A multi criteria analog model for assessing the vulnerability of rural catchments to road spills of hazardous substances

Bibliographic Details
Main Author: Siqueira, Hygor Evangelista [UNESP]
Publication Date: 2017
Other Authors: Tarle Pissarra, Teresa Cristina [UNESP], Valle Junior, Renato Farias do, Sanches Fernandes, Luis Filipe, Leal Pacheco, Fernando Antonio
Format: Article
Language: eng
Source: Repositório Institucional da UNESP
Download full: http://dx.doi.org/10.1016/j.eiar.2017.02.002
http://hdl.handle.net/11449/162792
Summary: Road spills of hazardous substances are common in developing countries due to increasing industrialization and traffic accidents, and represent a serious threat to soils and water in catchments. There is abundant literature on equations describing the wash-off of pollutants from roads during a storm event and there are a number of watershed models incorporating those equations in storm water quality algorithms that route runoff and pollution yields through a drainage system towards the catchment outlet. However, methods describing catchment vulnerability to contamination by road spills based solely on biophysical parameters are scarce. These methods could be particularly attractive to managers because they can operate with a limited amount of easily collectable data, while still being able to provide important insights on the areas more prone to contamination within the studied watershed. The purpose of this paper was then to contribute with a new vulnerability model. To accomplish the goal, a selection of medium properties appearing in wash-off equations and routing algorithms were assembled and processed in a parametric framework based on multi criteria analysis to define the watershed vulnerability: However, parameters had to be adapted because wash-off equations and water quality models have been developed to operate primarily in the urban environment while the vulnerability model is meant to run in rural watersheds. The selected parameters were hillside slope, ground roughness (depending on land use), soil permeability (depending on soil type), distance to water courses and stream density. The vulnerability model is a spatially distributed algorithm that was prepared to run under the IDRISI Selva software, a GIS platform capable of handling spatial and alphanumeric data and execute the necessary terrain model, hydrographic and thematic analyses. For illustrative purposes, the vulnerability model was applied to the legally protected Environmental Protection Area (APA), located in the Uberaba region, state of Minas Gerais, Brazil. In this region, the risk of accidents causing chemical spills is preoccupying because large quantities of dangerous materials are transported in two important distribution highways while the APA is fundamental for the protection of water resources, the riverine ecosystems and remnants of native vegetation. In some tested scenarios, model results show 60% of vulnerable areas within the studied area. The most sensitive parameter to vulnerability is soil type. To prevent soils from contamination, specific measures were proposed involving minimization of land use conflicts that would presumably raise the soil's organic matter and in the sequel restore the soil's structural functions. Additionally, the present study proposed the preservation and reinforcement of riparian forests as one measure to protect the quality of surface water. (C) 2017 Elsevier Inc. All rights reserved.
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spelling A multi criteria analog model for assessing the vulnerability of rural catchments to road spills of hazardous substancesRoad accidentsHazardous substancesRoad spillsMulti criteria analysisGeographic information systemsEnvironmental protection areaRoad spills of hazardous substances are common in developing countries due to increasing industrialization and traffic accidents, and represent a serious threat to soils and water in catchments. There is abundant literature on equations describing the wash-off of pollutants from roads during a storm event and there are a number of watershed models incorporating those equations in storm water quality algorithms that route runoff and pollution yields through a drainage system towards the catchment outlet. However, methods describing catchment vulnerability to contamination by road spills based solely on biophysical parameters are scarce. These methods could be particularly attractive to managers because they can operate with a limited amount of easily collectable data, while still being able to provide important insights on the areas more prone to contamination within the studied watershed. The purpose of this paper was then to contribute with a new vulnerability model. To accomplish the goal, a selection of medium properties appearing in wash-off equations and routing algorithms were assembled and processed in a parametric framework based on multi criteria analysis to define the