Multifunctional retention pond for stormwater management: A decision-support model using Analytical Network Process (ANP) and Global Sensitivity Analysis (GSA)

The ever-growing impervious and contaminated surfaces in urban areas result in severe floods, degraded waterways, and stormwater. Water-sensitive strategies and water-sensitive urban design and planning can manage stormwaters through multifunctional retention ponds; however, urban professionals seek...

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Autores principales:	Ali Keyvanfar, Arezou Shafaghat, Nurhaizah Ismail, Sapura Mohamad, Hamidah Ahmad
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Multifunctional retention pond Water-sensitive urban design and planning Stormwater management Decision-support model Analytical Network Process (ANP) Global Sensitivity Analysis (GSA) Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/0b1921b2d5b64e90b2f806e25cdfe78b
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spelling	oai:doaj.org-article:0b1921b2d5b64e90b2f806e25cdfe78b2021-12-01T04:42:25ZMultifunctional retention pond for stormwater management: A decision-support model using Analytical Network Process (ANP) and Global Sensitivity Analysis (GSA)1470-160X10.1016/j.ecolind.2020.107317https://doaj.org/article/0b1921b2d5b64e90b2f806e25cdfe78b2021-05-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X20312590https://doaj.org/toc/1470-160XThe ever-growing impervious and contaminated surfaces in urban areas result in severe floods, degraded waterways, and stormwater. Water-sensitive strategies and water-sensitive urban design and planning can manage stormwaters through multifunctional retention ponds; however, urban professionals seek an assessment model that evaluates and quantifies the performance of multifunctional retention ponds on stormwater management. This research has developed the Urban Retention Pond Index (URPI) assessment model, a universal multi-layered decision-support tool that constitutes three criteria (C1. Geotechnical functions, C2. Water quality and treatment, and C3. Structural and physical landscaping functions), and twenty sub-criteria. Employing Analytical Network Process (ANP) has determined the weights of indicators, which formulated the URPI index. The ANP result indicated soil investigation (WC1.1 = 0.170), soil retention (WC2.1 = 0.156), and infiltration rate (WC1.2 = 0.108) could extensively impact to the performance of multifunctional retention ponds. To validate the model, it was implemented in the Boneyard Creek retention pond using the Weighted Sum Method. The assessment analysis assigned grade A to this site, meaning, Boneyard Creek pond manages stormwater mainly through Soils Investigation (WC1.1 = 0.150), Soil retention (WC2.1 = 0.144), and Infiltration Rate (WC1.2 = 0.091). Furthermore, Global Sensitivity Analysis (GSA) was conducted to analyze the URPI model’s input–output uncertainty and effect of variations, through a series of methods; Cumulative Distribution Functions (CDF), Probability Density Function (PDF), Scatterplot-Histogram Plot, Box-Whisker Plot, and Parallel Coordination. GSA could support the dominant controls and robust decision-making of the URPI model. GSA results determined that model outputs are empirically distributed with minor regression variance to the theoretical distribution. Most of the outputs fall within the intervals where the mean and median are more significant than the mode. The multiple regression analysis has shown that the three criteria are positively and linearly correlated. The Box-Whisker plots revealed the behaviors of the four mentioned measures are similar. Notably, the Box-Whisker standard error plots indicated the minor errors of the outputs in the whole network of the URPI model. Meanwhile, the Parallel Coordination indicated the largest centrality degrees by the spillway and landscape habitat retention sub-criteria and the largest Eigenvector centralities by soil retention and soil investigation sub-criteria in the whole network.Ali KeyvanfarArezou ShafaghatNurhaizah IsmailSapura MohamadHamidah AhmadElsevierarticleMultifunctional retention pondWater-sensitive urban design and planningStormwater managementDecision-support modelAnalytical Network Process (ANP)Global Sensitivity Analysis (GSA)EcologyQH540-549.5ENEcological Indicators, Vol 124, Iss , Pp 107317- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Multifunctional retention pond Water-sensitive urban design and planning Stormwater management Decision-support model Analytical Network Process (ANP) Global Sensitivity Analysis (GSA) Ecology QH540-549.5
