فهرست مطالب مریم سادات کاهه

One of the important factors in the sustainability of a region's development is the availability of adequate and suitable water resources for various uses, which, in addition to quantity, should be suitable from a qualitative point of view. Groundwater resources are one of the most reliable sources of water supply, which has suffered in recent years due to increased harvesting. The aim of this study is to evaluate the quality of groundwater in Sari-Neka study area and zoning of this area for agricultural use. In this study, 65 water wells in this area were chemically analyzed in year 1392-93. The samples were examined for the effective parameters in agriculture including chlorine (Cl), electrical conductivity (EC), acidity and alkaline (PH), sodium carbonate (RSC) residue. Finally, the water quality status was evaluated using the Wilcox index and the qualitative zoning map was considered. The results showed that more than 90% of the quality water test samples of wells used for agriculture in the C3-S2 and C3-S1 classes are located.

In groundwater modeling, an array of factors are the cause of deviation between estimated results and observed data which demonstrate uncertainty in groundwater resources system. In this study, with the aim of investigating the uncertainty of groundwater flow model in Ali Abad plain of Qom with the area of 1712 km2, the parameter of hydraulic conductivity as the most important source of uncertainty was used to analyze the parametric uncertainty. For this purpose, in order to simulate ground water level, different uncertainty ranges in 90% of confidence interval of hydraulic conductivity was investigated by Monte Carlo method and the uncertainty assessment criteria were used to quantify the uncertainty. Eventually, the most appropriate uncertainty range was defined. The Rosenblueth’s Point Estimation Method (RPEM) was used to reduce the calculation process and time and then its performance for analyzing the parametric uncertainty was compared to Monte Carlo method using assessment criteria. Results showed that the most appropriate uncertainty range with RPEM and Monte Carlo method for hydraulic conductivity was obtained by increasing of 40% and reduction of 30% of this parameter. RPEM method showed a better performance account for 43% compared to Monte Carlo method.