Observed and simulated hydroclimatology using distributed hydrologic model from in-situ and multi-satellite remote sensing datasets in Lake Victoria region in East Africa

Abstract

Flooding is one of the most deadly natural hazards around the world. Distributed hydrologic models can provide the spatial and temporal distribution of precipitation, soil moisture, evapotranspiration and runoff. Implementation of a flood prediction and/or forecast system using a distributed hydrologic model can potentially help mitigate flood-induced hazards. In this study, we propose the use of the Coupled Routing and Excess STorage (CREST) distributed hydrological model driven by real-time rainfall forcing from TRMM-based multi-satellite products and/or precipitation forecast data from the Global Forecast System model (GFS), combined with automatic parameter optimization methods, to estimate hydrological fluxes, storages and inundated areas. Evaluations show that: 1) the capability of real-time streamflow prediction and/or forecast at drainage outlets and identification of inundated areas upstream is an achievable goal even for ungauged basins; 2) a-priori, physically-based parameter estimates with CREST reduce the dependence on rainfall-runoff data often required to calibrate distributed hydrologic models; and 3) the validation of CREST simulations of basin discharge are skillful in several basins throughout the world.