Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Dec 12;5(1):366-376.
doi: 10.1021/acsestwater.4c00891. eCollection 2025 Jan 10.

Application of the DRASTIC Model to Assess the Vulnerability of Groundwater Contamination Near Zaporizhzhia Nuclear Power Plant, Ukraine

Affiliations

Application of the DRASTIC Model to Assess the Vulnerability of Groundwater Contamination Near Zaporizhzhia Nuclear Power Plant, Ukraine

E W Slessarev et al. ACS ES T Water. .

Abstract

Russia's invasion of Ukraine continues to have a devastating effect on the well-being of Ukrainians and their environment. We evaluated a major environmental hazard caused by the war: the potential for groundwater contamination in proximity to the Zaporizhzhia Nuclear Power Plant (NPP). We quantified groundwater vulnerability with the DRASTIC index, which was originally developed by the United States Environmental Protection Agency and has been used at various locations worldwide to assess relative pollution potential. We found that there are two major gradients of groundwater vulnerability in the region: (1) broadly higher risk to the northeast of the NPP and lower risk to the southeast driven by a regional gradient in water availability and water table depth; and (2) higher risk in proximity to the channels and floodplains of the Dnipro River and tributaries, which host coarser-textured soils and sedimentary deposits. We also found that the DRASTIC vulnerability index can be used to identify and prioritize groundwater well-network monitoring. These and more detailed assessments will be necessary to prioritize monitoring and remediation strategies across Ukraine in the event of a nuclear accident, and more broadly demonstrate the utility of the DRASTIC approach for prognostic contamination risk assessment.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing financial interest.

Figures

Figure 1
Figure 1
Map of Ukraine showing its nuclear power plants and the study area of 40,000 km2 (shown by a dashed line) around the Zaporizhzhia NPP. Number of circles indicate the number of reactors. The acronym VVER denotes water–water energetic reactor type. Locations of NPPs were obtained from the World Nuclear Association.
Figure 2
Figure 2
An illustration of calculations of GIS-based DRASTIC vulnerability index mapping process. Adapted from Ramakrishna et al. (2020).
Figure 3
Figure 3
Map showing the 40,000 km2 study area in Ukraine with a yellow star showing the location of the Zaporizhzhia NPP. The aerial map is from Google Satellite Imagery (Map data ©2024 Google).
Figure 4
Figure 4
(A) Map of the study area showing groundwater monitoring wells from a series of historical hydrogeology maps, (B) well data extrapolated to estimate regional water table depths, and (C) the water table depth converted to DRASTIC water table rating using Table S4.
Figure 5
Figure 5
(A) TerraClimate water balance model runoff estimate for the Zaporizhzhia NPP region, which we assume approximates recharge and (B) the associated DRASTIC rating for the Recharge parameter following Table S5.
Figure 6
Figure 6
(A) Digitized lithological map of study area, (B) an aquifer media map derived from (A) denoting Sand and Gravel (“SG”; distinguished by grain size in parentheses) and Weathered Metamorphic/Igneous (“WMI”) material, and (C) DRASTIC aquifer media ratings following Table S6.
Figure 7
Figure 7
(A) Digitized soil map of study area for use in the DRASTIC model. Mapped taxonomy units correspond to labeled, colored polygons (“OrChz”: Ordinary Chernozems on loess; “SoChz”: Southern Chernozems on loess; “Cht”: Chestnut soils on loess; “Sld”: Solodized soils; “Sod”: Soddy soils; “Sol”: Solonetzs; “Mix”: Mixture of meadow-Chernozemic soils on loess and meadow soils on deluvial and alluvial deposits). (B) Map of soil textures derived from symbols plotted in (A). (C) The soil texture map translated to DRASTIC soil media ratings following Table S7.
Figure 8
Figure 8
(A) An elevation map of the study area generated from JAXA ALOS (AW3D30), (B) the Digital Elevation Map (DEM) data set translated to slope, and (C) DRASTIC topography rating following Table S8.
Figure 9
Figure 9
(A) Digitized lithological map of the study area for use in the DRASTIC model (mapped lithological units defined in Section 2.3), (B) vadose zone media map derived from this map (A) denoting Silt/Clay (“SC”), Sand and Gravel (“SG”), Sand and Gravel with significant Silt/Clay (“SGwSC”) and Metamorphic/Igneous (“WMI”) material, and (C) DRASTIC vadose zone rating following Table S9.
Figure 10
Figure 10
(A) Digitized lithological map of study area produced from Perelstein (1974) and Storchak (1983) for use in the DRASTIC model (mapped lithological units defined in Section 2.3),, (B) hydraulic conductivity ranges are estimated from this map based on aquifer material and the relationships presented in Table S10 and originally contained in Freeze and Cherry (1979, their Table 2.2), and (C) DRASTIC hydraulic conductivity ratings following Table S11.
Figure 11
Figure 11
(A) DRASTIC vulnerability index for the 40,000 km2 region centered on the Zaporizhzhia NPP. The vulnerability index is calculated from multiple hydrogeologic factors and conditions (eq 1) and the network of groundwater wells spatially encompassed by the analysis. (B) A histogram summarizing the relative extent to which these wells are vulnerable to contamination, which is determined by binning the range of DRASTIC indices into “Low risk” (<100), “Intermediate risk” (101–160), and “High risk” (>160) classes following Liggett and Gilchrist (2010).

Similar articles

References

    1. Hryhorczuk D.; Levy B. S.; Prodanchuk M.; Kravchuk O.; Bubalo N.; Hryhorczuk A.; Erickson T. B. The Environmental Health Impacts of Russia’s War on Ukraine. J. Occup Med. Toxicol. 2024, 19 (1), 1.10.1186/s12995-023-00398-y. - DOI - PMC - PubMed
    1. Groundwater Vulnerability: Chernobyl Nuclear Disaster, Faybishenko B.; Nicholson T., Eds.; Special Publications; AGU, American Geophysical Union: Washington, D.C, 2015.
    1. Zheleznyak M.; Donchyts G.; Maderich V.; Dronova I.; Tkalich P.; Trybushnyi D.; Faybishenko B.; Dvorzhak A. Ecological Footprint of Russia’s Ukraine Invasion. Science 2022, 377 (6612), 1273–1273. 10.1126/science.ade6869. - DOI - PubMed
    1. Aller L.; Bennet T.; Lehr J. H.; Petty R. J.; Hackett G.. DRASTIC: A Standardized System for Evaluating Ground Water Pollution Potential Using Hydrogeologic Settings; EPA US, 1987.
    1. Prokip A.Why the Zaporizhzhia Nuclear Power Plant Matters for the Whole World; Woodrow Wilson International Center for Scholars, 2022. https://www.wilsoncenter.org/blog-post/why-zaporizhzhia-nuclear-power-pl.... accessed 2024 March 17.