Abstract
This study investigates the utility of satellite-based rainfall estimates in simulating flash floods in Karpuz River Basin, Turkey, characterized by limited rain gauge network. Global Satellite Mapping of Precipitation (GSMaP) product was evaluated with the rain gauge network at daily and monthly time-scales considering seasonality, elevation zones, extreme events and rainfall intensity thresholds. Statistical analysis indicated that GSMaP shows acceptable linear correlation coefficient with rain gauges, however, suffers from significant underestimation bias. Statistical measures exhibited a remarkable deterioration with increasing elevation-following a linear relationship; for example, percent bias was found to increase by a rate of 11.7% with every 400 m interval. A multiplicative bias correction scheme was devised, and Hydrological River Basin Environmental Assessment Model (Hydro-BEAM) was implemented to simulate flash floods driven by the uncorrected/corrected GSMaP data. Analysis of intensity thresholds revealed that appropriate threshold selection is critically important for the bias correction procedure. The hydrological model was calibrated for flash flood events during October–December 2007 and 2012 and validated during October–December, 2009 and 2010. Flash floods simulations were improved by the local bias correction procedure applied to the GSMaP data, but the degree of improvement varied from one period to another. The results of the study indicate that bias factors incorporating multiple variables such as extreme events and elevation variability have the potential to further improve flood simulations.
Highlights
Flash floods are among the most devastating natural hazards regarding both mortality and economic loss [1,2]
The objective of the comparison was to evaluate the Global Satellite Mapping of Precipitation (GSMaP) product with the rain gauge dataset in the surroundings of the Karpuz River Basin
The results of the statistical analysis (Table A3 in Appendix A) show that daily rainfall estimates derived from GSMaP product are well correlated
Summary
Flash floods are among the most devastating natural hazards regarding both mortality and economic loss [1,2]. The Mediterranean region is projected to become increasingly exposed to flash floods due to the projected increase in hydrologic extremes [3] and rapid population growth. Operation of early warning systems requires good-quality observations (precipitation, streamflow, etc.), reliable model(s)—for hydrologic and weather prediction—and adequate lead time for the warning to be issued. In the Mediterranean region, flash floods are triggered by heavy precipitation events with accumulated rainfall higher than 100 mm, often within a few hours.
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