Identification of Vulnerability Potential of Groundwater Quality in Birjand Plain using DRASTIC Model and its calibration using AHP

Document Type : Full length article


1 MSc in Water Resources Engineering, Faculty of Agriculture, University of Malayer, Iran

2 Assistant Professor of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Iran

3 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.


Main Subjects

  1. احمدی، ج.، آخوندی، ل.، عباسی، ه.، خاشعی سیوکی، ع. و علیمددی، م. (1392). «تعیین آسیب‌پذیری آبخوان با استفاده از مدل دراستیک و اعمال آنالیز حساسیت تک‌پارامتری و حذفی (مطالعة موردی: دشت سلفچگان- نی‌زار)». مجلة پژوهش‌های حفاظت آب و خاک. ج20. ش3. ص1-25
  2. افروزی، م. و محمدزاده، ح. (1392). «ارزیابی آسیب‌پذیری آبخوان بروجن- فرادنبه با استفاده از مدل دراستیک براساس نیترات». مجلة پژوهش آب ایران. س7. ش12. ص213-218.
  1. کرمی شاه‌ملکی، ن.، بهبهانی، س.م.، مساح بوانی، ع. و خدایی، ک. (1391). «مقایسة روش‌های Logistic Regression، دراستیک اصلاح‌شده و AHP DRASTIC- در بررسی آسیب‌پذیری آب‌های زیرزمینی». مجلة محیط‌شناسی. س38. ش4. ص79-92.
  2. محمودزاده، ا.، رضاییان، س. و احمدی، آ. (1392). ارزیابی آسیب‌پذیری آبخوان دشت میمة اصفهان با استفاده از روش‌های تطبیقی DRASTIC، GODS، AVI». مجلة محیط‌شناسی. س39. ش2. ص45-60.
  3. معروفی، ص.، سلیمانی، س.، قبادی، م،ح.، رحیمی، ق. و معروفی، ح. (1391). «ارزیابی آسیب‌پذیری آبخوان دشت ملایر با استفاده از مدل‌های DRASTIC,SI,SINTACS». مجلة پژوهش‌های حفاظت آب و خاک. ج19. ش3. ص142-166.
    1. Afrozi, M. and Mohamadzadeh, H. (2013). "Aquifer vulnerability assessment Borujen-Faradonbeh Using DRASTIC model based on nitrate". Journal of Iran Water Researches. Year, 7. No. 12. pp. 213-218. (In Pershian).
    2. Ahmadi, J., Akhundi, L., Abbasi, H., Khasheii-Sivaki, A. and Alimadadi, M. (2013). "Determine aquifer vulnerability using DRASTIC model and apply single parameter sensitivity analysis and elimination (Case study: Plain Salafchegan-Reedy). Journal of researches Protection soil and water. Vol. 20. No. 3. pp. 1-25. (In Pershian).
    3. Aller, L., Bennett, T., Lehr, J.H., Petty, R.J. and Hackett, G.) 1987(. "DRASTIC: A Standardized System for Evaluating Ground Water Pollution Potential Using Hydrogeologic Settings". EPA-600/2-87-035. Ada, Oklahoma: U.S. Environmental Protection Agency.
    4. Akhavan, S., Mousavi, F., Abedi-Koupai, J. and Abbaspour, K. )2010(. "Conditioning DRASTIC model to simulate nitrate pollution case Study: Hamadan–Bahar plain. Environmental Earth Science". DOI: 10.1007/s12665-010-0790-1.
    5. Boughriba, M., Barkaoui, A., Zarhloule, Y., Lahmer, Z., El-Houadi, B. and Verdoya, M. )2010)."Groundwater vulnerability and risk mapping of the Angad transboundary aquifer using DRASTIC index method in GIS environment". Arabian Journal of Geosciences. 3. pp. 207–220.
    6. Fijani, E., Nadiri, A., Asghari-Moghaddam, A., T.-C. Tsai, T. and Dixon, B. (2013). "Optimization of DRASTIC method by supervised committee machine artificial intelligence to assess groundwater vulnerability for Maragheh–Bonab plain aquifer, Iran". Journal of Hydrology. 503. pp. 89-100.
    7. Gogu, R.C. and Dassargues, A. (2000). "Current trends and future challenges in groundwater vulnerability assessment using overlay and index methods". Environmental Geology. 39. pp. 549-559.
    8. Karami-Shahmolki, N., Behbahani, S.M, Masah-Boani, A and Khodaei, K. (2012). "Comparison of Logistic Regression, aquifer and groundwater vulnerability AHP DRASTIC- review". Journal of Environmental. Year 38. No. 4. pp. 79-92. (In Pershian).
    9. Mahmoud-zadeh, A., Rezaian, S. and Ahmadi, A, (2012). "Aquifer Vulnerability Assessment Meymeh plain of using comparative methods DRASTIC, GODS, AVI". Journal of Environmental. Year 39. No. 2. pp. 45-60. (In Pershian).
    10. Marofi, S., Soleymani, S., Ghobadi, M.H., Rahimi, GH. And Marofi, H. (2011). "Vulnerability Assessment Malayer plain of using Models DRASTIC, SI, SINTACS). Journal of researches Protection soil and water. Vol. 19. No 3. pp. 142-166. (In Pershian).


