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A new framework for strategic planning to stabilize a shrinking lake

Author:
Banihabib, Mohammad Ebrahim, Azarnivand, Ali, Peralta, Richard C.
Source:
Lake and reservoir management 2015 v.31 no.1 pp. 31-43
ISSN:
2151-5530
Subject:
drying, hybrids, lakes, models, multi-criteria decision making, planning, saline water, sustainable development
Abstract:
Preventing Lake Urmia, the sixth largest saltwater (endorheic) lake on the earth, from rapidly drying up is a paramount mission of the Iranian government. Thus, a new framework was proposed to develop a strategic plan to stabilize the shrinking lake, based on sustainable development criteria (SDC). We developed the strategies via the new hybrid Strategic Sustainable Planning Framework (SSPF), including a strength–weakness–opportunity–threat (SWOT) analysis matrix, SDC, multi-criteria decision making models (MCDMs), and sensitivity analysis. First, to develop aggressive, conservative, competitive, and defensive strategies, SSPF analyzed site-specific internal strengths and weaknesses plus external opportunities and threats. It then, preliminarily ranked the strategies by embedding SDC within MCDMs (Analytic Hierarchy Process [AHP]; Simple Additive Weighting [SAW]; and Technique for Order of Preference by Similarity to Ideal Solution [TOPSIS]). To promote confidence in selection of the strategy, sensitivity analyses of the results were also performed. Here, the selected strategy had the highest rank among the set of strategies, with the least sensitivity to the input data variations. SAW and AHP were the models least and most sensitive to SDC weight variations, respectively. According to sustainability analysis, the purely structurally oriented strategies were determined to be environmentally non-sustainable. Based on the results, we identified 2 conservative–competitive strategies that could stabilize the lake and prevent future losses. Adding MCDMs to the combination of SWOT and Quantitative Strategic Planning Matrix (SWOT-QSPM) enhanced the process of decision making. Hence, we recommend SSPF as a helpful approach in evaluating sustainable and strategic solutions to this and similar problems.
Agid:
1258726