Impact of climate change on hydro-climatological parameters in North Cyprus: application of artificial intelligence-based statistical downscaling models

There are many environmental challenges in water-limited places in the 21st century, particularly in dry and semi-arid regions, due to the threat of climate change caused by the greenhouse effect. This study intends to explore and assess the influence of climate change on hydro-climatological parame...

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Autores principales:	Gozen Elkiran, Vahid Nourani, Ogodor Elvis, Jazuli Abdullahi
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	global circulation models precipitation predictors statistical downscaling temperature Information technology T58.5-58.64 Environmental technology. Sanitary engineering TD1-1066
Acceso en línea:	https://doaj.org/article/4949481e1e744a4bb9414423294cb4b5
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spelling	oai:doaj.org-article:4949481e1e744a4bb9414423294cb4b52021-11-23T18:48:57ZImpact of climate change on hydro-climatological parameters in North Cyprus: application of artificial intelligence-based statistical downscaling models1464-71411465-173410.2166/hydro.2021.091https://doaj.org/article/4949481e1e744a4bb9414423294cb4b52021-11-01T00:00:00Zhttp://jh.iwaponline.com/content/23/6/1395https://doaj.org/toc/1464-7141https://doaj.org/toc/1465-1734There are many environmental challenges in water-limited places in the 21st century, particularly in dry and semi-arid regions, due to the threat of climate change caused by the greenhouse effect. This study intends to explore and assess the influence of climate change on hydro-climatological parameters using statistical downscaling and future forecasts of mean monthly precipitation and temperature throughout Famagusta (Mağusa), Nicosia (Lefkoşa), and Kyrenia (Girne) stations, North Cyprus. To achieve the study's goal, 13 predictors of BNU-ESM GCMs from CMIP5 were used at a grid point in the Karfas region. To find the primary predictors, GCM data were screened using mutual information (MI) and correlation coefficient (CC) feature extraction methods prior to downscaling modeling. A neural network (ANN), an adaptive neuro fuzzy inference system (ANFIS), and multiple linear regression (MLR) models were employed as the downscaling models. We used the best downscaling model as a benchmark for future precipitation and temperature estimates for the period 2018–2040 under the RCP4.5 scenario. In the future, Famagusta and Nicosia would have up to 22% less rain, and Famagusta and Kyrenia will have 2.9% greater heat. The findings of this research could be useful in decision-making, as well as water resource management and climate change. HIGHLIGHTS The paper use the downscaling modeling for parameter evaluation.; It reveals the temperature and rainfall variation for future prediction, 2045.; It analyses the effective parameter/s used for present and future evaluation.; It is a good reference source for researchers dealing with the topic.;Gozen ElkiranVahid NouraniOgodor ElvisJazuli AbdullahiIWA Publishingarticleglobal circulation modelsprecipitationpredictorsstatistical downscalingtemperatureInformation technologyT58.5-58.64Environmental technology. Sanitary engineeringTD1-1066ENJournal of Hydroinformatics, Vol 23, Iss 6, Pp 1395-1415 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	global circulation models precipitation predictors statistical downscaling temperature Information technology T58.5-58.64 Environmental technology. Sanitary engineering TD1-1066
spellingShingle	global circulation models precipitation predictors statistical downscaling temperature Information technology T58.5-58.64 Environmental technology. Sanitary engineering TD1-1066 Gozen Elkiran Vahid Nourani Ogodor Elvis Jazuli Abdullahi Impact of climate change on hydro-climatological parameters in North Cyprus: application of artificial intelligence-based statistical downscaling models
description	There are many environmental challenges in water-limited places in the 21st century, particularly in dry and semi-arid regions, due to the threat of climate change caused by the greenhouse effect. This study intends to explore and assess the influence of climate change on hydro-climatological parameters using statistical downscaling and future forecasts of mean monthly precipitation and temperature throughout Famagusta (Mağusa), Nicosia (Lefkoşa), and Kyrenia (Girne) stations, North Cyprus. To achieve the study's goal, 13 predictors of BNU-ESM GCMs from CMIP5 were used at a grid point in the Karfas region. To find the primary predictors, GCM data were screened using mutual information (MI) and correlation coefficient (CC) feature extraction methods prior to downscaling modeling. A neural network (ANN), an adaptive neuro fuzzy inference system (ANFIS), and multiple linear regression (MLR) models were employed as the downscaling models. We used the best downscaling model as a benchmark for future precipitation and temperature estimates for the period 2018–2040 under the RCP4.5 scenario. In the future, Famagusta and Nicosia would have up to 22% less rain, and Famagusta and Kyrenia will have 2.9% greater heat. The findings of this research could be useful in decision-making, as well as water resource management and climate change. HIGHLIGHTS The paper use the downscaling modeling for parameter evaluation.; It reveals the temperature and rainfall variation for future prediction, 2045.; It analyses the effective parameter/s used for present and future evaluation.; It is a good reference source for researchers dealing with the topic.;
format	article
author	Gozen Elkiran Vahid Nourani Ogodor Elvis Jazuli Abdullahi
author_facet	Gozen Elkiran Vahid Nourani Ogodor Elvis Jazuli Abdullahi
author_sort	Gozen Elkiran
title	Impact of climate change on hydro-climatological parameters in North Cyprus: application of artificial intelligence-based statistical downscaling models
title_short	Impact of climate change on hydro-climatological parameters in North Cyprus: application of artificial intelligence-based statistical downscaling models
title_full	Impact of climate change on hydro-climatological parameters in North Cyprus: application of artificial intelligence-based statistical downscaling models
title_fullStr	Impact of climate change on hydro-climatological parameters in North Cyprus: application of artificial intelligence-based statistical downscaling models
title_full_unstemmed	Impact of climate change on hydro-climatological parameters in North Cyprus: application of artificial intelligence-based statistical downscaling models
title_sort	impact of climate change on hydro-climatological parameters in north cyprus: application of artificial intelligence-based statistical downscaling models
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/4949481e1e744a4bb9414423294cb4b5
work_keys_str_mv	AT gozenelkiran impactofclimatechangeonhydroclimatologicalparametersinnorthcyprusapplicationofartificialintelligencebasedstatisticaldownscalingmodels AT vahidnourani impactofclimatechangeonhydroclimatologicalparametersinnorthcyprusapplicationofartificialintelligencebasedstatisticaldownscalingmodels AT ogodorelvis impactofclimatechangeonhydroclimatologicalparametersinnorthcyprusapplicationofartificialintelligencebasedstatisticaldownscalingmodels AT jazuliabdullahi impactofclimatechangeonhydroclimatologicalparametersinnorthcyprusapplicationofartificialintelligencebasedstatisticaldownscalingmodels
_version_	1718416152133107712

Impact of climate change on hydro-climatological parameters in North Cyprus: application of artificial intelligence-based statistical downscaling models

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