Scholarlink

<p>Accurate precipitation data are essential for hydrological modeling, yet ground-based observations remain scarce and often unreliable in arid and semi-arid regions. This study evaluates four widely used precipitation datasets (CHIRPS, GPM IMERG, PERSIANN-CDR, and ERA5) over the upstream Ziz-Rheris basins in southeastern Morocco. Their performance was assessed using both statistical indicators and hydrological modeling with the GR4J (daily) and GR2M (monthly) models. The results show clear differences in dataset performance across temporal scales. At the daily scale, ERA5 provides the most reliable streamflow simulations, demonstrating its ability to capture rainfall variability and hydrological responses in complex mountainous environments. GPM IMERG shows moderate but consistent performance. In contrast, CHIRPS and PERSIANN-CDR exhibit larger biases and lower accuracy. At the monthly scale, overall performance improves significantly. GPM IMERG outperforms the other datasets, providing the most accurate representation of hydrological dynamics, while ERA5 remains stable and reliable. These findings highlight the importance of selecting appropriate precipitation datasets according to the temporal scale of application. ERA5 is recommended for daily hydrological modeling, whereas GPM IMERG is better suited for monthly simulations. This study provides practical insights for improving water resources management in semi-arid, data-scarce mountainous regions.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Performance of satellite and reanalysis precipitation datasets in hydrological modeling of the Ziz-Rheris basins in southeastern Morocco

  • 期刊论文

  • 发表日期：

    2026年6月30日

查看全文
  • Zouhir Dichane,
  • Morad Chahid,
  • Brahim Meskour,
  • Safae Zahid,
  • Abdelhadi El Ouali,
  • Mohamed Sadiki,
  • Anas El Ouali

摘要

Accurate precipitation data are essential for hydrological modeling, yet ground-based observations remain scarce and often unreliable in arid and semi-arid regions. This study evaluates four widely used precipitation datasets (CHIRPS, GPM IMERG, PERSIANN-CDR, and ERA5) over the upstream Ziz-Rheris basins in southeastern Morocco. Their performance was assessed using both statistical indicators and hydrological modeling with the GR4J (daily) and GR2M (monthly) models. The results show clear differences in dataset performance across temporal scales. At the daily scale, ERA5 provides the most reliable streamflow simulations, demonstrating its ability to capture rainfall variability and hydrological responses in complex mountainous environments. GPM IMERG shows moderate but consistent performance. In contrast, CHIRPS and PERSIANN-CDR exhibit larger biases and lower accuracy. At the monthly scale, overall performance improves significantly. GPM IMERG outperforms the other datasets, providing the most accurate representation of hydrological dynamics, while ERA5 remains stable and reliable. These findings highlight the importance of selecting appropriate precipitation datasets according to the temporal scale of application. ERA5 is recommended for daily hydrological modeling, whereas GPM IMERG is better suited for monthly simulations. This study provides practical insights for improving water resources management in semi-arid, data-scarce mountainous regions.