Hydrology
Asghar Asgharai Moghaddam; Ata Allah Nadiri; Faiba Sadeghi Aghdam
Abstract
Naqadeh plain located in the southwestern part of Urmia Lake has suitable water resources. In recent years, agricultural development and increasing industrial units, in addition to inadequate disposal of urban, industrial and agricultural wastewater to the Gedar River, increase the risk of groundwater ...
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Naqadeh plain located in the southwestern part of Urmia Lake has suitable water resources. In recent years, agricultural development and increasing industrial units, in addition to inadequate disposal of urban, industrial and agricultural wastewater to the Gedar River, increase the risk of groundwater contamination. In order to monitor the groundwater resources of this plain, 33 water samples from exploitation wells were collected during July 2016. Hydrochemical parameters and the concentration of the major, minor and heavy metals elements of collected samples were analyzed. In order to identify the origin of heavy metals and the related geogenic and anthropogenic pollution sources of them, hydrochemical diagrams, statistical analysis, spatial distribution maps and geological interpretations were used. The results indicate the concentration of some parameters including EC, and heavy metals include, Fe, Mn, and Al are higher than the international standard limits. HPI was used to understand the drinking quality of groundwater resources in regard to the concentrations of six heavy metals. Classification results show a good quality for 70% and inadequate quality for 30% of the samples. The total HPI index of Naqadeh plain is 23.24, which is lower than its critical values(100). Also, the highest HPI of sampling points with values of 161,220 and 871 threaten human health. High concentrations of heavy metals can be related to the dissolution of geological formations, mining of iron ore, and the activity of industrial units and the condensation of elements in groundwater due to high evaporation in areas with a low depth of groundwater.
Yaser Bageri; Esfandiar Abbas Novinpour; A Nadiri; Keiwan Naderi
Abstract
Most of the country's geographically area is located in dry and semi-dry zone with low rainfall. The growing population, the limitation of water resources and the prevalence of groundwater resources in most parts of the country requirement to accurate prediction of the amount of these resources due to ...
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Most of the country's geographically area is located in dry and semi-dry zone with low rainfall. The growing population, the limitation of water resources and the prevalence of groundwater resources in most parts of the country requirement to accurate prediction of the amount of these resources due to the importance of these resources in optimal planning and management. In this research, in order to estimate the fluctuations of groundwater level in the Baruq aquifer, the artificial intelligence models including fuzzy, support vector machine and neural network models were used by the data of depth from 7 piezometers with long-term data of 14 years, as well as changes in temperature and precipitation in this period. Despite the inherent abilities of each models in predicting groundwater level, the heterogeneity of the study area prevented the high efficiency of these models. Therefore, SOM-AI modeling combined the self-organized maps (SOM) classification method and each model that is increased the efficiency of each composite model in different parts of the aquifer by dividing the study area into homogeneous regions. The results showed that the proposed method can be an effective method in the modeling of heterogeneous and even multi-layered aquifers.
