Geostatistical Contaminant Mapping

Creating prediction maps of environmental contaminants at global and country scales. This modelling approach uses a relatively small number of observation points (e.g. measured contaminant concentrations in groundwater) to predict the occurrence of a contaminant in other areas based on statistically significant correlations with spatially continuous predictor variables, such as geology, topography, climate, land use or soil type. These variables should relate to the physical processes of contaminant accumulation and ideally cover the entire geographical area of interest at a high resolution. While examples of previous studies include arsenic and fluoride in groundwater, I am also working on modeling other contaminants in groundwater as well as food crops. These studies have generally used the methods of logistic regression or random forest to model a binary target variable such that "high" and "low" values are analysed.

Isotope mapping of groundwater vulnerability and renewal

I am currently collaborating with the International Atomic Energy Agency (IAEA) to model the radioisotope tritium in groundwater in order to map groundwater vulnerability. Maps of aquifer vulnerability help water managers protect and conserve groundwater resources by identifying areas that are particularly sensitive to contamination or over-exploitation

Trace amounts of tritium occur naturally in rainfall by an interaction of cosmic radiation in the upper atmosphere. Although global tritium levels in rainfall have since declined to low pre-bomb natural levels, sensitive analytical detection capabilities still allow us to accurately detect the isotope.

Publications

Covatti, G., Li, K. Y., Podgorski, J., Winkel, L. H., & Berg, M. (2025). Nitrate contamination in groundwater across Switzerland: Spatial prediction and data-driven assessment of anthropogenic and environmental drivers. Science of the Total Environment, 973, 179121. doi: 10.1016/j.scitotenv.2025.179121

Zhan, Y., Guo, Z., Podgorski, J., Zeng, Z., Xu, P., Peng, L., Chen, K., Wu, R., Ding, C., Andrews, C. and Babovic, V., & Zheng, C. (2025). Changes in meat consumption can improve groundwater quality. Nature Food, 1-12. doi: 10.1038/s43016-025-01188-x

Bouwman, A.F., Bärlund, I., Beusen, A.H.W., Flörke, M., Gramberger, M., Cardona, J.R., Podgorski, J., van den Roovaart, J., Grizzetti, B., Janssen, A.B.G. & Kumar, R. (2024). Multimodel and multiconstituent scenario construction for future water quality. Environmental Science & Technology Letters, 11(12), pp.1272-1280. doi: 10.1021/acs.estlett.4c00789

Mukherjee, A., Coomar, P., Sarkar, S., Johannesson, K. H., Fryar, A. E., Schreiber, M. E., Ahmed, K. M., Alam, M. A., Bhattacharya, P., Bundschuh, J., Burgess, W., Chakraborty, M., Coyte, R., Farooqi, A., Guo, H., Ijumulana, J., Jeelani, G., Mondal, D., Nordstrom, D. K., Podgorski, J., Polya, D. A., Scanlon, B. R., Shamsudduha, M., Tapia, J., & Vengosh, A. (2024). Arsenic and other geogenic contaminants in global groundwater. Nature Reviews Earth & Environment, 5(4), 312-328. doi: 10.1038/s43017-024-00519-z

Podgorski, J., Kracht, O., Araguas-Araguas, L., Terzer-Wassmuth, S., Miller, J., Straub, R., Kipfer, R., & Berg, M. (2024). Groundwater vulnerability to pollution in Africa’s Sahel region. Nature Sustainability, 7(5), 558-567. doi: 10.1038/s41893-024-01319-5

Sadiq, M., Eqani, S. A. M. A. S., Podgorski, J., Ilyas, S., Abbas, S. S., Shafqat, M. N., Nawaz, I., & Berg, M. (2024). Geochemical insights of arsenic mobilization into the aquifers of Punjab, Pakistan. Science of The Total Environment, 935, 173452. doi: 10.1016/j.scitotenv.2024.173452

Zhi, W., Appling, A. P., Golden, H. E., Podgorski, J., & Li, L. (2024). Deep learning for water quality. Nature Water, 2(3), 228-241. doi: 10.1038/s44221-024-00202-z

Araya, D., Podgorski, J., & Berg, M. (2023). Groundwater salinity in the Horn of Africa: spatial prediction modeling and estimated people at risk. Environment International, 176, 107925. doi: 10.1016/j.envint.2023.107925

Sohail, M., Eqani, S.A.M.A.S., Ilyas, S., Bokhari, H., Ali, N., Podgorski, J.E., Muhammad, S., Adelman D., & Lohmann, R. (2023). Gaseous and soil OCPs and PCBs along the Indus River, Pakistan: spatial patterns and air–soil gradients. Environmental Science: Processes & Impacts. doi: 10.1039/D2EM00363E

