Adaptive hybrid architecture for enhancement of the complex hydroclimatic system and assessment of freshwater security

Future freshwater security relies on hydroclimatic (HC) shifts and regimes for sustainable development. The approximation of the HC system faces major uncertainties and complexities due to the incorporation of heavy datasets, characteristics, and constraints. The proposed study focused on the parall...

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Autores principales:	Venkatesh Budamala, Amit Baburao Mahindrakar
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	adaptive machine learning hybrid simulators hydroclimatology parallel computing spatial optimization water security Information technology T58.5-58.64 Environmental technology. Sanitary engineering TD1-1066
Acceso en línea:	https://doaj.org/article/af7b3c04573a43e99cbd181d394e2d8d
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id	oai:doaj.org-article:af7b3c04573a43e99cbd181d394e2d8d
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spelling	oai:doaj.org-article:af7b3c04573a43e99cbd181d394e2d8d2021-11-05T17:51:11ZAdaptive hybrid architecture for enhancement of the complex hydroclimatic system and assessment of freshwater security1464-71411465-173410.2166/hydro.2021.182https://doaj.org/article/af7b3c04573a43e99cbd181d394e2d8d2021-09-01T00:00:00Zhttp://jh.iwaponline.com/content/23/5/950https://doaj.org/toc/1464-7141https://doaj.org/toc/1465-1734Future freshwater security relies on hydroclimatic (HC) shifts and regimes for sustainable development. The approximation of the HC system faces major uncertainties and complexities due to the incorporation of heavy datasets, characteristics, and constraints. The proposed study focused on the parallel computing of emulator modeling-based spatial optimization to enhance the HC systems with the perspective of future freshwater security in the Upper Chattahoochee River basin (UCR). Here, the framework compiles both physical and machine learning concepts with adaptive technology for the replication of real-world scenarios. Besides, it contains 2Emulator Model Fitting, Spatial Optimization, Parallel Computing, and Initial and Adaptive sampling to upgrade model efficiency, while UCR has inadequate groundwater and the assessment of freshwater security in UCR is more necessary for varying future climatic conditions. The results displayed that the proposed spatial optimization algorithm proved to be an effective and efficient approach in the approximation of HC models. The assessment of water security in UCR was showed in terms of scarcity and vulnerability indicators for median and low-level conditions, respectively. Moreover, this study provides the potential framework for the enhancement of physical model predictions with the incorporation of hybrid concepts for problem-solving technology which can provide significant information on HC issues. HIGHLIGHTS A comprehensive framework for the integration of the physical and machine learning concepts to enhance the hydroclimatic system.; Adaptive emulator-based spatial optimization was introduced to control expensive simulations.; Parallel computing was incorporated in the framework to restrict the spatial variability in large-scale watersheds.; Assessed the future freshwater security based on the Blue/Green Water dynamics.;Venkatesh BudamalaAmit Baburao MahindrakarIWA Publishingarticleadaptive machine learninghybrid simulatorshydroclimatologyparallel computingspatial optimizationwater securityInformation technologyT58.5-58.64Environmental technology. Sanitary engineeringTD1-1066ENJournal of Hydroinformatics, Vol 23, Iss 5, Pp 950-965 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	adaptive machine learning hybrid simulators hydroclimatology parallel computing spatial optimization water security Information technology T58.5-58.64 Environmental technology. Sanitary engineering TD1-1066
spellingShingle	adaptive machine learning hybrid simulators hydroclimatology parallel computing spatial optimization water security Information technology T58.5-58.64 Environmental technology. Sanitary engineering TD1-1066 Venkatesh Budamala Amit Baburao Mahindrakar Adaptive hybrid architecture for enhancement of the complex hydroclimatic system and assessment of freshwater security
description	Future freshwater security relies on hydroclimatic (HC) shifts and regimes for sustainable development. The approximation of the HC system faces major uncertainties and complexities due to the incorporation of heavy datasets, characteristics, and constraints. The proposed study focused on the parallel computing of emulator modeling-based spatial optimization to enhance the HC systems with the perspective of future freshwater security in the Upper Chattahoochee River basin (UCR). Here, the framework compiles both physical and machine learning concepts with adaptive technology for the replication of real-world scenarios. Besides, it contains 2Emulator Model Fitting, Spatial Optimization, Parallel Computing, and Initial and Adaptive sampling to upgrade model efficiency, while UCR has inadequate groundwater and the assessment of freshwater security in UCR is more necessary for varying future climatic conditions. The results displayed that the proposed spatial optimization algorithm proved to be an effective and efficient approach in the approximation of HC models. The assessment of water security in UCR was showed in terms of scarcity and vulnerability indicators for median and low-level conditions, respectively. Moreover, this study provides the potential framework for the enhancement of physical model predictions with the incorporation of hybrid concepts for problem-solving technology which can provide significant information on HC issues. HIGHLIGHTS A comprehensive framework for the integration of the physical and machine learning concepts to enhance the hydroclimatic system.; Adaptive emulator-based spatial optimization was introduced to control expensive simulations.; Parallel computing was incorporated in the framework to restrict the spatial variability in large-scale watersheds.; Assessed the future freshwater security based on the Blue/Green Water dynamics.;
format	article
author	Venkatesh Budamala Amit Baburao Mahindrakar
author_facet	Venkatesh Budamala Amit Baburao Mahindrakar
author_sort	Venkatesh Budamala
title	Adaptive hybrid architecture for enhancement of the complex hydroclimatic system and assessment of freshwater security
title_short	Adaptive hybrid architecture for enhancement of the complex hydroclimatic system and assessment of freshwater security
title_full	Adaptive hybrid architecture for enhancement of the complex hydroclimatic system and assessment of freshwater security
title_fullStr	Adaptive hybrid architecture for enhancement of the complex hydroclimatic system and assessment of freshwater security
title_full_unstemmed	Adaptive hybrid architecture for enhancement of the complex hydroclimatic system and assessment of freshwater security
title_sort	adaptive hybrid architecture for enhancement of the complex hydroclimatic system and assessment of freshwater security
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/af7b3c04573a43e99cbd181d394e2d8d
work_keys_str_mv	AT venkateshbudamala adaptivehybridarchitectureforenhancementofthecomplexhydroclimaticsystemandassessmentoffreshwatersecurity AT amitbaburaomahindrakar adaptivehybridarchitectureforenhancementofthecomplexhydroclimaticsystemandassessmentoffreshwatersecurity
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Adaptive hybrid architecture for enhancement of the complex hydroclimatic system and assessment of freshwater security

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