|Title||Evaluation of watershed health using Fuzzy-ANP approach considering geo-environmental and topo-hydrological criteria|
|Author(s)||Alilou, Hossein; Rahmati, Omid; Singh, Vijay P.; Choubin, Bahram; Pradhan, Biswajeet; Keesstra, Saskia; Ghiasi, Seid Saeid; Sadeghi, Seyed Hamidreza|
|Source||Journal of Environmental Management 232 (2019). - ISSN 0301-4797 - p. 22 - 36.|
Alterra - Soil, water and land use
Soil Physics and Land Management
|Publication type||Refereed Article in a scientific journal|
|Keyword(s)||Analytical network process - Fuzzy theory - Multi-criteria decision analysis (MCDA) - Soil erosion - Watershed health|
Assessment of watershed health and prioritization of sub-watersheds are needed to allocate natural resources and efficiently manage watersheds. Characterization of health and spatial prioritization of sub-watersheds in data scarce regions helps better comprehend real watershed conditions and design and implement management strategies. Previous studies on the assessment of health and prioritization of sub-watersheds in ungauged regions have not considered environmental factors and their inter-relationship. In this regard, fuzzy logic theory can be employed to improve the assessment of watershed health. The present study considered a combination of climate vulnerability (Climate Water Balance), relative erosion rate of surficial rocks, slope weighted K-factor, topographic indices, thirteen morphometric characteristics (linear, areal, and relief aspects), and potential non-point source pollution to assess watershed health, using a new framework which considers the complex linkage between human activities and natural resources. The new framework, focusing on watershed health score (WHS), was employed for the spatial prioritization of 31 sub-watersheds in the Khoy watershed, West Azerbaijan Province, Iran. In this framework, an analytical network process (ANP) and fuzzy theory were used to investigate the inter-relationships between the above mentioned geo-environmental factors and to classify and rank the health of each sub-watershed in four classes. Results demonstrated that only one sub-watershed (C15) fell into the class that was defined as ‘a potentially critical zone’. This article provides a new framework and practical recommendations for watershed management agencies with a high level of assurance when there is a lack of reliable hydrometric gauge data.