Miandoab Plain is part of the Urmia Lake basin, which has significantly reduced the quantity and quality of its water resources in recent years. Groundwater vulnerability assessments provide a useful method for analyzing the sensitivity of aquifer to the contaminant. The purpose of this study was determining the vulnerability of the aquifer using AVI, GODS, DRASTIC and modified DRASTIC models so that the vulnerability potential to pollution can be determined more exactly. In this study, the data and information provided by the Regional Water Company of East Azarbaijan were used to provide layers needed for the preparation of each vulnerability model in the ArcGIS software. The new rates of modified DRASTIC model calculated using a correlation between each parameter and the nitrate concentration obtained from the analysis of 16 water samples taken in July 2016. The final mapping of the vulnerability maps was also verified by nitrate values. Also, validation of the final vulnerability maps was done with nitrate values. The coefficients of determined values between the nitrate concentration and vulnerability models of AVI, GODS, DRASTIC and modified DRASTIC were estimated to be 0. 004, 0. 13, 0. 18, and 0. 33, respectively. The results showed that after calibrating the model with the nitrate data, it is the best model for assessing the vulnerability of Aquifer. Based on this, it was observed that the most vulnerable groundwater pollution is in the northeast and parts of the west of the plain and the least vulnerable in the southern and southeastern parts of the plain.

Concept of vulnerability used in order to determine the pollution risk of Qazvin plains aquifer. Vulnerability map of the aquifer was developed by qualitative rating, and then pollution risk map was provided. Results shows, some part of the plain and south eastern part has high pollution risk, because of the high electric conductivity (EC) and the high groundwater level respectively. Some parts were in the low risk region and due to the high ground water level the confirmation based on the chemical analysis is unexpected. By using Nitrate data the vulnerability maps reveal dramatic changes. In the corrective drastic method, areas which were in low risk region in conventional drastic moves to the moderate risk region. Also, results from the fuzzy drastic was close to the corrective drastic. Major parts of the plane were in the moderate risk region. From the experts point of the view the results from the corrective drastic was realistic. Results from sensitivity analysis shows that weight of the aquifer depth layers and feeding decreased, unsaturated slop layer's weight and hydraulic conductivity increased. Also, the weight of the ambience of the aquifer layers and soil was remained constant.

Assessment of groundwater vulnerability to pollution is a proper tool for groundwater protection. In this study, the modified version of DRASTIC model versus the original DRASTIC model was used to investigate the vulnerability potential of Urmia groundwater which has a potential for contamination due to various industrial and agricultural activities. Precision to this model was achieved based on the revising of the ratings and weights of various factors using correlation methods in GIS environment and taking into account the correlation with the concentration of groundwater nitrate. The results showed that aquifer environment (A) did not have a significant correlation with nitrate concentration and was accordingly eliminated from the initial equation. The highest and lowest significant correlation was respectively found between soil factors (s) and depth to groundwater (D) and weighed 5 and 2. 7, respectively. The correction of ratings and weights led to improved zoning map with an increased correlation of DRASTIC index with nitrate concentration versus the original DRASTIC by 11%. Based on the modified index, 4. 3, 30. 8 and 64. 9 percent of the Urmia Plain were ranked as low, very low and without risk of pollution, respectively.

Given the fact that the DRASTIC index is ineffective in addressing the saltwater uprising issue in coastal plains, in the present study, three factors including land use, distance to shoreline, and differences between groundwater and sea level were added to the DRASTIC index. The proposed modification to DRASTIC was validated using the measured electrical conductivity (EC) data gathered from groundwater monitoring wells throughout the Talesh Plain. The results showed that the coefficient of correlation between the map of EC over the region and the modified DRASTIC was 0. 52, while for the original DRASTIC, the coefficient was 0. 45, thereby implying a stronger relationship between EC and the modified DRASTIC in the Talesh Plain. Sensitivity analysis also showed that DRASTIC and the modified DRASTIC were the most sensitive to, respectively, depth to groundwater (D) and land use (Lu). According to the single-parameter sensitivity analysis results, depth to water table and net recharge were the most effective parameters in DRASTIC, whereas the modified DRASTIC was the most sensitive to land use and depth to groundwater. It could be concluded that modifying the DRASTIC index would result in decreasing the area of very high and high vulnerable classes, and the area classified as low and moderate vulnerable could be increased...

