Precipitation is a crucial source of data in hydrological applications for water resources management. However, several regions suffer from limited data from a ground measurement network. Remotely sensed data may provide a viable alternative for these regions. This study aimed to evaluate six satellite products (GPM-F, CHIRPS, PERSIANN-CCS-CDR, GPM-L, GPM-E and PDIR-Now), with high spatio-temporal resolution, in the sub-Saharan regions of Morocco. Precipitation observation data from 33 rain-gauge stations were collected and used over the period from September 2000 to August 2020. The assessment was performed on three temporal scales (daily, monthly and annually) and two spatial scales (pixel and basin scales), using different quantitative and qualitative statistical indices. The results showed that the GPM-F product performed the best, according to the different evaluation metrics, up to events with 40 mm/day, while the GPM near real-time products (GPM-E and GPM-L) were better at detecting more intense rainfall events. At the daily time scale, GPM-E and GPM-L and, on monthly and annual scales, CHIRPS and PERSIANN-CCS-CDR, provided satisfactory precipitation estimates. Moreover, the altitude-based analysis revealed a bias increasing from low to high altitudes. The continental and mountainous basins showed the lowest performance compared to the other locations closer to the Atlantic Ocean. The evaluation based on the latitudes of rain gauges showed a decrease of bias towards the most arid zones. These results provide valuable information in a scarcely gauged and arid region, showing that GPM-F could be a valuable alternative to rain gauges.

<p>Precipitation is the main component of the hydrological cycle; it is a crucial source of data in hydroclimate applications for water resources management. However, several regions, especially mountainous and arid regions, suffer from limited data from a ground measurement network. Remotely sensed data may provide a viable alternative for these regions. This study aims to evaluate six high spatio-temporal resolution satellite products (GPM-F, GPM-L, GPM-E, CHIRPS, PERSIANN-CCS-CDR and PDIR-Now) in the sub-Saharan regions of Morocco during the period September 2000-August 2020. The record data from 33 rain-gauge stations was used to evaluate these products on two spatial scales (pixel and basin scales) and three temporal scales (daily, monthly and annually), adopting a quantitative and qualitative evaluation. For all examined timescales, the results showed that the GPM-F product performed the best quantitatively, while at the detection capability tested for different threshold and at daily time scale, the GPM near real-time products (GPM-E and GPM-L) were better at detecting more intense rainfall events higher than 40 mm/day. At the daily time scale, GPM-E and GPM-L and, on monthly and annual scales, CHIRPS and PERSIANN-CCS-CDR, provided satisfactory precipitation estimates. Moreover, the evaluation based on the altitudes of rain gauges revealed a bias increasing from low to high altitudes. The findings also highlight that the continental and mountainous basins showed the lowest performance compared to the other locations closer to the Atlantic Ocean. The latitude-based analysis showed a decrease of bias and increase of correlation towards the most arid zones. These results provide valuable information for a scarcely gauged and arid regions, showing that GPM-F could be a valuable alternative to rain gauges.</p>

<p>Satellite-based and Reanalysis rainfall products could be a valuable source of data for precipitation for hydrological modeling over data-scarce regions. The objective of this study is to assess the suitability of ERA5 Reanalysis and GPM IMERG V06 data (GPM-Early, GPM-Late and GPM-Final) for flood modeling over a Moroccan semi-arid watershed (Rheraya) during 2013–2018.  Both statistical scores and an event-based model were used to evaluate the performance of these products to estimate precipitation and simulate flood events. The results showed that the four products often overestimate the observed precipitation. The highest bias (124% and 145%) was obtained with GPM-E and GPM-L while the bias for GPM-F and ERA5 was much lower (31% and 42%). However, the four products showed acceptable correlations with observed data. In terms of precipitation detection capability on the hourly time scale, the GPM-E and GPM-L products presented satisfactory performance. They were the most efficient for different rainfall thresholds. In addition, by comparison with observed rainfall, flood modeling results showed that the GPM-E and GPM-L were the most efficient for flood event simulation (Nash greater than 0.4 for the majority of events and correlation coefficients greater than 0.7). This study showed that the different precipitation products tested herein have satisfactory performance for the hydrological modeling of floods. These sources of precipitation could be an alternative in ungauged or poorly gauged basins for flood simulation.</p>