watershed vulnerability: However, parameters had to be adapted because wash-off equations and water quality models have been developed to operate primarily in the urban environment while the vulnerability model is meant to run in rural watersheds. The selected parameters were hillside slope, ground roughness (depending on land use), soil permeability (depending on soil type), distance to water courses and stream density. The vulnerability model is a spatially distributed algorithm that was prepared to run under the IDRISI Selva software, a GIS platform capable of handling spatial and alphanumeric data and execute the necessary terrain model, hydrographic and thematic analyses. For illustrative purposes, the vulnerability model was applied to the legally protected Environmental Protection Area (APA), located in the Uberaba region, state of Minas Gerais, Brazil. In this region, the risk of accidents causing chemical spills is preoccupying because large quantities of dangerous materials are transported in two important distribution highways while the APA is fundamental for the protection of water resources, the riverine ecosystems and remnants of native vegetation. In some tested scenarios, model results show 60% of vulnerable areas within the studied area. The most sensitive parameter to vulnerability is soil type. To prevent soils from contamination, specific measures were proposed involving minimization of land use conflicts that would presumably raise the soil's organic matter and in the sequel restore the soil's structural functions. Additionally, the present study proposed the preservation and reinforcement of riparian forests as one measure to protect the quality of surface water. (C) 2017 Elsevier Inc. All rights reserved.FEDER/COMPETE/POCI - Operational Competitiveness Internationalization ProgrammeNational Funds of FCT-Portuguese Foundation for Science and TechnologyUniv Estadual Paulista, Fac Ciencias Agr & Vet, Dept Engn Rural, Jaboticabal, BrazilInst Fed Triangulo Mineiro, Lab Geoprocessamento, Campus Uberaba, Uberaba, BrazilUniv Tras Os Montes & Alto Douro, Ctr Invest & Tecnol Agroambientais & Biol, Ap 1013, P-5001801 Vila Real, PortugalUniv Tras Os Montes & Alto Douro, Ctr Quim Vila Real, Ap 1013, P-5001821 Vila Real, PortugalUniv Estadual Paulista, Fac Ciencias Agr & Vet, Dept Engn Rural, Jaboticabal, BrazilFEDER/COMPETE/POCI - Operational Competitiveness Internationalization Programme: POCI-01-0145-FEDER-006958National Funds of FCT-Portuguese Foundation for Science and Technology: UID/AGR/04033/2013National Funds of FCT-Portuguese Foundation for Science and Technology: UID/QUI/00616/2013Elsevier B.V.Universidade Estadual Paulista (Unesp)Inst Fed Triangulo MineiroUniv Tras Os Montes & Alto DouroSiqueira, Hygor Evangelista [UNESP]Tarle Pissarra, Teresa Cristina [UNESP]Valle Junior, Renato Farias doSanches Fernandes, Luis FilipeLeal Pacheco, Fernando Antonio2018-11-26T17:31:24Z2018-11-26T17:31:24Z2017-05-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article26-36application/pdfhttp://dx.doi.org/10.1016/j.eiar.2017.02.002Environmental Impact Assessment Review. New York: Elsevier Science Inc, v. 64, p. 26-36, 2017.0195-9255http://hdl.handle.net/11449/16279210.1016/j.eiar.2017.02.002WOS:000401381600004WOS000401381600004.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEnvironmental Impact Assessment Review1,071info:eu-repo/semantics/openAccess2024-01-08T06:28:04Zoai:repositorio.unesp.br:11449/162792Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-01-08T06:28:04Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A multi criteria analog model for assessing the vulnerability of rural catchments to road spills of hazardous substances
title A multi criteria analog model for assessing the vulnerability of rural catchments to road spills of hazardous substances
spellingShingle A multi criteria analog model for assessing the vulnerability of rural catchments to road spills of hazardous substances
Siqueira, Hygor Evangelista [UNESP]
Road accidents
Hazardous substances
Road spills
Multi criteria analysis
Geographic information systems
Environmental protection area
title_short A multi criteria analog model for assessing the vulnerability of rural catchments to road spills of hazardous substances
title_full A multi criteria analog model for assessing the vulnerability of rural catchments to road spills of hazardous substances
title_fullStr A multi criteria analog model for assessing the vulnerability of rural catchments to road spills of hazardous substances
title_full_unstemmed A multi criteria analog model for assessing the vulnerability of rural catchments to road spills of hazardous substances
title_sort A multi criteria analog model for assessing the vulnerability of rural catchments to road spills of hazardous substances
author Siqueira, Hygor Evangelista [UNESP]
author_facet Siqueira, Hygor Evangelista [UNESP]
Tarle Pissarra, Teresa Cristina [UNESP]
Valle Junior, Renato Farias do
Sanches Fernandes, Luis Filipe
