Data underlying the research of: Improving forecast skill of lowland hydrological models using ensemble Kalman filter and unscented Kalman filter

Dataset

Description

Research dataset underlying peer reviewed manuscript containing hydrological streamflow forecasts (using perfect forcing) covering a period of 10 years to determine the benefits of streamflow assimilation using the WALRUS hydrological model for a Dutch lowland area (Regge catchment)
Date made available27 Feb 2020
PublisherWageningen University & Research
Geographical coverageRegge, The Netherlands

Keywords

  • Conceptual Hydrological model
  • Ensemble Kalman Filter (EnKF)
  • Lowland Catchments
  • State Estimation
  • The Wageningen Lowland
  • Runoff Simulator (WALRUS)
  • Unscented Kalman Filter (UKF)

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