Evaluation of multiple satellite precipitation products for rainfed maize production systems over Vietnam

High-resolution reliable rainfall datasets are vital for agricultural, hydrological, and weather-related applications. The accuracy of satellite estimates has a significant effect on simulation models in particular crop simulation models, which are highly sensitive to rainfall amounts, distribution,...

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Autores principales: Gummadi, Sridhar, Dinku, Tufa, Shirsath, Paresh B., Kadiyala, M.D.M.
Formato: Journal Article
Lenguaje:Inglés
Publicado: Springer 2022
Materias:
Acceso en línea:https://hdl.handle.net/10568/129172
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author Gummadi, Sridhar
Dinku, Tufa
Shirsath, Paresh B.
Kadiyala, M.D.M.
author_browse Dinku, Tufa
Gummadi, Sridhar
Kadiyala, M.D.M.
Shirsath, Paresh B.
author_facet Gummadi, Sridhar
Dinku, Tufa
Shirsath, Paresh B.
Kadiyala, M.D.M.
author_sort Gummadi, Sridhar
collection Repository of Agricultural Research Outputs (CGSpace)
description High-resolution reliable rainfall datasets are vital for agricultural, hydrological, and weather-related applications. The accuracy of satellite estimates has a significant effect on simulation models in particular crop simulation models, which are highly sensitive to rainfall amounts, distribution, and intensity. In this study, we evaluated five widely used operational satellite rainfall estimates: CHIRP, CHIRPS, CPC, CMORPH, and GSMaP. These products are evaluated by comparing with the latest improved Vietnam-gridded rainfall data to determine their suitability for use in impact assessment models. CHIRP/S products are significantly better than CMORPH, CPC, and GsMAP with higher skill, low bias, showing a high correlation coefficient with observed data, and low mean absolute error and root mean square error. The rainfall detection ability of these products shows that CHIRP outperforms the other products with a high probability of detection (POD) scores. The performance of the different rainfall datasets in simulating maize yields across Vietnam shows that VnGP and CHIRP/S were capable of producing good estimates of average maize yields with RMSE ranging from 536 kg/ha (VnGP), 715 kg/ha (CHIRPS), 737 kg/ha (CHIRP), 759 kg/ha (GsMAP), 878 kg/ha (CMORPH) to 949 kg/ha (CPC). We illustrated that there is a potential for use of satellite rainfall estimates to overcome the issues of data scarcity in regions with sparse rain gauges.
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spelling CGSpace1291722025-11-12T04:59:45Z Evaluation of multiple satellite precipitation products for rainfed maize production systems over Vietnam Gummadi, Sridhar Dinku, Tufa Shirsath, Paresh B. Kadiyala, M.D.M. rain rainfed farming data satellites High-resolution reliable rainfall datasets are vital for agricultural, hydrological, and weather-related applications. The accuracy of satellite estimates has a significant effect on simulation models in particular crop simulation models, which are highly sensitive to rainfall amounts, distribution, and intensity. In this study, we evaluated five widely used operational satellite rainfall estimates: CHIRP, CHIRPS, CPC, CMORPH, and GSMaP. These products are evaluated by comparing with the latest improved Vietnam-gridded rainfall data to determine their suitability for use in impact assessment models. CHIRP/S products are significantly better than CMORPH, CPC, and GsMAP with higher skill, low bias, showing a high correlation coefficient with observed data, and low mean absolute error and root mean square error. The rainfall detection ability of these products shows that CHIRP outperforms the other products with a high probability of detection (POD) scores. The performance of the different rainfall datasets in simulating maize yields across Vietnam shows that VnGP and CHIRP/S were capable of producing good estimates of average maize yields with RMSE ranging from 536 kg/ha (VnGP), 715 kg/ha (CHIRPS), 737 kg/ha (CHIRP), 759 kg/ha (GsMAP), 878 kg/ha (CMORPH) to 949 kg/ha (CPC). We illustrated that there is a potential for use of satellite rainfall estimates to overcome the issues of data scarcity in regions with sparse rain gauges. 2022-01-11 2023-03-03T16:12:49Z 2023-03-03T16:12:49Z Journal Article https://hdl.handle.net/10568/129172 en Open Access application/pdf Springer Gummadi, S., Dinku, T., Shirsath, P. B., & Kadiyala, M. D. M. (2022). Evaluation of multiple satellite precipitation products for rainfed maize production systems over Vietnam. Scientific Reports, 12(1). https://doi.org/10.1038/s41598-021-04380-8
spellingShingle rain
rainfed farming
data
satellites
Gummadi, Sridhar
Dinku, Tufa
Shirsath, Paresh B.
Kadiyala, M.D.M.
Evaluation of multiple satellite precipitation products for rainfed maize production systems over Vietnam
title Evaluation of multiple satellite precipitation products for rainfed maize production systems over Vietnam
title_full Evaluation of multiple satellite precipitation products for rainfed maize production systems over Vietnam
title_fullStr Evaluation of multiple satellite precipitation products for rainfed maize production systems over Vietnam
title_full_unstemmed Evaluation of multiple satellite precipitation products for rainfed maize production systems over Vietnam
title_short Evaluation of multiple satellite precipitation products for rainfed maize production systems over Vietnam
title_sort evaluation of multiple satellite precipitation products for rainfed maize production systems over vietnam
topic rain
rainfed farming
data
satellites
url https://hdl.handle.net/10568/129172
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