BACKGROUND: Aridization of the southern territory increases the concentration of toxic substances in Russia in groundwater in the long-term future.
AIM: To analyze the potential of a multi-regression climate model to predict long-term dynamics of health risks associated with the oral release of toxicants from groundwater.
METHODS: An assessment of non-carcinogenic health risk (HI) was carried out for the period 2017-2022 within the occurrence of three groundwater basins in the Volgograd Trans-Volga region. Concentrations of toxicants were analyzed in 1149 water samples at the 95th percentile. NDMI and the De Martonne Index (DMI) values were calculated. DMI inputs data was modified using LST (Land Surface Temperature) satellite analysis. In the models, HI served as the dependent variable with NDMI and DMI values used as predictors.
RESULTS: A significant contribution of chloroform to the overall risk pattern for groundwater in the Volgograd Trans-Volga region was discovered. The maximum values were recorded in the Nizhnevolzhskiygroundwater basin (HQchildren/chloroform=3.20, HQadults/chloroform=1.37) in 2017. The satellite aridity index NDMI makes the greatest contribution to the reliability of the predictive model of long-term health risk dynamics that shape the oral intake of pollutants from groundwater in the Volgograd Trans-Volga region. The lowest multiple regression value was noted for the health risk for adults (ry,x1,x2=-0.909, p=0.012) in the Severo-Prikaspiyskiy basin, the maximum was recorded in Ryn-Peskovsky basin for children (ry,x1,x2=-0.992, p= 0.002) ). The De Martonne climate index provides insignificant reliability in predicting long-term dynamics of non-carcinogenic health risks associated with toxicants circulating in arid ecosystems of the South of Russia - the largest contribution of this predictor for the health risk of children in the Ryn-Peskovsky basin (rx2/x1=-0.554, p=0.105).
CONCLUSION: A potential of NDMI integration in the social and hygienic quality monitoring of underground water arid zones of southern Russia has been identified. The high resolution and sensitivity to water quantity in steppe vegetation confirms the accuracy of the NDMI indicator for arid topography.