A decision framework for potential dam site selection using GIS, MIF and TOPSIS in Ulhas river basin, India
The Ulhas River Basin, India has been severely impacted by climate change, frequent rainfall, and an ineffective drainage system in recent years, resulting in flooding. To alleviate flood and water scarcity issues, constructing dams in suitable locations is a crucial water management strategy. In th...
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Elsevier Ltd
2024
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Summary: | The Ulhas River Basin, India has been severely impacted by climate change, frequent rainfall, and an ineffective drainage system in recent years, resulting in flooding. To alleviate flood and water scarcity issues, constructing dams in suitable locations is a crucial water management strategy. In this study, potentiality of sites for dam construction have been evaluated by integrating spatial analytical Multi Influencing Factor (MIF), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Twelve climatic, geophysical, and accessibility factors were considered to delineate the dam site suitability. The dam site selection suitability map produced using the weighted overlay to delineate the suitability zones as 5 distinct classes �very high (15.36%),� �high (27.90%),� �moderate (25.74%),� �low (22.05%)� and �very low (8.95%). Total five suitable locations for dams have been recommended based on MIF and TOPSIS evaluation. Based on their maximum storage capacity, width, height, and cost, Dam E was given the highest ranking followed by Dam - C, A, B, and D, respectively. The majority of the chosen locations for dam construction were situated in the elevated and gently sloping eastern portion of the Ulhas River Basin. The ROC curve's AUC value was computed to be 0.806, indicating that the model's performance was �good� and suitability map exhibited a strong correlation with the available dam data. This study provides decision-makers with an inexpensive and useful tool to eliminate less suitable sites and concentrate on those with fewer limitations for constructing dams, resulting in valuable insights. � 2023 Elsevier Ltd |
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