AI Summary & Key Takeaways
AI InsightThe detailed results show that about 38.46% of the study area faces a high or very high risk of soil degradation, posing a significant threat to sustainable food production in ULB, which is known as one of the most critical food-producing areas in Iran.
📌 3 Key Takeaways
Abstract
The primary aim of this research was to chart the risk of land degradation in the plains around Urmia Lake, which is exacerbated by the widespread dispersal of salt and dust due to the lake's drought. We aimed to develop spatiotemporal maps indicating soil degradation risk through GIS-based spatial decision analysis, based on the integrated data-driven approaches and spatial decision support systems, and particularly the GIS-based multicriteria analysis (GIS-MCDA) approach. For this purpose, relevant indicators were used as causal criteria for land degradation. Accordingly, the causal criteria were evaluated to determine their significance using the integrated fuzzy analytical network. We also applied a sensitivity analysis using a Monte Carlo simulation and global sensitivity analysis to robust the efficiency of the GIS-MCDA modeling approach. Results of this study indicate that the drought of Urmia Lake leads to the development of vast salt lands and affects the fertility of agricultural lands. The detailed results show that about 38.46% of the study area faces a high or very high risk of soil degradation, posing a significant threat to sustainable food production in ULB, which is known as one of the most critical food-producing areas in Iran. The implementation of GIS-based decision rules enables effective monitoring, observation, and mapping of soil salinization and degradation risk. The outcomes of this study will offer crucial information for decision-makers, authorities, and local stakeholders in their efforts to mitigate the environmental impacts of the lake's drought and maintain food production for the 7.3 million residents of the region.