فهرست مطالب s. nosrat-akhtar

As one of the most necessary human needs, groundwater resources play a key role in the economic and political processes of societies. Climatic and land-use changes made serious challenges to the quantity and quality of groundwater resources in the Tehran-Karaj study area. The main objective of the present study is to develop a method based on individual intelligent models, including adaptive neural-fuzzy inference system (ANFIS), gene expression programming (GEP), and combined-wavelet (WANFIS, WGEP) methods for temporal and spatial estimation of total hardness (TH), total dissolved solids (TDS), and electrical conductivity (EC) variables in the groundwater resources of the Tehran-Karaj area for statistical period of 17 years (2004-2021). The results showed that 
combined-wavelet models have higher performance than individual models in estimating three selected variables. So that the performance improvement percentage of the WANFIS model compared to ANFIS and WGEP model compared to GEP, taking into account the evaluation index of root mean square error (RMSE) were obtained (23.713%, 18.018%), (12.581%, 33.116%), and (6.433%, 12.995%) for TH, TDS, and EC variables, respectively. The results indicated a very high spatial and temporal compatibility of the estimated values of the WGEP model with the observed values for all three qualitative variables in the Tehran-Karaj area. The results showed that the concentration of qualitative variables of groundwater resources from the north to the south of the study area has an upward trend for all three qualitative variables. In urban areas, pollution caused by sewage and population increase, as well as in agricultural areas, the use of chemical fertilizers and their continued infiltration into groundwater resources and 
over-extraction of groundwater resources aggravate their pollution. Therefore, in the study area, climatic changes and the type of land use are strongly related to the quality of groundwater resources.