Leila Davoodi Memar Otagvar; Ebrahim Fataei; Mehdi Tajiabadi; Babak Naeimi
Abstract
Assessing the quality of water resources is an important aspect of improving their management. Given the importance of groundwater resources in the Qazvin Plain, and to have a better understanding of the status of these resources, this study has focused on examining the quality of groundwater for drinking ...
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Assessing the quality of water resources is an important aspect of improving their management. Given the importance of groundwater resources in the Qazvin Plain, and to have a better understanding of the status of these resources, this study has focused on examining the quality of groundwater for drinking and agricultural purposes. For this purpose, using hydrogeochemical parameters, two quality indicators for drinking water and irrigation were selected to investigate and study the quality of groundwater in the years 2012, 2016, and 2020. Based on the results, quality indicator maps for drinking and irrigation water were classified, and the percentage of each class's area and their average values were obtained for different land uses using ArcMap 10.8.2 software, to consider the mutual effect of land use on groundwater quality. The results showed that the average drinking water quality index in the years 2012, 2016, and 2020 were 135.02, 128.30, and 127.38 respectively, indicating an improvement in drinking water quality. The average groundwater quality index for irrigation in recent years was 62.21, 63.51, and 63.39 respectively. Generally, the quality of groundwater for drinking and agricultural purposes in the northern regions was better than in the southern regions, while the groundwater in the central and eastern parts of the plain, which includes abandoned and neglected lands, has become increasingly restricted for irrigation over time. The results demonstrated that the area of land with suitable quality groundwater for drinking is decreasing. During the study period, the area of good class has decreased, while the area of poor class has increased.
Omid Asadi Nalivan; Seid Saeid Ghiasi; Sadat Feiznia; Narges sagghazade
Abstract
At present, Groundwater contamination by nitrate, serves as one of the most important environmental issues. In respect to various land uses of Silveh basin, its ground water quality parameters might vary spatially and temporally. For this, ground water samples taken from 145 points were evaluated. After ...
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At present, Groundwater contamination by nitrate, serves as one of the most important environmental issues. In respect to various land uses of Silveh basin, its ground water quality parameters might vary spatially and temporally. For this, ground water samples taken from 145 points were evaluated. After determining nitrate spatial variations by varyogram, different methods involved distance inverse method and geo-statistics methods of radial estimator approaches, local estimator, ordinary kriging, simple kriging and global kriging were evaluated using GIS software and nitrate spatial distribution map were prepared in two time intervals (pre and post-harvest). Criteria based on the Root Mean Squared Error(RMSE), ordinary kriging method has the lowest error, and the accuracy considerably. Spatial distribution of nitrate in area groundwater indicated that there was high concentration of nitrate in land uses of agriculture and arid area. Of course, presence of shale-stone causes nitrate releases, intensifying issues. Comparison of nitrate samples concentration with national and international standards suggested that 1.38%(2 Point) of all samples have been nitrate-contaminated before harvesting, while 11.03%(16 Point) of them have been contaminated after harvesting.
Arash Malekian; Mahsa Mirdashtvan
Abstract
Nowadays, with the increasing exploitation of groundwater resources, optimal use of these resources is more and more necessary. geostatistical methods can be used to assess and monitor the quality of groundwater resources. Hashtgerd Plain is the case study of this investigation. In this study firstly, ...
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Nowadays, with the increasing exploitation of groundwater resources, optimal use of these resources is more and more necessary. geostatistical methods can be used to assess and monitor the quality of groundwater resources. Hashtgerd Plain is the case study of this investigation. In this study firstly, by using data from qualitative data which were harvested from 41 Piezometric wells, different qualitative parameters were evaluated, then by using the geostatistical methods such as: Kriging, Co-kriging and IDW the best model for mapping for aquifer quality classification was selected. Results showed that most of the indicators are better simulated by Co-kriging method, based on mutual evaluation and RMSE. The parameters of SAR and EC were selected in order to determine the irrigation water quality parameters according to Wilcox diagram. Based on these two parameters by using ArcGIS v.10 software zoning maps were prepared. Results showed that 99% of the aquifer is classified in the category of good quality irrigation water (C2S1) and 1% level in the aquifer is classified as middle class (C3S1) based on Wilcox diagrams. The results of the study can be used in aquifer management and irrigation management in the agricultural purposes.
Kh. Osati; A. Salajegheh; S. Arekhi
Abstract
Spatiality assessment of groundwater pollution is very important to determine water quality condition, pollution sources and management decisions. In this case, GIS and geostatistics methods can be useful tools. Spatiality of groundwater quality parameters, in relation with various land uses, can be ...
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Spatiality assessment of groundwater pollution is very important to determine water quality condition, pollution sources and management decisions. In this case, GIS and geostatistics methods can be useful tools. Spatiality of groundwater quality parameters, in relation with various land uses, can be very extremely. Therefore water samples from 52 wells in the Kurdan area were analyzed in this study. The results show that nitrate concentrations are less than maximum acceptable concentration in drinking water (i.e. 50 mg/L as nitrate recommended by ISIRI and WHO guideline values) except to one sample (2 percent of samples) in the study area. Various geostatistics methods, e.g. IDW (power 1-4), ordinary Kriging and RBF (five Kernel functions) were compared after assessing the variograms and the spatiality of nitrate samples. Then the model parameters were calibrated and through the specific methods, predicted and standard errors maps were prepared. Errors criteria show that Kriging is the best fitting model in the study area. Finally, probability map of NO3 concentrations exceeding the threshold value of 50 mg/L, is generated using the Indictor Kriging method. Spatiality of NO3 show that Nitrate concentration is increased where the rock type is permeable, land use is agriculture and slope is enough low to infiltrate polluted water into the wells. This research also tries to describe how to assess the spatiality of groundwater parameters by GIS.
