MAPPING OF FLOOD SUSCEPTIBILITY IN CAMPINA GRANDE COUNTY - PB: A SPATIAL MULTICRITERIA APPROACH

The social and economic impacts caused by floods in urban areas are diverse and increase as the land becomes gradually impervious. Due to the increasing urbanization of cities, it is necessary to implement a better planning process and optimize the urban spaces management and occupation. Thus, the government needs to gather reliable and useful data for the decision-making process. Therefore, the GIS plays an important role among urban planning instruments. Given the current situation in Campina Grande County, Paraiba State, Brazil an area continually facing disturbances caused by occasional and concentrated rainfalls the current study aims to map the areas seen as the most susceptible to floods, by using a MCDA GIS-based model (Multi-Criteria Decision Analysis). There are five quantitative criteria considered in the analysis: slope, altitude, roads with drainage infrastructure, distance from water bodies and land use. It is a pixel by pixel analysis based on predetermined assumptions. Fuzzy functions were developed and overlay operations were performed. The results were consistent with historical records and with previous studies about the county, thus adding reliability to the model, which can be considered a potential management instrument for the case study area, as well as for cities facing similar issues.

[1]  Claudia Robbi Sluter,et al.  O PROBLEMA DA QUALIDADE DE DADOS ESPACIAIS NA ERA DAS INFORMAÇÕES GEOGRÁFICAS VOLUNTÁRIAS , 2015 .

[2]  P. Vincke,et al.  Multicriteria analysis: survey and new directions , 1981 .

[3]  Dagmar Haase,et al.  A multicriteria approach for flood risk mapping exemplified at the Mulde river, Germany , 2009 .

[4]  Xiaohong Chen,et al.  Hesitant fuzzy Hamacher aggregation operators for multicriteria decision making , 2015, Appl. Soft Comput..

[5]  Xiaowei Xu,et al.  Multi-criteria decision making approaches for supplier evaluation and selection: A literature review , 2010, Eur. J. Oper. Res..

[6]  G. Zeng,et al.  A GIS-Based Spatial Multi-Criteria Approach for Flood Risk Assessment in the Dongting Lake Region, Hunan, Central China , 2011 .

[7]  Paul E. Johnson,et al.  Psychological Investigations of Competence in Decision Making , 2004 .

[8]  P. Dheena,et al.  Multicriteria decision-making combining fuzzy set theory, ideal and anti-ideal points for location site selection , 2011, Expert Syst. Appl..

[9]  Hyun Il Choi,et al.  Identification of Flood Risk Areas using a Multi-criteria Decision Making Method , 2013 .

[10]  J. C. Packman,et al.  Assessing the impact of urbanization on storm runoff in a peri-urban catchment using historical change in impervious cover , 2014 .

[11]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[12]  Nadine Gottschalk,et al.  Hydrology In Practice , 2016 .

[13]  Dimitris Milakis,et al.  What about people in cycle network planning? applying participative multicriteria GIS analysis in the case of the Athens metropolitan cycle network , 2014 .

[14]  Jerome R. Busemeyer,et al.  Dynamic Decision Making , 2015 .

[15]  Julian Smit,et al.  Using multi-criteria evaluation and GIS for flood risk analysis in informal settlements of Cape Town: the case of graveyard pond , 2012 .

[16]  M. Bazerman.  Judgment in Managerial Decision Making , 1990 .

[17]  Nigel Harvey,et al.  Blackwell Handbook of Judgment and Decision Making , 2004 .

[18]  Eun-Sung Chung,et al.  A fuzzy multi-criteria approach to flood risk vulnerability in South Korea by considering climate change impacts , 2013, Expert Syst. Appl..

[19]  Mohamed El Alfy,et al.  Assessing the impact of arid area urbanization on flash floods using GIS, remote sensing, and HEC-HMS rainfall–runoff modeling , 2016 .

[20]  Chao Zhou,et al.  Comprehensive flood risk assessment based on set pair analysis-variable fuzzy sets model and fuzzy AHP , 2013, Stochastic Environmental Research and Risk Assessment.

[21]  S. Kafandaris.  Decision Sciences: An Integrative Perspective , 1993 .

[22]  C. Gagnet.  The World Bank Annual Report 2003 , 2003 .

[23]  Shyi-Ming Chen,et al.  Multicriteria linguistic decision making based on hesitant fuzzy linguistic term sets and the aggregation of fuzzy sets , 2014, Inf. Sci..

[24]  L. Innes.  South African School Geography: Underpinning the Foundation of Geospatial Competence , 2012 .

[25]  Yu-Wei Chang,et al.  A new method selection approach for fuzzy group multicriteria decision making , 2013, Appl. Soft Comput..

[26]  Milena Lakicevic,et al.  Decision making in urban forestry by using approval voting and multicriteria approval method (case study: Zvezdarska forest, Belgrade, Serbia) , 2014 .

[27]  Jacek Malczewski,et al.  GIS‐based multicriteria decision analysis: a survey of the literature , 2006, Int. J. Geogr. Inf. Sci..

[28]  Thorsten Gerber,et al.  Judgment And Decision Making An Interdisciplinary Reader , 2016 .

[29]  Jiangjiang Wang,et al.  Review on multi-criteria decision analysis aid in sustainable energy decision-making , 2009 .

[30]  P. Burrough,et al.  Principles of geographical information systems , 1998 .

[31]  Andréa Luiz de Sá de Oliveira.  Modelagem espacial de predição de riscos de incêndios com lógica fuzzy, comparação e validação , 2013 .