Desertification early warning based on forecasting of groundwater quantitative and qualitative parameters (Case Study: Mashhad plain aquifer)

This paper tries to forecast and determine the desertification warning threshold using groundwater resources quantitative and qualitative parameters modeling. The data from 62 piezometric wells and 55 quantitative wells were selected from Iranian Water Resources Management Company and Khorasan Razavi Regional Water Authority. Handling missing data, and statistical analyzes such as the Mann-Kendall test and Pearson correlation were performed. The desertification intensity and early waring maps was provided based on the Iranian Model of Desertification Potential Assessment (IMDPA) Model. The maps of quantitative and qualitative indices of groundwater were classified according to the desertification severity and threshold of each index for a 20-years period (1996-2016). Desertification intensity and warning threshold maps of each groundwater quantitative and qualitative index were classified according to the IMDPA Model. The ground water parameters were predicted by MATLAB 2015 software and artificial intelligence fore 2022. The results showed that among the quantitative and qualitative indices the highest decertification warning area was related to drop index. The electrical conductivity index was in second-order warning. Sodium sorption index is located in low desertification class and only southern part of Mashhad aquifer will be in warning condition in 2020. In terms of chlorine content, the aquifer of Mashhad plain has not been under warning condition. But considering the trend of changes in the index in the future may be on the verge of warning.