Land subsidence risk assessment using GIS fuzzy logic spatial modeling in Varamin aquifer, Iran

The extent of the subsidence and the consequents damage to most of the residential and populated areas of Iran have made this phenomenon one of the most important natural hazards after the earthquake. Accordingly, in this research to assess the land subsidence risk, a GIS fuzzy logic spatial modeling was applied. In this regard, four stages were performed. In stage 1, 14 factors affecting subsidence including aquifer thickness, bedrock depth, Debi zonation of pumping wells, transmissivity, specific yield, Groundwater drawdown in 20 year, soil type, slope, altitude based on DEM, erosion, annual rainfall, distance of fault, lithological units, and land use, were prepared based on the literature review. In stage 2, the parameters were standardized with the fuzzy membership functions. Moreover, in stage 3, for aggregation parameters, several fuzzy overlay operation models were used. Finally, to verification of the models, the statistical benchmarks based on observed land subsidence were used. Accordingly, the GAMMA 0.8 fuzzy overlay model with the most abundance of rank 1, and the SUM fuzzy overlay model with the most abundance of rank 16 among the other models are introduced as the most consistent and the worst consistent models with observed land subsidence data, respectively.

Automated summary

The research utilized GIS fuzzy logic spatial modeling to assess land subsidence risk, analyzing 14 factors and using fuzzy overlay operation models to identify the most consistent and least consistent models with observed land subsidence data.