Assessment of GPM Satellite Precipitation Performance after Bias Correction, for Hydrological Modeling in a Semi-Arid Watershed (High Atlas Mountain, Morocco)

Abstract

Due to its important spatiotemporal variability, accurate rainfall monitoring is one of the most difficult issues in semi-arid mountainous environments. Moreover, due to the inconsistent distribution of gauge measurement, the availability of precipitation data is not always secured and totally reliable at the instantaneous time step. As a result, earth observation of precipitation estimations could be an alternative for overcoming this restriction. The current study presents a framework for either the hydro-statistical evaluation and bias correction of the Global Precipitation Measurement (GPM) Integrated Multi-SatellitE Retrievals version 06 Early (IMERG-E), Late (IMERG-L), and Final (IMERG-F) products. On a sub-daily duration, from the Taferiat rain gauge-based station, which was used as a benchmark from 1 September 2014 to 31 August 2018. Statistical analysis was performed to examine each precipitation product’s performance. The results showed that all Post_Real_Time and Real_Time IMERG had a high level of awareness accuracy. The IMERG-L results were statistically similar to the gauge data, succeeded by the IMERG-F and IMERG-E. The Cumulative Distribution Function (CDF) has been employed to adjust the precipitation values of the three IMERG products in order to decrease bias estimation. The three products were then integrated into the “HEC-HMS” hydrological model to assess their dependability in flow modeling. Six flood occurrences were calibrated and validated for each product at 30-minute time steps. With a mean Nash-Sutcliffe coefficient of NSE 0.82, the calibration findings demonstrate that IMERG-F provides satisfactory hydrological performance. With an NSE = 0.80, IMERG-L displayed good hydrological utility, slightly better than IMERG-E with an NSE = 0.77. However, when the flood events were validated using the initial soil conditions, IMERG F and IMERG E overestimated the discharge by 13% and 10%, respectively. While IMERG L passed the validation phase with an average score of NSE = 0.69.

Keywords

• Satellite Precipitation
• bias correction
• hydrological modeling
• semi-arid region