Integrating AHP, GIS, and TOPSIS, for Optimal Dam Site Selection: Leveraging Valley Derivation and Contour Line Analysis to Mitigate Flood Risks in Baghdad, Iraq

Abstract

Assessing flood risk and identifying flood-prone areas are extremely important in scientific and engineering fields. Iraq faces significant challenges due to climate variability, experiencing hot and dry conditions in summer, water scarcity, cold and rainy winters, heavy rainfall that can lead to floods, and Water seepage into the ground. This article's significance extends beyond the accumulation of rainwater and floods during peak seasons; it also addresses the need to manage and mitigate floods in the event of the potential collapse of the Mosul Dam, which is currently at risk of failure. Additionally, the annual earthquakes along the Turkish-Iraqi border threaten dam infrastructure. This requires strong management strategies to reduce the severity and associated flood risks to choose the optimal dam building location. The study aims to organize water flow dynamics and develop, analyze, and evaluate the analytical hierarchy process (AHP) rooted in the theory of (multi-criteria decision-making (MCDM)). The paper integrates valley derivation and contour lines as core techniques within the GIS framework. This is not commonly found in most studies that use AHP and TOPSIS for dam site selection. Special importance is given to identifying hydrological features while considering the impacts of climate change. It combines these methods with six layers of GIS data (e.g., NDVI, NDWI, NDBI, NDMI), which provides a comprehensive hydrological and topographical analysis of flood-prone areas. Introduce weights to distance transformation in the AHP-TOPSIS workflow, offering a novel mathematical approach to decision-making in dam site selection. Four potential dam site options (C1, C2, C3, and C4) are evaluated through valley derivations and contour lines analysis, leading to the identification of three promising dams (A, B, and C). By comparing these, the most optimum dam can be determined. The study findings indicate that site C1 received the highest rating (P = 0.667) with a completion rate of 88.15%. "Dam A = region C1" The volume of dam A is 31 million cubic meters, a storage capacity of 28,177,200 cubic meters, a pixel area of 900, a total dam area of 775,000 square meters, and a height of 40 meters, making it the most suitable option among the alternatives.