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Spatial estimation of average daily precipitation using multiple linear regression by using topographic and wind speed variables in tropical climate

Complex topography and wind characteristics play important roles in rising air masses and in daily spatial distribution of the precipitations in complex region. As a result, its spatial discontinuity and behaviour in complex areas can affect the spatial distribution of precipitation. In this work, a...

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Main Authors:	Mohd Talha, Anees, Abdullah, Khiruddin, M. Nawawi, M. N., Nik Ab Rahman, Nik Norulaini, Mt. Piah, Abd. Rahni, Syakir, M.I, Ali Khan, Mohammad Muqtada, Mohd. Omar, Abdul Kadir
Format:	Indexed Article
Language:	English
Published:	2018
Online Access:	http://discol.umk.edu.my/id/eprint/7378/1/SPATIAL%20ESTIMATION%20OF%20AVERAGE%20DAILY%20PRECIPITATION%20USING.pdf http://discol.umk.edu.my/id/eprint/7378/ https://journals.vgtu.lt/index.php/JEELM/article/view/6337
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id	my.umk.eprints.7378
record_format	eprints
spelling	my.umk.eprints.73782022-05-23T15:38:47Z http://discol.umk.edu.my/id/eprint/7378/ Spatial estimation of average daily precipitation using multiple linear regression by using topographic and wind speed variables in tropical climate Mohd Talha, Anees Abdullah, Khiruddin M. Nawawi, M. N. Nik Ab Rahman, Nik Norulaini Mt. Piah, Abd. Rahni Syakir, M.I Ali Khan, Mohammad Muqtada Mohd. Omar, Abdul Kadir Complex topography and wind characteristics play important roles in rising air masses and in daily spatial distribution of the precipitations in complex region. As a result, its spatial discontinuity and behaviour in complex areas can affect the spatial distribution of precipitation. In this work, a two-fold concept was used to consider both spatial discontinuity and topographic and wind speed in average daily spatial precipitation estimation using Inverse Distance Weighting (IDW) and Multiple Linear Regression (MLR) in tropical climates. First, wet and dry days were identified by the two methods. Then the two models based on MLR (Model 1 and Model 2) were applied on wet days to estimate the precipitation using selected predictor variables. The models were applied for month wise, season wise and year wise daily averages separately during the study period. The study reveals that, Model 1 has been found to be the best in terms of categorical statistics, R2 values, bias and special distribution patterns. However, it was found that sets of different predictor variables dominates in different months, seasons and years. Furthermore, necessities of other data for further enhancement of the results were suggested. 2018 Indexed Article NonPeerReviewed text en http://discol.umk.edu.my/id/eprint/7378/1/SPATIAL%20ESTIMATION%20OF%20AVERAGE%20DAILY%20PRECIPITATION%20USING.pdf Mohd Talha, Anees and Abdullah, Khiruddin and M. Nawawi, M. N. and Nik Ab Rahman, Nik Norulaini and Mt. Piah, Abd. Rahni and Syakir, M.I and Ali Khan, Mohammad Muqtada and Mohd. Omar, Abdul Kadir (2018) Spatial estimation of average daily precipitation using multiple linear regression by using topographic and wind speed variables in tropical climate. Journal of Environmental Engineering and Landscape Management, 26 (4). pp. 299-316. ISSN 1648-6897 https://journals.vgtu.lt/index.php/JEELM/article/view/6337
institution	Universiti Malaysia Kelantan
building	Perpustakaan Universiti Malaysia Kelantan
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Kelantan
content_source	UMK Institutional Repository
url_provider	http://umkeprints.umk.edu.my/
language	English
description	Complex topography and wind characteristics play important roles in rising air masses and in daily spatial distribution of the precipitations in complex region. As a result, its spatial discontinuity and behaviour in complex areas can affect the spatial distribution of precipitation. In this work, a two-fold concept was used to consider both spatial discontinuity and topographic and wind speed in average daily spatial precipitation estimation using Inverse Distance Weighting (IDW) and Multiple Linear Regression (MLR) in tropical climates. First, wet and dry days were identified by the two methods. Then the two models based on MLR (Model 1 and Model 2) were applied on wet days to estimate the precipitation using selected predictor variables. The models were applied for month wise, season wise and year wise daily averages separately during the study period. The study reveals that, Model 1 has been found to be the best in terms of categorical statistics, R2 values, bias and special distribution patterns. However, it was found that sets of different predictor variables dominates in different months, seasons and years. Furthermore, necessities of other data for further enhancement of the results were suggested.
format	Indexed Article
author	Mohd Talha, Anees Abdullah, Khiruddin M. Nawawi, M. N. Nik Ab Rahman, Nik Norulaini Mt. Piah, Abd. Rahni Syakir, M.I Ali Khan, Mohammad Muqtada Mohd. Omar, Abdul Kadir
spellingShingle	Mohd Talha, Anees Abdullah, Khiruddin M. Nawawi, M. N. Nik Ab Rahman, Nik Norulaini Mt. Piah, Abd. Rahni Syakir, M.I Ali Khan, Mohammad Muqtada Mohd. Omar, Abdul Kadir Spatial estimation of average daily precipitation using multiple linear regression by using topographic and wind speed variables in tropical climate
author_facet	Mohd Talha, Anees Abdullah, Khiruddin M. Nawawi, M. N. Nik Ab Rahman, Nik Norulaini Mt. Piah, Abd. Rahni Syakir, M.I Ali Khan, Mohammad Muqtada Mohd. Omar, Abdul Kadir
author_sort	Mohd Talha, Anees
title	Spatial estimation of average daily precipitation using multiple linear regression by using topographic and wind speed variables in tropical climate
title_short	Spatial estimation of average daily precipitation using multiple linear regression by using topographic and wind speed variables in tropical climate
title_full	Spatial estimation of average daily precipitation using multiple linear regression by using topographic and wind speed variables in tropical climate
title_fullStr	Spatial estimation of average daily precipitation using multiple linear regression by using topographic and wind speed variables in tropical climate
title_full_unstemmed	Spatial estimation of average daily precipitation using multiple linear regression by using topographic and wind speed variables in tropical climate
title_sort	spatial estimation of average daily precipitation using multiple linear regression by using topographic and wind speed variables in tropical climate
publishDate	2018
url	http://discol.umk.edu.my/id/eprint/7378/1/SPATIAL%20ESTIMATION%20OF%20AVERAGE%20DAILY%20PRECIPITATION%20USING.pdf http://discol.umk.edu.my/id/eprint/7378/ https://journals.vgtu.lt/index.php/JEELM/article/view/6337
_version_	1763303833027477504
score	13.211869

Spatial estimation of average daily precipitation using multiple linear regression by using topographic and wind speed variables in tropical climate

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