Evaluation of water quality of Chahnimeh as natural reservoirs from Sistan region in southwestern Iran: a Monte Carlo simulation and Sobol sensitivity assessment

Environ Sci Pollut Res Int. 2023 May;30(24):65618-65630. doi: 10.1007/s11356-023-26879-5. Epub 2023 Apr 22.

Abstract

Maintaining the water quality is essential because of the limitation of drinking water bodies and their significant effects on life. Recently, much scientific interest has been attracted to the ecological condition assessment of water resources. Because of numerous health issues connected to water quality, the present work aimed to define the water quality status of Chahnimeh reservoirs, Sistan and Baluchistan province, Iran via the Iran Water Quality Index (IRWQISC), the National Sanitation Foundation Water Quality Index (NSFWQI), and human risk assessment. This cross-sectional descriptive work was accomplished in 4 seasons in 2020. The samples were gathered from 5 various points of Chahnimeh reservoirs. This study led to the results that the NSFWQI index was between 29.4 to 49.32, which showed "bad" quality, and the IRWQI index was between 19.27 and 39.23, which indicated "bad" and "relatively bad" quality. The best water quality based on both indexes was observed in the spring, and the worst was in the fall and summer. The highest value of HQ related to nitrate in drinking water was 1.60 in the group of children. However, according to the Monte Carlo simulation, HQ95% was estimated as 1.29. The Sobol sensitivity analysis of the first-order effect showed that daily water's daily ingestion rate (IR) was the most sensitive input. In addition, the value of the second-order effect indicated that the interaction effect of concentration-ingestion rate was the most sensitive input parameter for HQ. Therefore, regular monitoring is necessary to ensure water safety for human consumption.

Keywords: Chahnimeh reservoirs; Natural reservoirs; Nitrate, Monte Carlo, Sobol sensitivity analysis; Water quality.

MeSH terms

  • Child
  • Cross-Sectional Studies
  • Drinking Water* / analysis
  • Environmental Monitoring / methods
  • Humans
  • Iran
  • Monte Carlo Method
  • Risk Assessment
  • Water Pollutants, Chemical* / analysis
  • Water Quality

Substances

  • Drinking Water
  • Water Pollutants, Chemical