Abstract

ABSTRACT Interlinking rivers (ILRs) is a recent global initiative towards sustainable and equitable distribution and utilization of water resources. However, there are diverse, uncertain, and conflicting viewpoints of various water resource planning and management stakeholders towards ILR approach and its outcomes. On one hand, policy makers are seeing ILR as advantageous to the economic development of the nation; on the other hand, there is a growing concern about the negative environmental impacts of ILR. To ensure sustainable development, watershed planners across the globe need a decision support system (DSS) to effectively plan the implementation of ILR projects while considering the diverse stakeholder’s perspectives and conflicting socio-economic, environmental, and several technical criteria. Therefore, it is essential to identify and mathematically evaluate the strengths, weaknesses, opportunities, and threats (SWOT) of ILR projects to achieve economic and environmental objectives. It is indeed a challenge for watershed managers to simultaneously address the uncertainty associated with multiple criteria and group of decision-makers (stakeholders) involved in developing the SWOT model. To address these concerns, the present study proposes an advanced entropy-based SWOT fuzzy decision support system to evaluate the feasibility of ILR on a case study of ‘Ken-Betwa project’, India. The novel aspect of the advanced approach is its ability to devise seven hybrid mechanisms, which give the flexibility to reach the best solutions along with nominal, optimistic and pessimistic perspectives of the stakeholders while addressing uncertainty issues. Results demonstrate that adopting measures to minimize impact on biodiversity and climate change and implementation of sustainable construction techniques are pivotal for successful implementation of ILR project with a score of 0.12 and 0.11, respectively. The DSS provides a platform to the state and federal agencies to systematically achieve socio-economic and environmental objectives while incorporating suggestions of all decision-makers towards ILR projects.

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