Document Type : Full length article
MSc in Water Resources Engineering, Faculty of Agriculture, University of Malayer, Iran
Assistant Professor of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Iran
PhD Candidate in Water Resources Engineering, Pardis Aboureihan, University of Tehran, Iran
Water is the most important parameter in the development of human societies. One of the pillars in the development of water resources is the investigation of environmental conditions and environmental compatibility of the project. Identification of the areas vulnerable to pollution can play a major role in development strategies. In most areas of Iran, located in the arid and semi-arid region, groundwater is the most important water supply for agricultural, domestic and industrial uses. In most areas, the risk of groundwater contamination is considered as a serious restriction for this source. Therefore, it is essential to avoid groundwater contamination in groundwater resources management. One of the methods to identify vulnerable areas is the use of qualitative indicators. Among the qualitative indicators, the DRASTIC index of vulnerability to groundwater pollution has many applications. This index is obtained by combining seven different parameters. Each of the parameters of the model investigates the potential and the possibility of accepting the contamination of the aquifer and each parameter has a unique weight. So far, most studies which have been done with this indicator have led to aquifer vulnerability mapping but model calibration and optimization of input coefficients is less studied. This study was conducted to investigate the vulnerability of Birjand aquifer and increase in the accuracy of the model.
In this study, to estimate the vulnerability by contamination, different hydro-geological data were used. These data are including depth to water table, net recharge, aquifer environment, soil environment, topography, environment unsaturated and hydraulic conductivity. Then, plain vulnerability maps were computed using DRASTIC index with combination of these data. One of the most important and influential parameter in environmental contaminations is nitrate. In this project, in order to evaluate the vulnerability of the Birjand aquifer obtained by DRASTIC model, the observed data of nitrate in Birjand aquifer was tasted in 2011. According to the concentration of the Nitrate in the observation wells; the model was calibrated using Analytical Hierarchy Process (AHP). For this purpose, the parameters of the DRASTIC model, with respect to the inconsistency rate as stated, was modeled by AHP method using software provided by the Expert choice modeling. The calibration weight and then the analysis of these weights was done using the consistency coefficient.
Results and Discussion
DRASTIC layers were obtained using interpolation and classification tools in the ArcGIS 10.2 software. According to the preliminary results, depth to the water table and slope parameters has the highest weight in aquifer data.The recharge rate of the aquifer in two parts of urban areas, due to the recycled water, has higher weight than in other parts of the aquifer. According to drilling logs, influence testing, pedological testing and the aquifer environment are classified in two classes, the soil environment in four classes and unsaturated zone in tree classes. Given the high levels of recharge due to return flow, it was divided in urban areas and agricultural land according to the test results of pedological and hydraulic conductivity parameters in three classes. After obtaining the required parameters for vulnerability assessment, vulnerability map of the Birjand Aquifer was obtained using DRASTIC model. Incompatibility factor was chosen as one of the major constraints to optimize the coefficients and weights of DRASTIC model. Based on the obtained results and the value of using AHP method incompatibility factor of less than 0.08 is selected as the best option for analysis. The classification of Birjand aquifer vulnerability was presented based on DRASTIC with weight of AHP model. This includes four categories of very low, low, moderate and moderate to high. The results show the sensitivity of the aquifer in the outlets due to the high water table.
The results provided by the DRASTIC model showed that the model was not accurate enough to identify vulnerable areas and it is needed to calibrate the weights of models. Therefore, in this study using Analytical Hierarchy Process (AHP) and observational data of nitrate, the model was calibrated in the Birjand aquifer. The results indicated that the modified DRASTIC model has the higher accuracy in comparison with common DRASTIC model. There is also a good correlation between the improved weights using AHP method and the observed nitrate concentration in observation wells.