Gharnouki I. auteur aut IRD Aouissi J. auteur aut IRD Benabdallah S. auteur aut IRD Tramblay Yves auteur aut IRD text journalArticle eng text/pdf born digital access Precipitation is a key component in hydrologic processes. It plays an important role in hydrological modeling and water resource management. However, many regions suffer from limited and data scarcity due to the lack of ground-based rain gauge networks. The main objective of this study is to evaluate other source of rainfall data such as remote sensing data (three different satellite-based precipitation products (CHIRPS, PERSIANN, and GPM) and a reanalysis (ERA5) against ground-based data, which could provide complementary rainfall information in semiarid catchment of Tunisia (Haffouz catchment), for the period between September 2000 and August 2018. These remotely sensed-data are compared for the first time with observations in a semiarid catchment in Tunisia.Twelve rain gauges and two different interpolation methods (inverse distance weight and ordinary kriging) were used to compute a set of interpolated precipitation reference fields. The evaluation was performed at daily, monthly, and yearly time scales and at different spatial scales, using several statistical metrics. The results showed that the two interpolation methods give similar precipitation estimates at the catchment scale. According to the different statistical metrics, CHIRPS showed the most satisfactory results followed by PERSIANN which performed well in terms of correlation but overestimated precipitations spatially over the catchment. GPM underestimates the precipitation considerably, but it gives a satisfactory performance temporally. ERA5 shows a very good performance at daily, monthly, and yearly timescale, but it is unable to represent the spatial variability distribution of precipitation for this catchment. This study concluded that satellite-based precipitation products or reanalysis data can be useful in semiarid regions and data-scarce catchments, and it may provide less costly alternatives for data-poor regions. specialized Precipitation Satellite-based precipitation products Spatial interpolation Tunisia TUNISIE 062 126 [Early acces] [17 p.] 2024 1895-6572 https://www.documentation.ird.fr/hor/fdi:010089577 10.1007/s11600-024-01293-8 1895-6572 [F B010089577] https://www.documentation.ird.fr/hor/fdi:010089577 https://www.documentation.ird.fr/intranet/publi/2024-04/010089577.pdf Accès réservé (Intranet de l'IRD) IRD - Base Horizon / Pleins textes 2024-04-05 2025-11-06 fdi:010089577 fre