Satellite precipitation product assessment and correction technique selection at sub-basin scale for maximum annual events. Case study: Acaponeta River basin

Abstract

Satellite precipitation products (SPP) are increasingly being used for detailed hydrological studies due to scarce and discontinuous precipitation observations at different spatial and temporal scales. However, to evaluate its full utility, it is necessary to assess and correct the bias between estimated and observed precipitation (OP). The aim of this paper is to evaluate the CHIRPSv2.0 product for maximum annual events and different climatological conditions based on in-situ observations, using statistical metrics and selecting from linear scaling (LS), local intensity scaling (LOCI) and power transformation (PT) the appropriate bias correction technique (CT), at point and sub-basin scale, improving the maximum annual precipitation records for the period 2001-2020 in the Acaponeta River basin, Mexico. Previous applications of bias CT have focused on broader temporal scales rather than specific maximum events. Differences in the performance of the correction methods were identified between point and sub-basin scales. PT presented a good performance at the point scale, in contrast to percentual bias (PBIAS), which resulted in a great overestimation at the sub-basin scale in the upper zone for the average and dry years, while for the wet year, it overestimated in the lower part. Although LS and LOCI generally observed a good PBIAS reduction at the gauge stations, LS overestimated at the sub-basin scale overall. LOCI showed better SPP corrections in the middle and lower zones and a wider range of overestimation for the upper basins in the middle and wet years. The corrected annual maximum estimated values for the revised period are useful for hydrological analysis in the context of flood risk assessment.