Assessing the influence of weather parameters on rainfall to forecast river discharge based on short-term

Assessing the influence of weather parameters on rainfall to forecast river discharge based on short-term

Rain serves as one of the key components in water cycle and it comes in the form of water droplets that are condensed from atmosphere and then fall on earth surface as rainfall. It has much importance. However, excessive rainfall can cause environmental hazards. This work developed an adaptive neuro...

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Main Authors: A. Danladi, M. Stephen, B.M. Aliyu, G.K. Gaya, N.W. Silikwa, Y. Machael
Format: Article
Language:English
Published: Elsevier 2018-06-01
Series:Alexandria Engineering Journal
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016817300959
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spelling doaj-9280514243584b04a8e9be355dc6e8ac2021-06-02T10:20:36ZengElsevierAlexandria Engineering Journal1110-01682018-06-0157211571162Assessing the influence of weather parameters on rainfall to forecast river discharge based on short-termA. Danladi0M. Stephen1B.M. Aliyu2G.K. Gaya3N.W. Silikwa4Y. Machael5Corresponding author.; Department of Pure and Applied Physics, Adamawa State University, Mubi, NigeriaDepartment of Pure and Applied Physics, Adamawa State University, Mubi, NigeriaDepartment of Pure and Applied Physics, Adamawa State University, Mubi, NigeriaDepartment of Pure and Applied Physics, Adamawa State University, Mubi, NigeriaDepartment of Pure and Applied Physics, Adamawa State University, Mubi, NigeriaDepartment of Pure and Applied Physics, Adamawa State University, Mubi, NigeriaRain serves as one of the key components in water cycle and it comes in the form of water droplets that are condensed from atmosphere and then fall on earth surface as rainfall. It has much importance. However, excessive rainfall can cause environmental hazards. This work developed an adaptive neuro – fuzzy inference system (ANFIS) to relate certain weather parameters (temperature and relative humidity) with rainfall in order to forecast the amount of rainfall capable of causing River Yazaram in Mubi town to discharge. It is predicted that, Mubi will experience high rainfall on 7th, 27th and 30th August 2016 as 56 mm, 28.8 mm and 28.8 mm respectively. Furthermore, on 7th August 2016 River Yazaram is likely to discharge. The model developed is validated with mean square percentage error (MAPE) of 4.64% and correlation coefficient of 0.1277 and 0.075 of rainfall with temperature and relative humidity respectively. Keywords: Model, Weather parameters, Forecasting and rainfallhttp://www.sciencedirect.com/science/article/pii/S1110016817300959
collection DOAJ
language English
format Article
sources DOAJ
author A. Danladi
M. Stephen
B.M. Aliyu
G.K. Gaya
N.W. Silikwa
Y. Machael
spellingShingle A. Danladi
M. Stephen
B.M. Aliyu
G.K. Gaya
N.W. Silikwa
Y. Machael
Assessing the influence of weather parameters on rainfall to forecast river discharge based on short-term
Alexandria Engineering Journal
author_facet A. Danladi
M. Stephen
B.M. Aliyu
G.K. Gaya
N.W. Silikwa
Y. Machael
author_sort A. Danladi
title Assessing the influence of weather parameters on rainfall to forecast river discharge based on short-term
title_short Assessing the influence of weather parameters on rainfall to forecast river discharge based on short-term
title_full Assessing the influence of weather parameters on rainfall to forecast river discharge based on short-term
title_fullStr Assessing the influence of weather parameters on rainfall to forecast river discharge based on short-term
title_full_unstemmed Assessing the influence of weather parameters on rainfall to forecast river discharge based on short-term
title_sort assessing the influence of weather parameters on rainfall to forecast river discharge based on short-term
publisher Elsevier
series Alexandria Engineering Journal
issn 1110-0168
publishDate 2018-06-01
description Rain serves as one of the key components in water cycle and it comes in the form of water droplets that are condensed from atmosphere and then fall on earth surface as rainfall. It has much importance. However, excessive rainfall can cause environmental hazards. This work developed an adaptive neuro – fuzzy inference system (ANFIS) to relate certain weather parameters (temperature and relative humidity) with rainfall in order to forecast the amount of rainfall capable of causing River Yazaram in Mubi town to discharge. It is predicted that, Mubi will experience high rainfall on 7th, 27th and 30th August 2016 as 56 mm, 28.8 mm and 28.8 mm respectively. Furthermore, on 7th August 2016 River Yazaram is likely to discharge. The model developed is validated with mean square percentage error (MAPE) of 4.64% and correlation coefficient of 0.1277 and 0.075 of rainfall with temperature and relative humidity respectively. Keywords: Model, Weather parameters, Forecasting and rainfall
url http://www.sciencedirect.com/science/article/pii/S1110016817300959
work_keys_str_mv AT adanladi assessingtheinfluenceofweatherparametersonrainfalltoforecastriverdischargebasedonshortterm
AT mstephen assessingtheinfluenceofweatherparametersonrainfalltoforecastriverdischargebasedonshortterm
AT bmaliyu assessingtheinfluenceofweatherparametersonrainfalltoforecastriverdischargebasedonshortterm
AT gkgaya assessingtheinfluenceofweatherparametersonrainfalltoforecastriverdischargebasedonshortterm
AT nwsilikwa assessingtheinfluenceofweatherparametersonrainfalltoforecastriverdischargebasedonshortterm
AT ymachael assessingtheinfluenceofweatherparametersonrainfalltoforecastriverdischargebasedonshortterm
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