Assessing Pollution Risk in Ardabil Aquifer
Groundwater of Iran with Arsenic and Nitrate
Using the SINTACS Model

Dizaji, Alireza Razavi; Hosseini, Seyed Abbas; Rezaverdinejad, Vahid; Sharafati, Ahmad

doi:10.15244/pjoes/112903

Cited by 14 publications

(4 citation statements)

References 28 publications

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“…It also underscores the ongoing need for monitoring and evaluation to secure water supplies and inform effective conservation policies. In the semi-arid region of Rajasthan, the methods of DRASTIC, SINTACS, and their modified models by using LULC and temperature are used to assess the groundwater's susceptibility to contamination [16,41,43]. According to the features of the location, the results appear to be practical and satisfactory.…”

Section: Discussionmentioning

confidence: 99%

“…The initial seven factors used to assess the inherent vulnerability of aquifer systems were used to create the name SINTACS [40,41]. The SINTACS vulnerability index is computed using the symbols listed below.…”

Section: Sintacs Vulnerability Indexmentioning

confidence: 99%

“…The SINTACS index number is calculated by multiplying each parameter by weight and averaging the results. Each characteristic is rated between 1 and 10, with a score of 10 indicating a high level of pollution potential [39,41,42].…”

Section: Sintacs Vulnerability Indexmentioning

confidence: 99%

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Integrated Multi-Model Approach for Assessing Groundwater Vulnerability in Rajasthan’s Semi-Arid Zone: Incorporating DRASTIC and SINTACS Variants

Narisetty,

Tripathi,

Kanga

et al. 2023

Hydrology

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Groundwater pollution in Rajasthan, India, poses significant challenges due to the region’s heavy reliance on this resource for drinking and irrigation. Given the increasing water scarcity and overexploitation, this study assesses the susceptibility of groundwater pollution in this semi-arid area. We applied and compared vulnerability mapping methods, DRASTIC and SINTACS, and their modified versions. These methodologies considered various geological and environmental factors such as depth-to-water table, recharge, aquifer conductivity, soil, and topography. The modified versions also integrated land use and temperature data for enhanced sensitivity. Validation was achieved by comparing contaminant data from the Central Ground Water Board (CGWB), India, focusing on primary contaminants such as fluoride, nitrate, chloride, and total dissolved solids (TDS). The results strongly align with the modified methodologies and observed groundwater ion values. Specifically, more than half of the 300 sample points analyzed indicated TDS values exceeding the permissible 300 ppm limit, with over 80 points surpassing 500 ppm. The vulnerability was classified into the following five categories: very low; low; medium; high; and very high. Notably, 30.53% of the area displayed “very high” vulnerability under the modified DRASTIC model. Districts like Jalore, Pali, Sirohi, and Jodhpur emerged as highly vulnerable zones, while areas within Udaipur, Kota, and Jaipur, among others, showed very high vulnerability. This research highlights the importance of conducting groundwater vulnerability assessments, especially for regions grappling with water scarcity like Rajasthan. The findings from this research are pivotal in guiding sustainable ground water resource management, as well as advocating continual monitoring and effective groundwater conservation strategies in the region.

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Section: Discussionmentioning

confidence: 99%

Section: Sintacs Vulnerability Indexmentioning

confidence: 99%

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Integrated Multi-Model Approach for Assessing Groundwater Vulnerability in Rajasthan’s Semi-Arid Zone: Incorporating DRASTIC and SINTACS Variants

Narisetty,

Tripathi,

Kanga

et al. 2023

Hydrology

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“…Another important indicator for nitrate flow or leaching is the content of soil sand (Duffková et al, 2019). Additionally, it is suggested that in the deep layers of the soil, there is a greater accumulation of nitrates in the middle slopes, since the nitrate ion tends to be trapped there (Yang et al, 2020) (Razavi Dizaji et al, 2020. The slope is generally considered an important variable in explaining contamination by various substances in groundwater, including nutrients (Ouedraogo, Defourny and Vanclooster, 2019).…”

Section: Introductionmentioning

confidence: 99%

Effect of the Ground Slope and Soil Infiltration on the Water Nitrate Ion Concentrations

Ceferino¹,

Restrepo²,

Ramírez³

2021

reveia

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Soil characterization plays an essential role in the water flow and availability of nutrients. In accordance with the above, this research sought to find a relationship between the soil slope, soil particle grain size distribution, infiltration rate, and the nitrate ion movement through the soil profile and in the water table of the Quebrada La Nitrera, located in a Colombian tropical nature forest reserve. It was observed that the slope and the rate of infiltration explain the nitrate concentrations from one site to another. Additionally, in April 2018, where on average there is more precipitation for the study area, the highest groundwater nitrate ions concentration (18 mg / L) was reported according to the standard value for natural waters (10 mg / L). This suggests that hydrological events also influence the transport of these minerals.

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Prediction of dissolved oxygen, biochemical oxygen demand, and chemical oxygen demand using hydrometeorological variables: case study of Selangor River, Malaysia

Salih

Alakili

Beyaztaş

et al. 2020

Environ Dev Sustain

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In this research, three water quality (WQ) indexes, namely dissolved oxygen (DO), biochemical oxygen demand (BOD), and chemical oxygen demand (COD), in Selangor River of peninsular Malaysia were simulated using a stochastic model based on vector autoregression (VAR). The simulation was adopted based on three modeling scenarios of inputs as predictor: (i) related WQ parameters, (ii) WQ parameters and river flow data, and (iii) WQ parameters and rainfall data. The WQ parameters as input were determined based on the correlation analysis. The numerical analyses revealed that the prediction accuracy of VAR model substantially increases with the increase in input number. The model provided better accuracy in predictions of WQ indexes (root mean square error ≈ 0.11 and mean absolute error ≈ 0.26) when all environmental, hydrological, and climatological variables were considered. Further improvement in model performance (root mean square error ≈ 0.0248 and mean absolute error ≈ 0.1259) can be achieved if physiochemical parameters like suspended solid material and the turbidity are used as additional inputs.

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Assessing Pollution Risk in Ardabil Aquifer Groundwater of Iran with Arsenic and Nitrate Using the SINTACS Model

Cited by 14 publications

References 28 publications

Integrated Multi-Model Approach for Assessing Groundwater Vulnerability in Rajasthan’s Semi-Arid Zone: Incorporating DRASTIC and SINTACS Variants

Integrated Multi-Model Approach for Assessing Groundwater Vulnerability in Rajasthan’s Semi-Arid Zone: Incorporating DRASTIC and SINTACS Variants

Effect of the Ground Slope and Soil Infiltration on the Water Nitrate Ion Concentrations

Prediction of dissolved oxygen, biochemical oxygen demand, and chemical oxygen demand using hydrometeorological variables: case study of Selangor River, Malaysia

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