Assessment of the quality and quantity of groundwater in Bahadoran plain using neural network methods, geostatistical and multivariate statistical analysis

Growing water demand in various sectors including agriculture, industry, drinking water and eventually increasing production and risk of pollution have imposed mounting pressure on water resources. The relative stability of renewable water resources makes it necessary to pay special attention to the conservation and optimal use of these resources, especially in desert areas such as Iran, and this requires careful and principle planning for the optimal use of existing water resources. In this research, a descriptive-analytical method was adopted. The data were collected from fifteen wells during an 8-year period (2010-2017). The Kolmogorov-Smirnov method was recruited to assess the normality of data distribution. Also, since the classical data (water quality data) did not take into account the spatial distribution of groundwater quality parameters, we used the geostatistics for this purpose. The results suggested that the dominant groundwater type in the Bahadoran region was sodium chloride (NaCl), which is highly volatile. This volatility can be attributed to cationic and anionic exchanges as well as the dissolution of salt and gypsum in the neogene formation of the region. On the other hand, overexploitation and increasing drainage of agricultural, residential and even industrial wastewaters in the plain water resources have drastically influenced the groundwater quality. In the second period of the studied period (2012-2013), the level of maximum classes of most parameters has increased compared to the first period, and these changes have increased with a greater slope in the third period. According to the studies, the most important formations in terms of reservoir rock, feed source of alluvial plains and groundwater quality are lower cretaceous calcareous sediments of Bahadoran.