Assessing the vulnerability of groundwater is an effective tool to identify vulnerable areas and conservation activities in order to maintain water quality in these areas. DRASTIC method has been used for vulnerability assessment more than other methods in scale area. The weakness of this method is estimating the weights of the model parameter. The aim of this research is to optimize the weights of DRASTIC model by using statistical nonparametric method. In this regard, the appropriate inputs of DARSTIC model were collected from Dezful area, and then vulnerability of the groundwater of this area was determined based on the primary weights of the model parameters. The final weights of the parameters were optimized using nonparametric test and the concentration of the nitrates in Dezful area. Results show better performance of optimized DRASTIC model than original DRASTIC model.

IntroductionDrastic model is an index and overlapping model that has been designed for producing vulnerability scores for different points by combining several thematic layers. Overlapping distinguished methods are the most applicable methods for evaluating vulnerability of aquifers because they are cheap, they can directly reach a defined goal, the used data in the methods are accessible or can be estimated, their final results can easily be described, and they are suitable for managerial decision making. However, ranking system of parameters of this method is an irrational and unreliable system. These classifications are based on Boolean method. If classification is done based on Boolean method, it will cause a zone to displace a story to a higher or lower score with little change which is not acceptable and justifiable. But it seems that one can present a suitable method for classification and ranking using fuzzy theoretical fundamentals compared with Boolean method.

The main land use in Kordkandi-Duzduzan plain is agricultural activities and therefore the possibility of aquifer contamination by irrigation return flows contaminated by chemical fertilizers is very high. Thus, vulnerability assessment of the aquifer seems to be essential for the land use management and preventing groundwater contaminations in the area. The main aim of this study is mapping the region's vulnerability by DRASTIC method and then calibration of DRASTIC model with nitrate data to improve this method. Factors affecting the groundwater vulnerability such as depth of groundwater, net recharge, aquifer media, soil media, topography, impact of vadose zone, and hydraulic conductivity were prepared as raster format in GIS media. Two nitrate data sets were used for validation and calibration of DRASTIC model. The results showed that the determination coefficient between nitrate concentration and the corresponding vulnerability increased from 0.6783 to 0.7903 when modifying layer weights. Based on calibrated DRASTIC vulnerability map, vulnerability index for the study area was calculated between 66.56 and 148.89. The determination coefficient between nitrate concentration values and calibrated DRASTIC vulnerability map were increased compared to the original DRASTIC map which confirms the validity of the calibration process.

Proper management of groundwater resources, as the main source of fresh water, is very important. Groundwater vulnerability assessment has been applied as a management tool for prioritizing the use of resources, controling the contaminant transfer and adopting cost-effective ways for aquifer management. This study has adopted a novel approach based on DRASTIC method, analytic hierarchy process (AHP), and genetic algorithm (GA) optimization method to assess the vulnerability of Shiraz aquifer. AHP was utilized to modify the rank of DRASTIC model’ s parameters and GA optimization model was used to optimize the weights of DRASTIC parameters based on hydro-geological characteristics and nitrate concentrations of the Shiraz aquifer. The main aim of the GA-AHP model was to maximize the DRASTIC index correlation with nitrate concentration. The vulnerability map of Shiraz plain was provided using geographic information system (GIS). The results suggested that the southern and southeastern areas of Shiraz plain were faced with very high and high classes of vulnerability, respectively. The Pearson correlation coefficient between the developed vulnerability index and the nitrate concentrations was estimated as 80%, which confirmed the accuracy of the vulnerability map of Shiraz plain.

The best way to prevent the pollution of ground water is identifying the pollution sources and vulnerable areas then providing a suitable management practice. The aim of this study was to determine the vulnerability map for urban areas and paddy fields of Babol city to present the management options. For these purposes, the aquifer of the city was evaluated with DRASTIC model. The required parameters were provided for the hydrological system and then for considering the effects of urban areas and paddy fields, some parameters' weights and rankings in DRASTIC model were modified based on the prevailing conditions in the study area. Considering the main characteristics of the study area (urban and paddy fields) DRASTIC index was calculated and the aquifer vulnerability of Babol city that was in which showed of 127 to 174. The presence of the paddy fields which showed around the city as well as unconfined aquifer in paddy fields' domain have increased the vulnerability of the aquifer in the peripheral areas of the city. Urban, multiple urban wastewater wells and absence of a centralized sewage collection system, have provided the conditions for leakage of the pollutants into the aquifer and this has caused the urban area to be considered as a region with moderate vulnerability. It is recommended to prevent to prevent from continuing damage to the Babol aquifer by employing some management practices such as centralized sewage collection system and reducing the use of agricultural inputs in paddy fields.

