Determining suitable agricultural land use based on increasing virtual water storage and saving agricultural water needs (2022)

Improper allocation of water resources has created numerous problems from various aspects. In recent years, the population residing in water-scarce regions of different countries has faced water stress and issues arising from drought, such as threats to food security. On the other hand, countries and governments can manage virtual water effectively in their water policies to control their access to global water resources and, correspondingly, reduce the pressure on their limited resources. The more advanced a country is in terms of water management structures and physical infrastructure, and the greater its ability to regulate and control water based on land-use changes over time, the more adaptable it becomes. Achieving effective results in land-use change considering virtual water reserves requires taking into account various and sometimes conflicting objectives (such as reducing difficulty, increasing adaptability, continuity, economic profit, etc.).

Meeting all these goals in a way that addresses all existing needs is a very challenging task. In this regard, the use of optimization algorithms can facilitate the resolution of these issues and can be utilized in Geographic Information Systems (GIS) as decision support tools for land-use change.

In this project, a spatial decision support model has been designed for optimizing land use, based on genetic algorithms (GA and NSGA-II) to generate suitable patterns for optimizing allocation with a virtual water approach. The final results of the model development are presented as several optimal patterns in defined scenarios for the issue, which can be selected and implemented based on the existing conditions in the region.