Novel approach for issues identification in transboundary water management using fuzzy c-means clustering

Rivers, a major freshwater resource, are transboundary in nature (310 international basins) and are not governed by any water agreements. Scientific knowledge based on transboundary water resources is confined; hence, the identification of knowledge gaps to smoothen decision making in water management is necessary. To figure out the issues that affect water sharing is deemed important. This paper highlights the core issues involved in transboundary water management and prioritizes the identified issues using fuzzy c-means clustering algorithm. A group of 30 experts from various fields were consulted to rank the issues which were clustered to determine the prioritized rank. In a hypothetical basin affected by all the transboundary issues, flood control and benefit sharing are rated with very high importance. Prioritization would help in the identification of issues of high relevance that affect water sharing. This may facilitate efficient water sharing agreements among riparians and be useful in international water governance.