Abstract
Watershed sustainability involves hydrologic, socioeconomic, environmental, and governance aspects, assessed by the Watershed Sustainability Index—WSI. However, in data-scarce basins, the application of the WSI can be biased, because of data incompleteness and uncertainty. This bias can be mitigated by the utilization of expert-based systems and user preferences. The objective of the present study was to assess basin sustainability of a data-scarce basin (Beheshtabad basin, in Iran) using the WSI, with weights calculated by automatic expert-based methods, and to compare the basin sustainability score with those of different basins of the world. Analytical Hierarchical and Network Processes (AHP and ANP) were used to obtain unbiased WSI weights, based on the results of questionnaires applied to 30 basin managers and specialists. Although the WSI weights calculated with the AHP and ANP methods varied from 0.19 to 0.33, and were significantly different from the WSI original weights (0.25), the overall WSI scores for the Beheshtabad basin using the modified and original WSI were similar (0.69 and0.70, respectively). The similar WSI scores resulted from the additive and balanced structure of the WSI index, compensating for the variation in the indicator weights. Compared to the WSI of 10 basins from developing countries around the world, the Beheshtabad watershed ranked third. The WSI bottlenecks affecting basin sustainability were related to water availability, which could be tackled by the establishment of appropriate water management policies.
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Data availability
The datasets generated during and/or analyzed during the current study are not publicly available because the permission to publish them is in the hands of responsible organizations, and researchers are not allowed to publish them, but are available from the corresponding author on reasonable request.
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This research was supported by Shahrekord University.
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Zare Bidaki, R., Esmaeilzadeh, M. & Chaves, H.M.L. Assessing watershed sustainability with automatic expert-based methods and managers’ preferences. Sustain. Water Resour. Manag. 9, 70 (2023). https://doi.org/10.1007/s40899-023-00847-w
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DOI: https://doi.org/10.1007/s40899-023-00847-w