Evaluating CHIRPS Satellite-Based Rainfall Data for Hydrologic Modeling and Climate Impact Assessment in the Abra River Basin, Philippines
Nathaniel R. Alibuyog(1), Shivherly Benedict Feland T. Dolores(2), and Rodel T. Utrera(1)

(1)Coastal Engineering Research and Management Center, Mariano Marcos State University, nralibuyog[at]mmsu.edu.ph
(2)College of Computing and Information Sciences, Mariano Marcos State University, stdolores[at]mmsu.edu.ph
(3)Research Directorate, Mariano Marcos State University, rtutrera[at]mmsu.edu.ph


Abstract

Reliable rainfall data are essential for hydrologic modeling and water resource planning, particularly in data-scarce and topographically complex regions like the Abra River Basin (ARB) in Northern Luzon, Philippines. This study evaluates the performance of CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), a satellite-based rainfall product, against ground-observed data from the PAGASA Vigan station for the period 1990-2020. Comparative statistical analysis revealed that CHIRPS captured higher mean annual rainfall (2,571.8 mm) with lower variability (CV = 14.53%) than PAGASA (2,190.4 mm- CV = 22.23%). CHIRPS also demonstrated improved spatial representation, particularly in higher elevation areas of the basin and across climatic transitions, as reflected in a lower seasonality index (0.76 vs. 0.99).
Hydrologic simulations using the Soil and Water Assessment Tool (SWAT) showed that CHIRPS-based inputs produced more consistent baseflow and total water yield estimates, validating its reliability for modeling ungauged basins. Furthermore, future climate scenarios (SSP5-8.5 for 2050 and 2070) based on CHIRPS input projected increases in rainfall (up to 15%), surface runoff (42%), groundwater recharge (9%), and total water yield (18%), alongside elevated evapotranspiration rates due to warming temperatures.
These results emphasize the utility of CHIRPS as a robust alternative to sparse ground observations for hydrologic modeling, climate change impact assessments, and sustainable water resource management. The study highlights how remote sensing technologies contribute to SDG 6 (Clean Water and Sanitation) and SDG 13 (Climate Action) through data-driven planning in vulnerable watersheds.

Keywords: Satellite-based rainfall estimation, Abra River Basin, Remote sensing for water resources, Sustainable Development Goals (SDGs), CHIRPS precipitation data

Topic: Topic E: Sustainable Development Goals

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