In countries with arid and semi-arid climates, conserving water resources is important. For this purpose, different models were presented to determine the vulnerability of areas. In Iran, due to climatic conditions and water shortage, so for years, various researchers have used various methods, including the drastic method to determine the vulnerability. In this research, a vulnerability map of Sabzevar aquifer has been prepared using a drastic model. Sabzevar aquifer located in the northeast of Iran with an area of 5455. 4 square kilometers has a dry and desert climate with hot and dry summers and cold winters. The drastic model is obtained through 7-layer overlap (groundwater depth, net nutrition, aquifer environment, soil type, topography, influence of unsaturated area and hydraulic conductivity of the aquifer) and shows a detailed map of the aquifer vulnerability. ArcGis10. 5 software was used to draw the drastic model map. The numerical value of the drastic model in the study area is between 81 and 159 (from low vulnerability to high vulnerability). Drastic map showed that a very small area from the west of the study area has low vulnerability and the central areas of the plain have high vulnerability. Other parts of the region are moderately vulnerable. Shallow groundwater depth in the central areas of the plain and also low slope in the above area has the greatest impact on the vulnerability of the region. Due to the volume of agricultural activities in the central areas of the plain, measures should be taken to prevent possible contamination of the aquifer. Due to the fact that the concentration of nitrate in groundwater sources was not available in the study area, so electrical conductivity was used to validate the zoning of the drastic model. The overlap of electrical conductivity with the drastic map showed that the electrical conductivity was high in the center of the vulnerable plain. This can also confirm the accuracy of the drastic model.

Coastal aquifers have a high potential for contamination by seawater intrusion. Thus, the vulnerability of groundwater resources can be very effective in identifying vulnerabilities and sensitive groundwater aquifers. This study was conducted to evaluate Kish island aquifer vulnerability. The DRASTIC model was employed and modified based on the coastal aquifer conditions. Two additional parameters were included to the model which describes the balance between seawater and aquifer water level. The vulnerability maps were produced by DRASTIC and M-DRASTIC models. The comparison of these maps was performed using EC and TDS as the main indicators. The required data were collected from the existing reports as well as some extra direct water sample measurements. The overlaying of the vulnerability map was obtained by the DRASTIC method. Comparison of M-DRASTIC with EC and TDS maps showed that the mean differences for DRASTIC map with EC map is 17.41 and 10.24, respectively and for M-DRASTIC is 0.69 and 0.55, respectively. This indicates that the M-DRASTIC model is more adapted to coastal zones. The vulnerability index in DRASTIC method is generally lower than M-DRASTIC range. Based on the M-DRASTIC vulnerability analysis, it was found that 17.8, 48.1 and 34.1 percents of Kish island area is under average, high and very high risk of groundwater contamination, respectively.

Locating and identifying vulnerable areas of the aquifer and managing water supplies use and land use is a good approach to preventing underground water pollution. Nitrate has always been considered as a water pollution index. The aim of this study was assessing the vulnerability of Meymeh aquifer to nitrate through GIS, statistical methods, and Drastic Model. Drastic Model identified the vulnerability of Meymeh Aquifer as low and medium (75-128). After calculating the drastic new index using Raster Calculation in ArcGIS, the correlation between nitrate concentrations in groundwater samples and the new drastic index was calculated. The correlation coefficient of-0/162 (before optimization) to0/842 (after optimization) has increased. These correlations were significant at the 95% probability level (P-value <0/05). To gain nitrate concentration maps, samples were taken through standard sampling principles from 10 wells and analyzed through spectrophotometry approach. Next, nitrate concentration maps were drawn using interpolation models. Combining vulnerability map and nitrate concentration map indicates that most of the area under study was safe and low-risk and only one area of Meymeh was a high-risk area with nitrate concentration above 50 milligrams per liter in underground water. According to the nitrate concentration zonation map, The highest concentrations were observed in groundwater in the southern region of the Meymeh aquifer is due to the interaction of pollution caused by farming activities, Return water irrigation, Lithology, Higher nutrition rates, Hydraulic Conductivity and The permeability of the soil.

Groundwater vulnerability assessment is typically accomplished as a management tool to protect groundwater resources. In this research, the DRASTIC model which is an empirical one used for evaluating the potential of an aquifer for pollution was employed to evaluate the vulnerability of Shahrood alluvial aquifer. Moreover, the sensitivity of the model paramneters was assessed to identify the ones with greatest effect on vulnerability. The model layers including depth to groundwater table level, recharge, aquifer media, topography, impact of unsaturated zone, and hydraulic conductivity were prepared and classified in the ArcGIS software based on analyses of both the available data and the layer of surface soil texture using Aster satellite images. Once the vulnerability index was calculated, the sensitivity map of Shahroud aquifer vulnerability was analyzed using the two parameter removal and single parameter sensitivity methods. These were further verified by textural analysis of soil samples from different parts of the region. The layers with appropriate weights were overlaid and the DRASTIC index of the aquifer was estimated at 28 to 148. The highest vulnerability was detected in the northern margins and southwestern parts of the aquifer while other parts were characterized by medium to low vulnerability. The low nitrogen concentration observed in the farm areas and its rise to 45 mg/l in the northern stretches of the aquifer bear witness to the accuracy of the zoning rendered by the DRASTIC model. Based on the vulnerability map of Sharoud aquifer, it was found that 1.6% of the aquifer’s area has a very high vulnerability or potential for pollution followed by 10%, 28.8%, and 18.9% of the area were identified as having high, medium and low potentials for pollution, respecytively. The remaining (i.e., 40.5%) was found to have no risk of pollution.