Groundwater
Sana Maleki; Vahid Nourani; Hessam Najafi
Abstract
Systems for assessing groundwater vulnerability are designed to protect groundwater resources from pollution. The DRASTIC method is a well-known approach for determining groundwater susceptibility. One drawback of the DRASTIC method is that it relies on expert judgment to rank parameters, which introduces ...
Read More
Systems for assessing groundwater vulnerability are designed to protect groundwater resources from pollution. The DRASTIC method is a well-known approach for determining groundwater susceptibility. One drawback of the DRASTIC method is that it relies on expert judgment to rank parameters, which introduces uncertainty. This study used a new generation of Fuzzy Logic (FL), called the Z-number theory, to estimate the specific vulnerability of aquifers and address this uncertainty. The specific vulnerability of the Ardabil and Qorveh-Dehgolan aquifers was estimated using two scenarios: the DRASTIC parameters as inputs and nitrate concentration values as output. The vulnerability of the aquifer was also evaluated by comparing the results of the proposed models with those of the DRASTIC model, which served as a benchmark. The analysis showed that the Z-number Based Modeling (ZBM), which considered data reliability and weighted the rules appropriately, produced higher-quality results than the classic FL. In the Ardabil plain, the ZBM yielded results that were 53% better (using seven inputs) and 184% better (using four inputs) compared to the classic FL. In the Qorveh-Dehgolan Plain (QDP), the ZBM produced results that were 127% better (using seven inputs) and 311% better (using four inputs) than the classic FL. The irregularity and non-linearity of the data, such as the high coefficient of variation (CV) in the Ardabil plain compared to the QDP, may contribute to the high CV value in the plains. Therefore, in plains with high CV, the quality of the extracted Z-number-based rules may be lower.
erfan bahrami; Ali Shahidi
Abstract
were prepared as seven raster layers, and after ranking and weighing, the obtained DRASTIC index ranged between 45 and 115. Yet, as far as the model's major problem is applying expert opinions in ranking and weighing the variables, the main purpose of this study is to improve the DRASTIC model by using ...
Read More
were prepared as seven raster layers, and after ranking and weighing, the obtained DRASTIC index ranged between 45 and 115. Yet, as far as the model's major problem is applying expert opinions in ranking and weighing the variables, the main purpose of this study is to improve the DRASTIC model by using the gene expression model, which as an intelligent model has shown a desirable performance. Also, in a mixed form, it can cope with other models to provide acceptable results. Thus, DRASTIC variables of a 20- year statistical period (1999-2009) were defined as the model input, and nitrate concentration was defined as its output. Data in GEP model were divided into two categories: training and experimentation. Moreover, using the statistical parameters (R2, RMSE, MAE and r), the simulation results of the gene expression model were evaluated. The results indicate the model's high ability in estimating nitrate concentration and its high capability in improving DRASTIC model. For validation and improvement of DRASTIC model, statistical parameters, R2 and r, were used, which were specified according to the error of the range model. Also, for each time combining the parameter with the GEP model, a score was gained during different stages and repeated performances of the weight ranking model using weighing rank model of each parameter. Finally, by removing two parameters, S and T, the modified formula of the DRASTIC index which was obtained based on weighing was 5D, 4R, 5A, 5I, and 4C.
Majid Ramezani Sarbandi; Reza Ghazavi; Siamak Dokhani; Seyyed Mostafa Mortazavi
Volume 4, Issue 10 , June 2017, , Pages 65-80
Abstract
Groundwater is one of the most important natural resources in the world. Currently, the considerable part of Iran's water consumption, minly its drinking water, is provided from underground water sources. The emission of the surface contaminants to groundwater resources, especially in the arid and semi-arid ...
Read More
Groundwater is one of the most important natural resources in the world. Currently, the considerable part of Iran's water consumption, minly its drinking water, is provided from underground water sources. The emission of the surface contaminants to groundwater resources, especially in the arid and semi-arid regions with a limited water resources is a serious problem. In this research, the DRASTIC and GODS methods were used to study Rafsanjan plain's potential vulnerability to pollution. To this end, seven layers including groundwater depth, net recharge, aquifer media, soil, topography, and unsaturated zone hydraulic conductivity were produced for the DRASTIC method. In addition, to create potential vulnerability maps using GIS for the GODS method, four layers including type of groundwater, unsaturated zone, water table depth, and soil environment were combined. The degree of the changes of the electrical conductivity of the plains was used for the validation of the models. According to the results, the DRASTIC index is between 61.33 and 183.75 for the region, categorizing Rafsanjan plain to five classes of vulnerabilities including very low 0/54%, low 32/93%, medium 55/40%, high10/54%, and very high 0/59%. The GODS model, in contrast, classifies the region to three classes of vulnerability including low 32/27%, medium 67/04%, and high 0/69%. In both models, the most part of the study area was classified into medium level of vulnerability which were respectively 55.40 and 67.04 in the DRASTIC and the GODS models.
Asghar Asgari Moghaddam; Ataollah Nadiri; Vahid Pakniya
Volume 3, Issue 8 , December 2016, , Pages 21-52
Abstract
Received: 2015.06.08 Accepted: 2016.10.29 Asghar Asghari Moghaddam[1]* Ataollah Nadiri[2] Vahid Pakniya[3] Abstract Bostan Abad plain is located in East Azerbaijan province, North West of Iran. Groundwater resources of the plain supply significant portion of the drinking and agricultural water demands ...
Read More
Received: 2015.06.08 Accepted: 2016.10.29 Asghar Asghari Moghaddam[1]* Ataollah Nadiri[2] Vahid Pakniya[3] Abstract Bostan Abad plain is located in East Azerbaijan province, North West of Iran. Groundwater resources of the plain supply significant portion of the drinking and agricultural water demands of the area, as a result, protection of these resources from contamination is an important task. Therefore, for assessing of the aquifer vulnerability, DRASTIC and SINTACS models were used in GIS software setting. The plain vulnerability maps for each model, according to data layers including depth of water table, net recharge rate, aquifer media, soil media, topography, VA-dose zone media and hydraulic conductivity were prepared. The final map of aquifer vulnerability with five zone of vulnerability from very low to high is produced. DRASTIC and SINTACS index were calculated from 61 to188 and 92 to 202 respectively. The sensitivity analysis was determined by a single parameter that the vadose zone media has the most significant impact on the vulnerability index. The distribution of nitrate ions concentrations were used for the models verification. The adaptation nitrate layer and zoning map of vulnerability for both models showed that the areas with high concentration of nitrates are coincided with high potential vulnerability areas. The correlation coefficient of 0.75 between DRASTIC model and nitrate layer were obtained. For preparing the contamination risk map of groundwater, the land use layer was overlapped to DRASTIC vulnerability map. The results of overlapping maps showed that 31.33 percent of the total area of land used for agriculture is high potential vulnerable area. According to the final maps of vulnerability for both models the central and northwestern parts of the plain contains the highest contamination potential in the area. [1]- Professor, Dept. of Earth Science, University of Tabriz (Corresponding Autor), Email:moghaddam@tabrizu.ac.ir. [2]- Assistant Prof, Dept. of Earth Science, University of Tabriz. [3]- M.Sc student, Dept. of Earth Science, University of Tabriz.