  1. Neshat, A., Pradhan, B., Pirasteh, S. and Zulhaidi Mohd Shafri, H. (2013)."Estimating groundwater vulnerability to pollution using a modified DRASTIC model in the Kerman agricultural area, Iran". Environ Earth Sci. 13 pages.
  2. Rakad, A., Ta’any, Mohammad A. 1 1 . Alaween, 2Mustafa, M., Al-Kuisi and 1Naser M. Al-Manaseer (2013). "GIS Based Model of Groundwater Vulnerability and Contamination Risk of Wadi Kufrinja Catchment Area". Jordan. World Applied Sciences Journal. 24 (5). pp. 570-581.
  3. Saaty, T.L. (1980). The Analytic Hierarchy Process. New York: McGraw-Hill International.
  4. Sener, E. and Davraz, A. (2012). "Assessment of groundwater vulnerability based on a modified DRASTIC model, GIS and an analytic hierarchy process (AHP) method: the case of Egirdir Lake basin (Isparta, Turkey)". Hydrogeology Journal. 21. pp. 701–714.
  5. 20.     Thirumalaivasan, D., Karmegam. M. and Venugopal, K. (2003). "AHP-DRASTIC: software for specific aquifer vulnerability assessment using DRASTIC model and GIS".Environmental Modelling & Software. 18. pp. 645–656.
  6. Tirkey, P., Gorai, A.K. and Iqbal, J. (2013). "AHP-GIS Based DRASTIC Model for Groundwater Vulnerability to Pollution Assessment: A Case Study of Hazaribag District, Jharkhand". India. International Journal of Environmental Protection. Vol. 2. Iss. 3. pp. 20-31.
  7. Victor Rodriguez-Galiano, Maria Paula Mendes, Maria Jose Garcia-Soldado, Mario Chica-Olmo and Luis Ribeiro (2014). "Predictive modeling of groundwater nitrate pollution using Random Forest and multisource variables related to intrinsic and specific vulnerability: A case study in an agricultural setting (Southern Spain)". Science of the Total Environment. Vol. 476–477. pp. 189–206.
  8. Vrba, J. and Zoporozec, A. (1994). "Guidebook on mapping groundwater vulnerability". International Contribution for Hydrogeology. Hannover Heise. p. 16.
  9. US EPA (Environmental Protection Agency). (1985). "DRASTIC: a standard system for evaluating groundwater potential using hydrogeological settings". Ada, Oklahoma WA/EPA Series. p. 163.