Ali, W., Zhang, H., Mao, K., Shafeeque, M., Aslam, M.W., Yang, X., Zhong, L., Feng, X., & Podgorski, J. (2022). Chromium contamination in paddy soil-rice systems and associated human health risks in Pakistan. Science of The Total Environment, 153910, doi: 10.1016/j.scitotenv.2022.153910

Araya, D., Podgorski, J., Kumi, M., Mainoo, P.A., & Berg, M. (2022). Fluoride contamination of groundwater resources in Ghana: Country-wide hazard modeling and estimated population at risk. Water Research, 118083, doi: 10.1016/j.watres.2022.118083

Ling, Y., Podgorski, J., Sadiq, M., Rasheed, H., Eqani, S.A.M.A.S., & Berg, M. (2022). Monitoring and prediction of high fluoride concentrations in groundwater in Pakistan. Science of The Total Environment, 156058, doi: 10.1016/j.scitotenv.2022.156058

Misstear, B., Vargas, C. R., Lapworth, D., Ouedraogo, I., & Podgorski, J. (2022). A global perspective on assessing groundwater quality. Hydrogeology Journal, 1-4, doi: 10.1007/s10040-022-02461-0

Podgorski, J., Araya, D., & Berg, M. (2022). Geogenic manganese and iron in groundwater of Southeast Asia and Bangladesh–Machine learning spatial prediction modeling and comparison with arsenic. Science of The Total Environment, 155131, doi: 10.1016/j.scitotenv.2022.155131

Podgorski, J., & Berg, M. (2022) Global analysis and prediction of fluoride in groundwater. Nature Communications, 13, 4232. doi: 10.1038/s41467-022-31940-x

Sohail, M., Eqani, S.A.M.A.S., Bokhari, H., Hashmi, M.Z., Ali, N., Alamdar, A., Podgorski, J.E., Adelman, D., & Lohmann, R. (2022). Freely dissolved organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) along the Indus River Pakistan: spatial pattern, air-water exchange and risk assessment. Environmental Science and Pollution Research, doi: 10.1007/s11356-022-20418-4

Vengosh, A., Coyte, R.M., Podgorski, J., & Johnson, T.M. (2022). A critical review on the occurrence and distribution of the uranium-and thorium-decay nuclides and their effect on the quality of groundwater. Science of The Total Environment, 808, 151914, doi: 10.1016/j.scitotenv.2021.151914

Alam, M.F., Villholth, K.G., & Podgorski, J. (2021). Human arsenic exposure risk via crop consumption and global trade from groundwater-irrigated areas. Environmental Research Letters, 16(12), 124013, doi: 10.1088/1748-9326/ac34bb

Joodavi, A., Aghlmand, R., Podgorski, J., Dehbandi, R., & Abbasi, A. (2021). Characterization, geostatistical modeling and health risk assessment of potentially toxic elements in groundwater resources of northeastern Iran. Journal of Hydrology: Regional Studies, 37, 100885, doi: 10.1016/j.ejrh.2021.100885

Wu, R., Podgorski, J., Berg, M., & Polya, D.A. (2021). Geostatistical model of the spatial distribution of arsenic in groundwaters in Gujarat State, India. Environmental Geochemistry and Health, 43(7), 2649-2664, doi: 10.1007/s10653-020-00655-7

Podgorski, J., & Berg, M. (2020). Global threat of arsenic in groundwater. Science, 368(6493), 845-850, doi: 10.1126/science.aba1510 FULL TEXT

Podgorski, J., Wu, R., Chakravorty, B., & Polya, D.A. (2020) Groundwater Arsenic Distribution in India by Machine Learning Geospatial Modeling. Int. J. Environ. Res. Public Health, 17, 7119, doi: 10.3390/ijerph17197119

Moeck, C., Grech-Cumbo, N., Podgorski, J., Bretzler, A., Gurdak, J.J., Berg, M., & Schirmer, M. (2020). A global-scale dataset of direct natural groundwater recharge rates: A review of variables, processes and relationships. Science of the Total Environment, 717, 137042, doi: 10.1016/j.scitotenv.2020.137042

Razanamahandry, L.C., Digbeu, P.M., Andrianisa, H.A., Karoui, H., Podgorski, J., Manikandan, E., Maaza, M., & Yacouba, H. (2020). Comparative methods for predicting cyanide pollution into artisanal small scale gold mining catchment by using logistic regression and kriging with GIS. African Journal of Science, Technology, Innovation and Development. doi: 10.1080/20421338.2020.1734325

Podgorski, J., Berg, M., & Kipfer, R. (2019). Isotope mapping of groundwater pollution and renewal. IAEA Bulletin, 31. PDF

