Abstract
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.
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.
| Original language | English |
|---|---|
| Pages (from-to) | 22-36 |
| Number of pages | 15 |
| Journal | Journal of Environmental Management |
| Volume | 232 |
| DOIs | |
| Publication status | Published - 15 Feb 2019 |
