaM_D02_SEAS5_BCSD BRAZIL (Rio São Francisco River Basin): Lat/Long/Datum -25.0 -50.0 -5.0 -35.0 (WGS 84) application/x-tar