Health Assessment of Agriculture-Dominated Watersheds in a Data-Scarce Region

Watershed health assessment is essential for getting a clear understanding of the present condition of watershed systems, which enables the effective allocation of resources and prioritization of management actions in a river basin. This study used an innovative framework for evaluating watershed health in data-scarce regions by considering the complex interrelations among geophysical, environmental, climatic, and anthropogenic factors. The framework brings together the Analytical Network Process (ANP) and Fuzzy Logic, addressing the challenges of managing interdependent variables.

The methodology is applied to 30 sub-watersheds of the Budhabalanga River Basin, located along the east coast of India. The ANP is used to analyse the intricate interplay among climate variables, topographic factors, non-point pollution sources, and human activities. Further, the Fuzzy Logic is employed to classify sub-watersheds based on their health status. Results show variations in watershed health, with upstream sub-watersheds being healthier compared to those in the middle and downstream regions of the river basin.

The proposed Fuzzy-ANP framework proved to be an effective tool for assessing watershed health in data-scarce regions. It provides a practical approach to sustainable resource management and can be easily adapted to other river basins. Thus providing valuable insights for enhancing watershed resilience and supporting better decision-making.