Assessment of satellite precipitation products at different time scales over a cyclone prone coastal river basin in India
Abstract Precipitation is a fundamental input for many hydrological and water management studies. With the advancement in science, a variety of satellite precipitation products are available. In this study, the ability of three satellite precipitation products (TRMM-3B42v7, PERSIANN-CDR and GPM-IMER...
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Published in | Journal of water and climate change Vol. 14; no. 1; pp. 38 - 65 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
London
IWA Publishing
01.01.2023
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Subjects | |
Online Access | Get full text |
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Summary: | Abstract
Precipitation is a fundamental input for many hydrological and water management studies. With the advancement in science, a variety of satellite precipitation products are available. In this study, the ability of three satellite precipitation products (TRMM-3B42v7, PERSIANN-CDR and GPM-IMERGv6) to capture rainfall were evaluated with ground-based Indian Meteorological Department (IMD) gridded data and also by driving the Soil Water Assessment Tool (SWAT) hydrological model for a cyclone prone coastal river basin in the southeast of India. Results indicate that among the three, GPM-IMERG v6 outperformed in all the statistical metrics, followed by TRMM-3B42 v7 at different temporal scales. GPM-IMERG v6 exhibited the highest correlation coefficient (0.48) and lowest root mean square error (9.52 mm/day), followed by TRMM-3B42 v7 (CC = 0.44, RMSE = 9.58 mm/day) at daily scale. In contrast to other studies in similar regions, IMERGV6 showed better performance than the PERSIANN CDR in detection skills of low, medium and high intensity rainfall events as well as False Alarm Ratio. Hydrological evaluation of the three products using the SWAT model over the study area showed satisfactory results at daily and monthly scale during the calibration and validation period. IMERGV6 is found to have better performance in hydrological evaluation as well. |
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ISSN: | 2040-2244 2408-9354 |
DOI: | 10.2166/wcc.2022.166 |