A probabilistic GIS-OWA approach for flood susceptibility assessment

A fundamental part of flood risk management is the detection of potential flood susceptible areas. This research presents a GIS-based probabilistic framework for flood susceptibility mapping. The main advantage of the method proposed is the integration of probabilistic approach and ordered weighted averaging (OWA) to take into account the impact of the uncertainty in criteria weights and different risk attitudes of the decision maker via Monte Carlo simulation. The probabilistic GIS-OWA approach is used in a case study of evaluating susceptibility conditions in Gucheng County, central China. The spatial database includes digital elevation model (DEM), slope (SL), maximum three-day precipitation (M3DP), topographic wetness index (TWI), distance from the river (Dr), Soil Conservation Service Curve Number (SCS-CN). The results demonstrate that further improvement in the robustness of flood susceptibility evaluation can be achieved by articulating the presence of uncertainty included in criteria weights and exploring the influence of risk attitude on decision-making.

[1]  Yun Chen,et al.  The spatial framework for weight sensitivity analysis in AHP-based multi-criteria decision making , 2013, Environ. Model. Softw..

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

[3]  Pece V Gorsevski,et al.  Integrating multi-criteria evaluation techniques with geographic information systems for landfill site selection: a case study using ordered weighted average. , 2012, Waste management.

[4]  Erik Mostert,et al.  Application of the Ordered Weighted Averaging (OWA) method to the Caspian Sea conflict , 2014, Stochastic Environmental Research and Risk Assessment.

[5]  J. Malczewski,et al.  Ordered weighted averaging with fuzzy quantifiers: GIS-based multicriteria evaluation for land-use suitability analysis , 2006 .

[6]  Ian N. Durbach,et al.  Modeling uncertainty in multi-criteria decision analysis , 2012, Eur. J. Oper. Res..

[7]  R. Jacinto,et al.  Continental Portuguese Territory Flood Susceptibility Index – contribution to a vulnerability index , 2014 .

[8]  Ronald R. Yager,et al.  On ordered weighted averaging aggregation operators in multicriteria decisionmaking , 1988, IEEE Trans. Syst. Man Cybern..

[9]  L. Vasiliades,et al.  Multi-Criteria Analysis Framework for Potential Flood Prone Areas Mapping , 2014, Water Resources Management.

[10]  G. Karatzas,et al.  Flood management and a GIS modelling method to assess flood-hazard areas—a case study , 2011 .

[11]  F. Dottori,et al.  A methodology for flood susceptibility and vulnerability analysis in complex flood scenarios , 2018 .

[12]  S. Stefanidis,et al.  Assessment of flood hazard based on natural and anthropogenic factors using analytic hierarchy process (AHP) , 2013, Natural Hazards.

[13]  M. O'Hagan,et al.  Aggregating Template Or Rule Antecedents In Real-time Expert Systems With Fuzzy Set Logic , 1988, Twenty-Second Asilomar Conference on Signals, Systems and Computers.

[14]  Mustafa Neamah Jebur,et al.  Spatial prediction of flood susceptible areas using rule based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS , 2013 .

[15]  E. Rosenbloom.  A probabilistic interpretation of the final rankings in AHP , 1997 .

[16]  A. Santo,et al.  Flood susceptibility assessment in a highly urbanized alluvial fan: the case study of Sala Consilina (southern Italy) , 2011 .

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