Evaluation of Groundwater Vulnerability of aquifers in Aisin plain by DRASTIC and GODS models and GIS

In arid and semi-arid regions such as Iran, where the average annual rainfall is less than one-third of the world's average annual rainfall, groundwater is an important source of drinking water. Quantitive and irregular rainfall, limited surface water resources, and its absence in many parts of the country have led to the widespread use of groundwater. Today, increasing agricultural, horticultural and livestock activities on the one hand and industrial and workshop activities and population development along with population growth, on the other hand, excessive use of natural resources and expansion of industrial and agricultural activities and mass production of waste and scrap, groundwater resources are threatened. Seriously and has caused a lot of pollution. Qualitatively, most groundwater reservoirs are vulnerable to ministerial sources. Point sources of pollution from domestic and industrial wastewater and non-point sources of pollutants result from improper and excessive consumption of fertilizers and pesticides and their leaching into groundwater. Widespread groundwater pollution and the growth and awareness of human societies about the importance of these vulnerable resources have led to extensive efforts to protect groundwater. The process of regenerating aquifers on a regional scale in a reasonable time frame is not possible because groundwater flows very slowly. Vulnerability assessment is a way to zoning areas that are most prone to contamination; therefore, to prevent contamination and effective groundwater management, it is necessary to assess the vulnerability of aquifers because vulnerability can help determine practical and practical policies for the management of groundwater resources in the path of sustainable exploitation. In our country, in the last decade, the assessment of groundwater vulnerability to pollution has grown significantly and has had good results. Vulnerability assessment is a low-cost and powerful way to identify areas prone to contamination. Vulnerability assessment is a low-cost and powerful way to identify areas prone to contamination. In the Aisin plain of Hormozgan, due to its small area, low annual rainfall, and lack of water resources in this area, the use of groundwater resources is very important. Due to population growth, industrial activities and agricultural development, and the use of agricultural pesticides and chemical fertilizers in this plain and due to lack of knowledge or understanding of the exact level of groundwater vulnerability in this area, the need for rapid techniques to identify and assess vulnerabilities. It is underground in this area. The purpose of this research is was to map the vulnerability of groundwater in the Aisin plain of  Hormozgan using DRASTIC and GODS methods and with the help of GIS.

This research was carried out by DRASTIC and GODS methods with the help of GIS. The DRASTIC method is the most important rating method for determining vulnerability, which is more common among researchers and experts and has been used. The DRASTIC method consists of a combination of seven measurable and effective hydrogeological features effective in transferring contamination to groundwater, including groundwater depth, net recharge, aquifer, soil environment, Topography, Impact of the vadose zone, and hydraulic conductivity. Aisin plain based on available data extracted from Hormozgan Regional Water Company in GIS environment and after ranking and weighing them between 1 to 10 and superimposing them, the final vulnerability map of Aisin aquifer based on the DRASTIC model obtained Came. The GODS model, which is a very simple, practical, and experimental method for rapid assessment of groundwater pollution potential, also has four characteristics of aquifer type, unsaturated area, groundwater depth, and soil type, which were used in this study. The data used in the above models were extracted from 19 piezometric wells located in Aisin plain, which were available from 1987 to 2018. In the GODS method, like the DRASTIC method for each of the hydrogeological characteristics based on the available data, in the GIS environment, a map was prepared and ranked between 1 and 5, then after superimposing them, vulnerability maps of Aisin plain with GODS model obtained.

Since in the DRASTIC model index, the minimum possible vulnerability is 23 and the maximum is 230; However, the results of the final Aisin aquifer vulnerability map by the DRASTIC method, which is almost the most complete indicator for assessing groundwater vulnerability, Showed that the range of DRASTIC index values is between 59 and 163. The map of this index has been extracted in 6 categories from non-vulnerability to high vulnerability. Most of the area (33.66%), which covers the northeastern parts, from the center to the south of the plain, has low to moderate vulnerability. After that, moderate vulnerability (19.29%) was located in parts of the center and northwest, respectively, and also very low vulnerability (14.75%) in parts of the south and east, in parts of the east and south without vulnerability (29 11.11%), in the northern and part of the center and south with low vulnerability (10.15%) and finally, high vulnerability (10.84%) in the central and western parts were in the next categories in terms of area. In fact, according to the DRASTIC model, most of the aquifer sections of the Aisin plain were in low and medium to medium vulnerability classes in terms of vulnerability potential. Also, the results of the GODS model showed that the study area is divided into three parts including low, medium, and high vulnerability. Most of the Aisin plain (66.83%) is in the range of moderate vulnerability with ranks between 0.5 to 0.3 And the lowest level (11.31%) is related to the high vulnerability potential with a rank of 0.5 to 0.7.

In general, in both methods, the inherent vulnerability of the Aisin aquifer has been evaluated in low to high vulnerability ranges, but the extent of expansion of their vulnerability ranges has been different and the DRASTIC model of different vulnerability zones due to more characteristics and different weights based on these characteristics are different. Contamination is more accurately identified.