Assessment of three satellite precipitation products for hydrological studies in a data-scarce context: Ouarzazate basin, southern Morocco

Arid and semi-arid regions, such as southern Morocco, face challenges due to limited precipitation data availability, posing significant obstacles for climate and hydrological studies. To bridge this data gap, this study directly evaluates the reliability of Satellite Precipitation Products (SPPs) from the latest version (V06) of the 3-hourly Integrated Multi-satellite Retrievals (3IMERG-V06) for Global Precipitation Measurement (GPM), The Tropical Rainfall Measuring Mission (TRMM-3B42-V7), and Climate Hazards Group Infrared Rainfall Station (CHIRPSV2.0). The assessment involves comparing ground-based measurements in the Ouarzazate basin to estimate precipitation characteristics. Additionally, SPPs are indirectly evaluated for their ability to simulate runoff using two hydrological models (GR4J and HEC-HMS). The analysis employs the point-to-pixel method, and various performance criteria, including R 2 , NSE, PBIAS, RMSE, and Distance between Simulation and Observation Indices (DISO), are utilized for result comparison. Findings indicate that all three products struggle to accurately replicate daily precipitation amounts, with R 2 values ​< ​0.5 and positive PBIAS values suggesting precipitation overestimation. However, when evaluating hydrological performance, the HEC-HMS model correctly simulates the observed flow when using ground-based data, with NSE (R 2 ) values of 0.76 (0.63) during the validation phase. In contrast, the GR4J model performs poorly, with NSE (R 2 ) values of 0.30 (0.45). When the three SPPs forced both models, HEC-HMS acceptably simulates flows using TRMM data, with NSE (R 2 ) values of 0.57 (0.56) during the calibration phase and 0.63 (0.67) during the validation phase, along with positive PBIAS values below 15.30%. Additionally, flow irregularities and outliers affect simulation results in continuous mode, which can lead to biased estimates. However, the hydrological evaluation method is considered a complementary approach to assess the performance of SPPs, particularly in arid regions where data is scarce.

Authors

Institutions

Publication Details

Journal
Natural Hazards Research
Published
2025-02-28
DOI
https://doi.org/10.1016/j.nhres.2025.02.008
Citations
17
Primary Topic
Precipitation Measurement and Analysis
Type
article
Field-Weighted Citation Impact
22.11
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessment of three satellite precipitation products for hydrological studies in a data-scarce context: Ouarzazate basin, southern Morocco

Ismail Hilal, Ismail Bouizrou, Aqil Tariq, Khalid En-Nagre et al.
17 citations
Natural Hazards Research
Precipitation Measurement and Analysis
22.11
article

Assessment of three satellite precipitation products for hydrological studies in a data-scarce context: Ouarzazate basin, southern Morocco

Ismail Hilal, Ismail Bouizrou, Aqil Tariq, Khalid En-Nagre, Mourad Aqnouy, Jamal Eddine Stitou El Messari, Abdelmounim Bouadila, Morad Chahid, Chaimaa Et-Takaouym
article en
17 citations

Abstract

Arid and semi-arid regions, such as southern Morocco, face challenges due to limited precipitation data availability, posing significant obstacles for climate and hydrological studies. To bridge this data gap, this study directly evaluates the reliability of Satellite Precipitation Products (SPPs) from the latest version (V06) of the 3-hourly Integrated Multi-satellite Retrievals (3IMERG-V06) for Global Precipitation Measurement (GPM), The Tropical Rainfall Measuring Mission (TRMM-3B42-V7), and Climate Hazards Group Infrared Rainfall Station (CHIRPSV2.0). The assessment involves comparing ground-based measurements in the Ouarzazate basin to estimate precipitation characteristics. Additionally, SPPs are indirectly evaluated for their ability to simulate runoff using two hydrological models (GR4J and HEC-HMS). The analysis employs the point-to-pixel method, and various performance criteria, including R 2 , NSE, PBIAS, RMSE, and Distance between Simulation and Observation Indices (DISO), are utilized for result comparison. Findings indicate that all three products struggle to accurately replicate daily precipitation amounts, with R 2 values ​< ​0.5 and positive PBIAS values suggesting precipitation overestimation. However, when evaluating hydrological performance, the HEC-HMS model correctly simulates the observed flow when using ground-based data, with NSE (R 2 ) values of 0.76 (0.63) during the validation phase. In contrast, the GR4J model performs poorly, with NSE (R 2 ) values of 0.30 (0.45). When the three SPPs forced both models, HEC-HMS acceptably simulates flows using TRMM data, with NSE (R 2 ) values of 0.57 (0.56) during the calibration phase and 0.63 (0.67) during the validation phase, along with positive PBIAS values below 15.30%. Additionally, flow irregularities and outliers affect simulation results in continuous mode, which can lead to biased estimates. However, the hydrological evaluation method is considered a complementary approach to assess the performance of SPPs, particularly in arid regions where data is scarce.

Natural Hazards ResearchVol. 5(4)
Abdelmalek Essaâdi University (MA), National Centre for Nuclear Energy, Science and Technology (MA), University of Florence (IT), Instituto Superior da Maia (PT), Sidi Mohamed Ben Abdellah University (MA), Mississippi State University (US)
Openalex Percentile: Top 0%
Precipitation Measurement and Analysis
22.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.