Integrated Watershed Management

Integrated Watershed Management

Landslide hazard mapping using hybrid Multi-Attribute Decision-Making methods in the Qezel Owzan Watershed, Qazvin Province

Document Type : Original Article

Authors
Amin Salehpour Jam 1
Jamal Mosaffaie 1
Samad Shadfar 1
Faramarz Sarfaraz 2
1 Soil Conservation and Watershed Management Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran
2 Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Qazvin, Iran
10.22034/iwm.2024.2045897.1189
Abstract
Extended Abstract
Introduction: Landslides are a natural hazard that cause human and financial losses. This phenomenon also results in significant environmental damage through land degradation in landslide-prone areas. In this regard, it is important to prepare landslide hazard maps to effectively plan for landslide risk management. In recent years, multi-attribute decision-making (MADM) methods have been used in landslide hazard mapping. This study aims to evaluate the performance of widely used hybrid MADM methods, including AHP-SAW, AHP-TOPSIS, and AHP-VIKOR for creating landslide hazard maps in the Qezel Owzan region, Qazvin Province.
Materials and methods: In the present study, various causal factors, including rainfall, slope angle, slope aspect, lithology, altitude, land use, distance to roads, distance to faults, and distance to streams, were considered as effective indicators for predicting landslide occurrence. Two normalization methods were employed, namely, the Min-Max normalization method for the SAW method and the vector normalization method for the TOPSIS and VIKOR methods. In addition, the group decision-making method in the Analytical Hierarchy Process (AHP) was used to determine the weights of causal factors based on the perspectives of 12 experts. Furthermore, the Quality sum (Qs) index and the Area Under the Curve (AUC) values of the Receiver Operating Characteristic (ROC) curves were used to validate the performance of the different MADM methods used in this study.
Results and Discussion: The Qs values ​​for the AHP-SAW, AHP-TOPSIS, and AHP-VIKOR methods were calculated as 0.241, 0.262, and 0.626, respectively. Also, the AUC values ​​for​​ these three methods were calculated 0.769, 0.786, and 0.805, respectively, so that they are within the acceptable and excellent acceptance range. In this study, the AHP-VIKOR method is introduced as the best method for producing a landslide hazard map. One of the disadvantages of using hybrid MADM methods is their reliance on the precise calculation of the weights of causal factors, which heavily depends on expert's view points in the AHP method. To adress this, the group decision-making method was applied in AHP to improve weights calculations. It is worth noting that the AHP-SAW method used in this study, which demonstrates acceptable accuracy in producing landslide hazard maps, has also been introduced in other studies as a simple and efficient method. Although the SAW method is a simple weighting method based on normalizing the decision matrix data, determining the weights of the indicators, and aggregating the indicators based on the weighted average method, it is widely used in environmental assessments. Additionally, the Density Ratio (Dr) values ​​of different landslide hazard classes, calculated for the VIKOR method, exhibit an upward trend from areas with very low potential for landslide occurrence (class I) to areas with very high potential for landslide occurrence (class V). This trend highlights the VIKOR method capability for producing landslide hazard maps in the study area.
Conclusion: The evaluation of hybrid MADM methods based on performance evaluation indicators, indicated acceptable (AHP-SAW and AHP-TOPSIS) and excellent (AHP-VIKOR) performance of methods for producing landslide hazard maps. Due to the presence of areas with high to very high landslide hazard potential in this region, planning for landslide risk management is strongly recommended. Although landslide distribution maps are beneficial for evaluating MADM methods, the lack of reliance on these maps during the MADM process is one of the strengths of this approach. However, accurately determining the weights of causal factors remains a challenge. To enhance the weight calculation process, using the group decision-making method in AHP is highly advisable.
Keywords
AHP
Causal factors
Decision matrix
Group decision-making
MADM

Subjects

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  • Receive Date 16 November 2024
  • Revise Date 01 December 2024
  • Accept Date 21 December 2024