Application of GIS-Interval Rough AHP Methodology for Flood Hazard Mapping in Urban Areas

Abstract

Abstract:Floods are natural disasters with significant socio-economic consequences. Urban areas with uncontrolled urban development, rapid population growth, an unregulated municipal system and an unplanned change of land use belong to the highly sensitive areas where floods cause devastating economic and social losses. The aim of this paper is to present a reliable GIS multi-criteria methodology for hazard zones' mapping of flood-prone areas in urban areas. The proposed methodology is based on the combined application of geographical information systems (GIS) and multi-criteria decision analysis (MCDA). The methodology considers six factors that are relevant to the hazard of flooding in urban areas: the height, slope, distance to the sewage network, the distance from the water surface, the water table and land use. The expert evaluation takes into account the nature and severity of observed criteria, and it is tested using three scenarios: the modalities of the analytic hierarchy process (AHP). The first of them uses a new approach to the exploitation of uncertainty in the application of the AHP technique, the interval rough numbers (IR'AHP). The second one uses the fuzzy technique for the exploitation of uncertainty with the AHP method (F'AHP), and the third scenario contemplates the use of the traditional (crisp) AHP method. The proposed methodology is demonstrated in Palilula Municipality, Belgrade, Serbia. In the last few decades, Palilula Municipality has been repeatedly devastated by extreme flood events. These floods severely affected the transportation networks and other infrastructure. Historical flood inundation data have been used in the validation process. The final urban flood hazard map proves a satisfactory agreement between the flood hazard zones and the spatial distribution of historical floods that happened in the last 58 years. The results indicate that the scenario in which the IR'AHP methodology is used provides the highest level of compatibility with historical data on floods. The produced map showed that the areas of very high flood hazard are located on the left Danube River bank. These areas are characterized by lowland morphology, gentle slope, sewage network, expansion of impermeable locations and intense urbanization. The proposed GIS-IR'AHP methodology and the results of this study provide a good basis for developing a system of flood hazard management in urban areas and can be successfully used for spatial city development policy.

Novel Integrated Multi-Criteria Model for Supplier Selection: Case Study Construction Company

“…In this way the relative factors can be divided into cause-and-effect in order to gain a better insight into their mutual relations. This also provides a better understanding of the complex structure of this problem, relations between the factors, and relations between the structure level and influence of the factors [99].…”

“…The combination of rough AHP and MABAC method proposed in [95][96][97], and is used in [98] for selection of medical tourism sites. The combination of interval rough AHP and GIS is proposed for flood hazard mapping [99]. Rough AHP and rough TOPSIS approach are also used in the work of Song et al [100].…”

Review of the Literature on Multicriteria Methods Applied in the Field of Public Security

“…The literature indicates that the MCDA methods are used and applied to solve decision problems in many areas, as [2,11,19]: information and communication technologies [22]; business intelligence [23]; environmental risk analysis [24,25]; environmental impact assessment and environmental sciences [26]; water resources management [27][28][29]; solid waste management [30,31]; remote sensing [32,33]; flood risk management [34,35]; health technology assessment [36,37]; health care [38]; transportation [39]; nanotechnology research [40]; climate change [41]; energy [42,43]; international politics and laws [44]; Human resources [45]; Investment decisions [46]; performance and benchmarking [47]; Supplier selection [48]; E-commerce and m-commerce [49]; Agriculture and horticulture [50]; Chemical and biochemical engineering [51]; Software evaluation [52]; Network selection [53]; Policy, social and education [54]; HVAC systems and small scale energy management [55].…”

Location Selection for Wind Farms Using GIS Multi-Criteria Hybrid Model: An Approach Based on Fuzzy and Rough Numbers

“…Since rough numbers belong to the group of interval numbers, arithmetic operations applied in interval numbers is also appropriate for rough numbers [55].…”

“…Then we assume that there exists set build with k classes representing DMs preferences, R = (J 1 , J 2 , ..., J k ) with condition J 1 < J 2 <, ..., < J k . Then, ∀ X ∈ U, J q ∈ R, 1 ≤ q ≤ k lower approximation Apr(J q ), upper approximation Apr(J q ) and boundary interval Bnd(J q ) are determined, respectively, as follows [55]:…”