Podgorski, J.E., Labhasetwar, P., Saha, D., & Berg, M. (2018). Prediction modeling and mapping of groundwater fluoride contamination throughout India. Environmental Science & Technology, 52(17), 9889–9898, doi: 10.1021/acs.est.8b01679

Razanamahandry, L.C., Andrianisa, H.A., Karoui, H., Podgorski, J., & Yacouba, H. (2018). Prediction model for cyanide soil pollution in artisanal gold mining area by using logistic regression. Catena, 162, 40-50, doi: 10.1016/j.catena.2017.11.018

Sohail, M., Eqani, S.A.M.A.S., Podgorski, J., Bhowmik, A.K., Mahmood, A., Ali, N., Sabo-Attwood, T., Bokhari, H., & Shen, H. (2018). Persistent organic pollutant emission via dust deposition throughout Pakistan: Spatial patterns, regional cycling and their implication for human health risks. Science of the Total Environment, 618, 829-837, doi: 10.1016/j.scitotenv.2017.08.224

Podgorski, J.E., Eqani, S.A.M.A.S., Khanam, T., Ullah, R., Shen, H., & Berg, M. (2017). Extensive arsenic contamination in high-pH unconfined aquifers in the Indus Valley. Science Advances, 3(8), e1700935. doi: 10.1126/sciadv.1700935

Podgorski, J.E., Kinzelbach, W.K., & Kgotlhang, L. (2017). Using helicopter TEM to delineate fresh water and salt water zones in the aquifer beneath the Okavango Delta, Botswana. Advances in Water Resources, 107, 265-279, doi: 10.1016/j.advwatres.2017.06.021

Bretzler, A., Lalanne, F., Nikiema, J., Podgorski, J., Pfenninger, N., Berg, M., & Schirmer, M. (2017). Groundwater arsenic contamination in Burkina Faso, West Africa: Predicting and verifying regions at risk. Science of the Total Environment, 584, 958-970, doi: 10.1016/j.scitotenv.2017.01.147

Podgorski, J.E., Green, A.G., Kalscheuer, T., Kinzelbach, W.K., Horstmeyer, H., Maurer, H., Rabenstein, L., Doetsch, J., Auken, E., Ngwisanyi, T., Tshoso, G., Jaba, B.C., Ntibinyane, O., & Laletsang, K. (2015). Integrated interpretation of helicopter and ground-based geophysical data recorded within the Okavango Delta, Botswana. Journal of Applied Geophysics, 114, 52-67, doi: 10.1016/j.jappgeo.2014.12.017

Kalscheuer, T., Blake, S., Podgorski, J.E., Wagner, F., Green, A.G., Maurer, H., Jones, H.G., Muller, M., & Tshoso, T. (2015). Joint inversions of three types of electromagnetic data explicitly constrained by seismic observations: results from the central Okavango Delta, Botswana. Geophysical Journal International, 202(3), 1429-1452, doi: 10.1093/gji/ggv184

Meier, P., Kalscheuer, T., Podgorski, J., Green, A., Greenhalgh, S., Rabenstein, L., Doetsch, J., Kinzelbach, W., Auken, E., Mikkelsen, P., Foged, N., Jaba, B., Tshoso, G., & Ntibinyane, O. (2014). Hydrogeophysical investigations in the western and north-central Okavango Delta (Botswana) based on helicopter and ground-based transient electromagnetic data and electrical resistance tomography, Geophysics, 79, 201-211, doi: 10.1190/geo2014-0001.1

Podgorski, J.E., Green, A.G., Kgotlhang, L., Kinzelbach, W.K.H., Kalscheuer, T., Auken, E., & Ngwisanyi, T. (2013). Paleo megalake and paleo megafan in southern Africa, Geology, 41, doi: 10.1130/G34735.1

Podgorski, J.E., Auken, E., Schamper, C., Christiansen, A.V., Kalscheuer, T., & Green, A.G. (2013). Processing and inverting commercial helicopter time-domain electromagnetic data for environmental assessments and geological and hydrological mapping, Geophysics, 78, E149-E159, doi: 10.1190/geo2012-0452.1

Reiser, F., Podgorski, J., Schmelzbach, C., Horstmeyer, H., Green, A., Kalscheuer, T., Maurer, H., Kinzelbach, W., & Gomotsang, T. (2013). Constraining helicopter electromagnetic models of the Okavango Delta with seismic-refraction and seismic-reflection data, Geophysics, 79, B123-B134, doi: 10.1190/geo2013-0278.1

Podgorski, J., Hearn, E.H., McClusky, S., Reilinger, R., Taymaz, T., Tan, O., Prilepin, M., Guseva, T., & Nadariya, M. (2007). Postseismic deformation following the 1991 Racha, Georgia, earthquake, Geophysical Research Letters, 34, L04310, doi:10.1029/2006GL028477