Performance of GPM-IMERG satellite precipitation for rainfall-runoff modeling in Indonesia

Accurate discharge predictions are essential for effective water resource management, including irrigation, drinking water supply, hydropower, reservoir management, environmental flow, and flood assessment. Satellite precipitation data, such as GPM-IMERG, offers a viable solution for estimating rive...

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Bibliographic Details
Published in:Water practice and technology 2024-10, Vol.19 (10), p.3909-3928
Main Authors: Hidayah, Entin, Saifurridzal, Saifurridzal, Wiyono, Retno Utami Agung, Widiarti, Wiwik Yunarni, Martini, Resa, Juliastuti, Juliastuti, Riduwan, Mohammad
Format: Article
Language:English
Subjects:
Accuracy
Calibration
Concentration time
Data analysis
Data processing
Drinking water
Environmental management
Flood management
Flood predictions
Floods
High flow
Hydroelectric power
Hydrologic data
Hydrologic models
Hydrology
Irrigation water
Land use
Modelling
Parameter sensitivity
Polygons
Precipitation
Rain
Rain gauges
Rainfall
Rainfall distribution
Rainfall-runoff relationships
Research methodology
Reservoir management
Resource management
River discharge
River flow
Runoff
Satellites
Sensitivity analysis
Soils
Water discharge
Water resources
Water resources management
Water supply
Watersheds
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Summary:Accurate discharge predictions are essential for effective water resource management, including irrigation, drinking water supply, hydropower, reservoir management, environmental flow, and flood assessment. Satellite precipitation data, such as GPM-IMERG, offers a viable solution for estimating river discharge, especially in ungauged or sparsely gauged watersheds. This study evaluates the use of GPM-IMERG data in the HEC-HMS hydrological model to predict discharge in the Mayang Watershed, Jember Regency, Indonesia. The study employs the Arithmetic, Polygon Thiessen, and Isohyet methods to analyze rainfall distribution. Results indicate that the Polygon Thiessen method, when paired with GPM-IMERG data, provides more reliable precipitation estimates due to its consideration of rain gauge proximity. Calibration and validation confirm the superiority of GPM-IMERG data over traditional observational data, particularly under high-flow conditions. Despite some limitations in detecting low-intensity precipitation, GPM-IMERG outperforms other satellite products like TRMM in terms of accuracy. Sensitivity analysis highlights the significant influence of parameters such as curve Number and time of concentration on model outcomes. Further research should explore emerging rainfall data products to improve hydrological modeling accuracy.
ISSN:1751-231X
1751-231X
DOI:10.2166/wpt.2024.240