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Geostatistical Estimation of Daily Monsoon Precipitation at Fine Spatial Scale: Koshi River Basin
AbstractThe use of appropriate space and time scales is fundamental to model the water budget in mountainous regions and to give appropriate replies to the initial requests. However, at a daily scale, the determination of precipitation behavior is not an easy task due to its high variability in moun...
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Published in: | Journal of hydrologic engineering 2016-09, Vol.21 (9) |
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creator | Gonga-Saholiariliva, Nahossio Neppel, Luc Chevallier, Pierre Delclaux, François Savéan, Marie |
description | AbstractThe use of appropriate space and time scales is fundamental to model the water budget in mountainous regions and to give appropriate replies to the initial requests. However, at a daily scale, the determination of precipitation behavior is not an easy task due to its high variability in mountainous areas. Seven years (2001–2008) of accurate precipitation maps (1 km ground resolution) have been produced for the monsoon season over the Koshi River basin (Nepal) to be used for hydrological modeling. Due to field and topographical constraints, the geostatistical method of ordinary cokriging interpolation (OCK) was used to compute precipitation grids over a 57,800 km2 basin with a rain gauge network made of 47 stations. Using elevation as a covariable, regionalization models were run to produce 976 daily precipitation grids. They describe temporal and spatial variability close to observed data. Comparisons of the OCK results to an Aphrodite’s reference grid (resolution of 25 km) show that the OCK grids are characterized by a higher spatial variability. Both OCK and Aphrodite data sets underestimate observations, with OCK grids showing the best fit to observed data. However, the OCK method, with an eventual adaptation of the cokriging model, appears consistent for situations where the resolution of the precipitation’s spatial distribution is insufficient and an alternate explaining variable such as elevation is available. |
doi_str_mv | 10.1061/(ASCE)HE.1943-5584.0001388 |
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However, at a daily scale, the determination of precipitation behavior is not an easy task due to its high variability in mountainous areas. Seven years (2001–2008) of accurate precipitation maps (1 km ground resolution) have been produced for the monsoon season over the Koshi River basin (Nepal) to be used for hydrological modeling. Due to field and topographical constraints, the geostatistical method of ordinary cokriging interpolation (OCK) was used to compute precipitation grids over a 57,800 km2 basin with a rain gauge network made of 47 stations. Using elevation as a covariable, regionalization models were run to produce 976 daily precipitation grids. They describe temporal and spatial variability close to observed data. Comparisons of the OCK results to an Aphrodite’s reference grid (resolution of 25 km) show that the OCK grids are characterized by a higher spatial variability. Both OCK and Aphrodite data sets underestimate observations, with OCK grids showing the best fit to observed data. 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Both OCK and Aphrodite data sets underestimate observations, with OCK grids showing the best fit to observed data. 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However, at a daily scale, the determination of precipitation behavior is not an easy task due to its high variability in mountainous areas. Seven years (2001–2008) of accurate precipitation maps (1 km ground resolution) have been produced for the monsoon season over the Koshi River basin (Nepal) to be used for hydrological modeling. Due to field and topographical constraints, the geostatistical method of ordinary cokriging interpolation (OCK) was used to compute precipitation grids over a 57,800 km2 basin with a rain gauge network made of 47 stations. Using elevation as a covariable, regionalization models were run to produce 976 daily precipitation grids. They describe temporal and spatial variability close to observed data. Comparisons of the OCK results to an Aphrodite’s reference grid (resolution of 25 km) show that the OCK grids are characterized by a higher spatial variability. Both OCK and Aphrodite data sets underestimate observations, with OCK grids showing the best fit to observed data. However, the OCK method, with an eventual adaptation of the cokriging model, appears consistent for situations where the resolution of the precipitation’s spatial distribution is insufficient and an alternate explaining variable such as elevation is available.</abstract><pub>American Society of Civil Engineers</pub><doi>10.1061/(ASCE)HE.1943-5584.0001388</doi><orcidid>https://orcid.org/0000-0001-7283-6614</orcidid></addata></record> |
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subjects | Case Studies Case Study Climatology Continental interfaces, environment Earth Sciences Environment and Society Environmental Engineering Environmental Sciences Glaciology Global Changes Hydrology Sciences of the Universe |
title | Geostatistical Estimation of Daily Monsoon Precipitation at Fine Spatial Scale: Koshi River Basin |
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