Water shortage is one of the society's problems regarding to population increase and industries development nowadays. In addition to quantity, water quality is of special importance. The quality of groundwater and prevent further contamination, especially in areas where have highly vulnerable aquifers is particularly important. Most of the canals in the Kuchesfehan-Astane plain are no lining and this factor leads to more water waste. High water leakage has the main role of underground water pollution in this region because ground water level is high and the salient farming is the water farming in this region. This article attempts to determine the rate of water leakage from traditional irrigation canals by the Seep w software and regarding this the network parameter was made and added to drastic parameters as the 8th parameter. A new plan was drawn that presented better results regarding to the standard drastic plan. It is realized that the vulnerability rate of NW drastic plan is about 7.9 percent but in the standard drastic plan is about 1.67 percent by the comparison of standard drastic plan and NW drastic plan. Correlation coefficient was used for the appropriateness assessment and comparison of two plans (between vulnerability and nitrate density factors) and it was about 40 percent for the standard drastic and 60 percent for the NW drastic that shows the high accuracy of NW drastic plan.

Groundwater is one of the main sources of drinking water in Ranchi district and hence its vulnerability assessment to delineate areas that are more susceptible to contamination is very important. In the present study, GIS-based fuzzy pattern recognition model was demonstrated for groundwater vulnerability to pollution assessment. The model considers the seven hydrogeological factors [depth to water table (D), net recharge (R), aquifer media (A), soil media (S), topography (T), impact of vadose zone (I), and hydraulic conductivity (C)] that affect and control the groundwater contamination. The model was applied for groundwater vulnerability assessment in Ranchi district, Jharkhand, India and validated by the observed nitrate concentrations in groundwater in the study area. The performance of the developed model is compared to the standard DRASTIC model. It was observed that GIS-based fuzzy pattern recognition model have better performance than the standard DRASTIC model. Aquifer vulnerability maps produced in the present study can be used for environmental planning and predictive groundwater management. Further, a sensitivity analysis has been performed to evaluate the influence of single parameters on aquifer vulnerability index.

Background: Groundwater protection against pollution is a very important issue. Groundwater vulnerability maps are useful tools for protecting aquifers and assessing the potential for contamination. Therefore, the purpose of this study was to prepare vulnerability maps and perform sensitivity analysis to identify the most influential factors in the vulnerability of the studied aquifer. Methods: In this study, groundwater vulnerability to pollution was evaluated using DRASTIC, composite DRASTIC, and nitrate vulnerability (NV) models. Drastic is an index for the systematic assessment of potential groundwater pollution. In this method, the drastic index was calculated from the total weight and rank of the factors. For this purpose, first the factors affecting the pollution transfer, were weighted, ranked, and merged using GIS software. Then, using the overlapping techniques and after applying the necessary weight coefficients on each layer, a map of the vulnerability area of the study aquifer was prepared. Results: It was revealed that there is a significant linear relationship between all three models with the distribution of nitrate concentration. Accordingly, it was the most efficient NV model, followed by the composite DRASTIC (CD) and DRASTIC models, respectively. Also, in the studied aquifer, the DRASTIC index was between 147 and 136, the combined DRASTIC index was between 70 and 190, and the nitrate index was between 13 and 132. Conclusion: Vulnerability assessment of the studied aquifer using DRASTIC, and combined DRASTIC, and NV indices shows that, according to the DRASTIC index, 69. 7% of the studied aquifer was in the medium vulnerability class. Also, according to the combined DRASTIC index, the largest area (53. 62%) has low vulnerability and 31. 56% has moderate vulnerability. But according to the nitrate index, 77. 16% of the aquifers had very low vulnerability.

Background and Purposes: Statistical methods are widely used in environmental studies to evaluate natural hazards. Within groundwater vulnerability in particular, statistical methods are used to support decisions about environmental planning and management. In this study, the optimized of DRASTIC, Pesticide DRASTIC model parameters and land use layers (LU) were used to assess of pollution risk in catchment basin aquifer in south of Namak lake using of statistical methods. Methods: Information layers were prepared, rated (deterministic and fuzzy-statistical), weighted (original and statistical) and combined (by Index-Overlay method) in GIS environment. For modeling, from nonlinear regression for fuzzy-statistical rating (scaling) and the Pearson correlation coefficients between of nitrate concentrations with scaling parameters of DRASTIC, P-DRASTIC model and sensitivity analysis (removal and single-parameter) were performed to determine and modify of parameters weighted. Results: As result P-RASIC-LU and RASIC-LU model with statistical rating and weighting, removal-parameter sensitivity analysis, determine as best selection model based on correlation coefficient = 62%, P-value = 0. 01 and with parameters of net recharge, aquifer media, soil media, impact of vadose zone, hydraulic conductivity and land use with the weighty values of 3. 1, 4. 0, 4. 1, 3. 1, 2, 2 and 2. 5, 4. 63, 4. 15, 3. 03, 2, 1. 96 consequently. According to this model, western and southern parts of the aquifer has high pollution risk due to high net recharge and coarse-grain material in the impact of vadose zone, soil and aquifer media. Conclusion: Since reviewing of weight and rank of model parameters is limited personal opinions and increased model validation using statistical methods and GIS, It can be expected that favorable results to be followed for optimization of pollution risk model.