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Investigating the Optimal Configuration of Conceptual Hydrologic Models for Satellite-Rainfall-Based Flood Prediction

In this letter, we investigated the optimal configuration of conceptual hydrologic models for satellite-rainfall-based flood prediction in the 970-km2 Upper Cumberland basin of Kentucky. We explored the impact of integrating NASA's real-time global satellite rainfall product (IR-3B41RT), available at 0.25deg-hourly resolution, in four conceptual model configurations: three built using the modular Hydrologic Modeling System of the Hydrologic Engineering Center that focused on structural differences in infiltration schemes (i.e., National Resources Conservation Service (NRCS) curve number (CN) method, Green-Ampt infiltration method, and deficit/constant loss method) and the fourth being the topographic-index-based TOPMODEL. For the case presented in this letter, a spatially distributed model application did not appear to yield greater accuracy than lumped approaches when using spatially distributed satellite rainfall data for such a medium-sized basin. In general, the NRCS CN method was found to be most effective in terms of minimizing flood prediction uncertainty, followed by the Green-Ampt infiltration and deficit/constant loss methods.