spellingShingle	Multifunctional retention pond Water-sensitive urban design and planning Stormwater management Decision-support model Analytical Network Process (ANP) Global Sensitivity Analysis (GSA) Ecology QH540-549.5 Ali Keyvanfar Arezou Shafaghat Nurhaizah Ismail Sapura Mohamad Hamidah Ahmad Multifunctional retention pond for stormwater management: A decision-support model using Analytical Network Process (ANP) and Global Sensitivity Analysis (GSA)
description	The ever-growing impervious and contaminated surfaces in urban areas result in severe floods, degraded waterways, and stormwater. Water-sensitive strategies and water-sensitive urban design and planning can manage stormwaters through multifunctional retention ponds; however, urban professionals seek an assessment model that evaluates and quantifies the performance of multifunctional retention ponds on stormwater management. This research has developed the Urban Retention Pond Index (URPI) assessment model, a universal multi-layered decision-support tool that constitutes three criteria (C1. Geotechnical functions, C2. Water quality and treatment, and C3. Structural and physical landscaping functions), and twenty sub-criteria. Employing Analytical Network Process (ANP) has determined the weights of indicators, which formulated the URPI index. The ANP result indicated soil investigation (WC1.1 = 0.170), soil retention (WC2.1 = 0.156), and infiltration rate (WC1.2 = 0.108) could extensively impact to the performance of multifunctional retention ponds. To validate the model, it was implemented in the Boneyard Creek retention pond using the Weighted Sum Method. The assessment analysis assigned grade A to this site, meaning, Boneyard Creek pond manages stormwater mainly through Soils Investigation (WC1.1 = 0.150), Soil retention (WC2.1 = 0.144), and Infiltration Rate (WC1.2 = 0.091). Furthermore, Global Sensitivity Analysis (GSA) was conducted to analyze the URPI model’s input–output uncertainty and effect of variations, through a series of methods; Cumulative Distribution Functions (CDF), Probability Density Function (PDF), Scatterplot-Histogram Plot, Box-Whisker Plot, and Parallel Coordination. GSA could support the dominant controls and robust decision-making of the URPI model. GSA results determined that model outputs are empirically distributed with minor regression variance to the theoretical distribution. Most of the outputs fall within the intervals where the mean and median are more significant than the mode. The multiple regression analysis has shown that the three criteria are positively and linearly correlated. The Box-Whisker plots revealed the behaviors of the four mentioned measures are similar. Notably, the Box-Whisker standard error plots indicated the minor errors of the outputs in the whole network of the URPI model. Meanwhile, the Parallel Coordination indicated the largest centrality degrees by the spillway and landscape habitat retention sub-criteria and the largest Eigenvector centralities by soil retention and soil investigation sub-criteria in the whole network.
format	article
author	Ali Keyvanfar Arezou Shafaghat Nurhaizah Ismail Sapura Mohamad Hamidah Ahmad
author_facet	Ali Keyvanfar Arezou Shafaghat Nurhaizah Ismail Sapura Mohamad Hamidah Ahmad
author_sort	Ali Keyvanfar
title	Multifunctional retention pond for stormwater management: A decision-support model using Analytical Network Process (ANP) and Global Sensitivity Analysis (GSA)
title_short	Multifunctional retention pond for stormwater management: A decision-support model using Analytical Network Process (ANP) and Global Sensitivity Analysis (GSA)
title_full	Multifunctional retention pond for stormwater management: A decision-support model using Analytical Network Process (ANP) and Global Sensitivity Analysis (GSA)
title_fullStr	Multifunctional retention pond for stormwater management: A decision-support model using Analytical Network Process (ANP) and Global Sensitivity Analysis (GSA)
title_full_unstemmed	Multifunctional retention pond for stormwater management: A decision-support model using Analytical Network Process (ANP) and Global Sensitivity Analysis (GSA)
title_sort	multifunctional retention pond for stormwater management: a decision-support model using analytical network process (anp) and global sensitivity analysis (gsa)
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/0b1921b2d5b64e90b2f806e25cdfe78b
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_version_	1718405802357686272

Multifunctional retention pond for stormwater management: A decision-support model using Analytical Network Process (ANP) and Global Sensitivity Analysis (GSA)

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