Bias correction demonstration in two of the Indian Himalayan river basins

There is imperative need of robust basin-scale data for climate impact studies over the topographically varying and landuse heterogenous river basins in the Indian Himalayan Region (IHR). Even finer resolution regional climate models’ (RCMs) information is elusive for these purposes. Based on availa...

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Autor principal:	A. P. Dimri
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	bias correction himalayan river basin indian himalayan region precipitation temperature Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/c431f5b2e4df453099f5fb1b7aee3c55
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spelling	oai:doaj.org-article:c431f5b2e4df453099f5fb1b7aee3c552021-11-05T18:52:39ZBias correction demonstration in two of the Indian Himalayan river basins2040-22442408-935410.2166/wcc.2020.119https://doaj.org/article/c431f5b2e4df453099f5fb1b7aee3c552021-06-01T00:00:00Zhttp://jwcc.iwaponline.com/content/12/4/1297https://doaj.org/toc/2040-2244https://doaj.org/toc/2408-9354There is imperative need of robust basin-scale data for climate impact studies over the topographically varying and landuse heterogenous river basins in the Indian Himalayan Region (IHR). Even finer resolution regional climate models’ (RCMs) information is elusive for these purposes. Based on available model fields and corresponding in-situ observed fields, bias correction for precipitation over Upper Ganga River Basin (UGRB) and temperature over Satluj River Basin (SRB) is demonstrated. These chosen river basins are in central and western Himalayas, respectively. Model precipitation (temperature) field from RegCM4.7 (REMO) and corresponding observed precipitation (temperature) field from nine (eight) stations of UGRB (SRB) are considered. Empirical quantile mapping (inverse function method) method is used. It is seen that each model has a distinct systematic bias relating to both precipitation and temperature means with respect to their corresponding observed means. Applying bias correction methods to the model fields resulted in reducing these mean biases and other errors. These findings illustrate handling and improving the model fields for hydrology, glaciology studies, etc. HIGHLIGHTS Bias correction using empirical quantile mapping (inverse function method) is employed on both precipitation and temperature model.; Applying bias correction methods to the model fields resulted in reducing the mean biases and other errors.; These findings illustrate handling and improving the model fields for hydrologist, glaciologist, etc.;A. P. DimriIWA Publishingarticlebias correctionhimalayan river basinindian himalayan regionprecipitationtemperatureEnvironmental technology. Sanitary engineeringTD1-1066Environmental sciencesGE1-350ENJournal of Water and Climate Change, Vol 12, Iss 4, Pp 1297-1309 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	bias correction himalayan river basin indian himalayan region precipitation temperature Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350
spellingShingle	bias correction himalayan river basin indian himalayan region precipitation temperature Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 A. P. Dimri Bias correction demonstration in two of the Indian Himalayan river basins
description	There is imperative need of robust basin-scale data for climate impact studies over the topographically varying and landuse heterogenous river basins in the Indian Himalayan Region (IHR). Even finer resolution regional climate models’ (RCMs) information is elusive for these purposes. Based on available model fields and corresponding in-situ observed fields, bias correction for precipitation over Upper Ganga River Basin (UGRB) and temperature over Satluj River Basin (SRB) is demonstrated. These chosen river basins are in central and western Himalayas, respectively. Model precipitation (temperature) field from RegCM4.7 (REMO) and corresponding observed precipitation (temperature) field from nine (eight) stations of UGRB (SRB) are considered. Empirical quantile mapping (inverse function method) method is used. It is seen that each model has a distinct systematic bias relating to both precipitation and temperature means with respect to their corresponding observed means. Applying bias correction methods to the model fields resulted in reducing these mean biases and other errors. These findings illustrate handling and improving the model fields for hydrology, glaciology studies, etc. HIGHLIGHTS Bias correction using empirical quantile mapping (inverse function method) is employed on both precipitation and temperature model.; Applying bias correction methods to the model fields resulted in reducing the mean biases and other errors.; These findings illustrate handling and improving the model fields for hydrologist, glaciologist, etc.;
format	article
author	A. P. Dimri
author_facet	A. P. Dimri
author_sort	A. P. Dimri
title	Bias correction demonstration in two of the Indian Himalayan river basins
title_short	Bias correction demonstration in two of the Indian Himalayan river basins
title_full	Bias correction demonstration in two of the Indian Himalayan river basins
title_fullStr	Bias correction demonstration in two of the Indian Himalayan river basins
title_full_unstemmed	Bias correction demonstration in two of the Indian Himalayan river basins
title_sort	bias correction demonstration in two of the indian himalayan river basins
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/c431f5b2e4df453099f5fb1b7aee3c55
work_keys_str_mv	AT apdimri biascorrectiondemonstrationintwooftheindianhimalayanriverbasins
_version_	1718444124388982784

Bias correction demonstration in two of the Indian Himalayan river basins

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