Leal Pacheco, Fernando Antonio
author_role author
author2 Tarle Pissarra, Teresa Cristina [UNESP]
Valle Junior, Renato Farias do
Sanches Fernandes, Luis Filipe
Leal Pacheco, Fernando Antonio
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Inst Fed Triangulo Mineiro
Univ Tras Os Montes & Alto Douro
dc.contributor.author.fl_str_mv Siqueira, Hygor Evangelista [UNESP]
Tarle Pissarra, Teresa Cristina [UNESP]
Valle Junior, Renato Farias do
Sanches Fernandes, Luis Filipe
Leal Pacheco, Fernando Antonio
dc.subject.por.fl_str_mv Road accidents
Hazardous substances
Road spills
Multi criteria analysis
Geographic information systems
Environmental protection area
topic Road accidents
Hazardous substances
Road spills
Multi criteria analysis
Geographic information systems
Environmental protection area
description Road spills of hazardous substances are common in developing countries due to increasing industrialization and traffic accidents, and represent a serious threat to soils and water in catchments. There is abundant literature on equations describing the wash-off of pollutants from roads during a storm event and there are a number of watershed models incorporating those equations in storm water quality algorithms that route runoff and pollution yields through a drainage system towards the catchment outlet. However, methods describing catchment vulnerability to contamination by road spills based solely on biophysical parameters are scarce. These methods could be particularly attractive to managers because they can operate with a limited amount of easily collectable data, while still being able to provide important insights on the areas more prone to contamination within the studied watershed. The purpose of this paper was then to contribute with a new vulnerability model. To accomplish the goal, a selection of medium properties appearing in wash-off equations and routing algorithms were assembled and processed in a parametric framework based on multi criteria analysis to define the watershed vulnerability: However, parameters had to be adapted because wash-off equations and water quality models have been developed to operate primarily in the urban environment while the vulnerability model is meant to run in rural watersheds. The selected parameters were hillside slope, ground roughness (depending on land use), soil permeability (depending on soil type), distance to water courses and stream density. The vulnerability model is a spatially distributed algorithm that was prepared to run under the IDRISI Selva software, a GIS platform capable of handling spatial and alphanumeric data and execute the necessary terrain model, hydrographic and thematic analyses. For illustrative purposes, the vulnerability model was applied to the legally protected Environmental Protection Area (APA), located in the Uberaba region, state of Minas Gerais, Brazil. In this region, the risk of accidents causing chemical spills is preoccupying because large quantities of dangerous materials are transported in two important distribution highways while the APA is fundamental for the protection of water resources, the riverine ecosystems and remnants of native vegetation. In some tested scenarios, model results show 60% of vulnerable areas within the studied area. The most sensitive parameter to vulnerability is soil type. To prevent soils from contamination, specific measures were proposed involving minimization of land use conflicts that would presumably raise the soil's organic matter and in the sequel restore the soil's structural functions. Additionally, the present study proposed the preservation and reinforcement of riparian forests as one measure to protect the quality of surface water. (C) 2017 Elsevier Inc. All rights reserved.
publishDate 2017
dc.date.none.fl_str_mv 2017-05-01
2018-11-26T17:31:24Z
2018-11-26T17:31:24Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1016/j.eiar.2017.02.002
Environmental Impact Assessment Review. New York: Elsevier Science Inc, v. 64, p. 26-36, 2017.
0195-9255
http://hdl.handle.net/11449/162792
10.1016/j.eiar.2017.02.002
WOS:000401381600004
WOS000401381600004.pdf
url http://dx.doi.org/10.1016/j.eiar.2017.02.002
http://hdl.handle.net/11449/162792
identifier_str_mv Environmental Impact Assessment Review. New York: Elsevier Science Inc, v. 64, p. 26-36, 2017.
0195-9255
10.1016/j.eiar.2017.02.002
WOS:000401381600004
WOS000401381600004.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Environmental Impact Assessment Review
1,071
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 26-36
application/pdf
dc.publisher.none.fl_str_mv Elsevier B.V.
publisher.none.fl_str_mv Elsevier B.V.
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
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reponame_str Repositório Institucional da UNESP
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repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
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