We attempted to investigate the utility of gauge-corrected satellite-based rainfall estimates to improve flash floods simulation at semi-arid basin. Different scenarios were conducted to estimate the bias factors to correct GSMaP data. We found underestimated bias and good linear correlation. Also, an appropriate threshold selection is critically important for correction. Then, the HydroBEAM model was calibrated and validated showing a reasonable performance based on the statistical analysis.
We attempted to investigate the utility of gauge-corrected satellite-based rainfall estimates to...
Received: 22 Oct 2016 – Accepted for review: 10 Nov 2016 – Discussion started: 11 Nov 2016
Abstract. This study investigates the utility of gauge-corrected satellite-based rainfall estimates in simulating flash floods at Karpuz River - a semi-arid basin in Turkey. Global Satellite Mapping of Precipitation (GSMaP) product was evaluated with the rain gauge network at monthly and daily time-scales considering various time periods and rainfall rate thresholds. Statistical analysis indicated that GSMaP shows acceptable linear correlation coefficient with rain gauges however suffers from significant underestimation bias. A rainfall rate threshold of 1 mm/month was the best choice to improve the match between GSMaP and rain gauges implying that appropriate threshold selection is critically important for the bias correction. Multiplicative bias correction was applied to GSMaP data using the bias factors calculated between GSMaP and observed rainfall. Hydrological River Basin Environmental Assessment Model (Hydro-BEAM) was used to simulate flash floods at the hourly time scale driven by the corrected GSMaP rainfall data. The model parameters were calibrated for flash flood events during October-December 2007 and then validated for flash flood events during October-December 2009. The results show that the simulated surface runoff hydrographs reasonably coincide with the observed hydrographs.
We attempted to investigate the utility of gauge-corrected satellite-based rainfall estimates to improve flash floods simulation at semi-arid basin. Different scenarios were conducted to estimate the bias factors to correct GSMaP data. We found underestimated bias and good linear correlation. Also, an appropriate threshold selection is critically important for correction. Then, the HydroBEAM model was calibrated and validated showing a reasonable performance based on the statistical analysis.
We attempted to investigate the utility of gauge-corrected satellite-based rainfall estimates to...