Role of Knowledge in Water Crisis Management: A Bayesian Network Model Approach

Abstract

Water is one of the critical natural resources in the world and one of the scarce inputs of the agriculture sector in arid and semi-arid areas, including Iran. Consecutive droughts, lower groundwater levels, and lower water quality are among the concerns of farmers and policymakers in Iran. Therefore, the impacts of various factors, including the knowledge-based economy index, on the water crisis in Iran were investigated. In the present study, the Bayesian Network has been applied for modeling water crisis management in Iran. Therefore, key factors related to water crisis management were identified. The U.N. indicator was used to assess the water crisis. The composite index of the knowledge-based economy was calculated using the Knowledge Assessment Methodology. The results of the U.N. indicator indicated that Iran is in a state of a severe water crisis. The modeling results showed that advances in the knowledge-based economy index could alleviate the water crisis. Also, increased economic growth can exacerbate the water crisis. Sensitivity analysis showed that drought has the most significant impact on the water crisis in Iran. Therefore, planning and policymaking to advance the various components of the knowledge-based economy and moving towards sustainable development can help manage the water crisis in Iran.

Keywords

• bayesian network
• drought
• economic growth
• water productivity
• sensitivity analysis