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A global-scale dataset of direct natural groundwater recharge rates: a review of variables, processes and relationships
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 (19 pp.). https://doi.org/10.1016/j.scitotenv.2020.137042
Global threat of arsenic in groundwater
Podgorski, J., & Berg, M. (2020). Global threat of arsenic in groundwater. Science, 368(6493), 845-850. https://doi.org/10.1126/science.aba1510
Groundwater arsenic distribution in India by machine learning geospatial modeling
Podgorski, J., Wu, R., Chakravorty, B., & Polya, D. A. (2020). Groundwater arsenic distribution in India by machine learning geospatial modeling. International Journal of Environmental Research and Public Health, 17(19), 7119 (17 pp.). https://doi.org/10.3390/ijerph17197119
Comparative methods for predicting cyanide pollution in artisanal small-scale gold mining catchment by using logistic regression and kriging with GIS
Razanamahandry, L. C., Digbeu, P. M., Andrianisa, H. A., Karoui, H., Podgorski, J., Manikandan, E., … Yacouba, H. (2020). Comparative methods for predicting cyanide pollution in artisanal small-scale gold mining catchment by using logistic regression and kriging with GIS. African Journal of Science, Technology, Innovation and Development, 12(3), 287-295. https://doi.org/10.1080/20421338.2020.1734325
Geostatistical model of the spatial distribution of arsenic in groundwaters in Gujarat State, India
Wu, R., Podgorski, J., Berg, M., & Polya, D. A. (2020). Geostatistical model of the spatial distribution of arsenic in groundwaters in Gujarat State, India. Environmental Geochemistry and Health. https://doi.org/10.1007/s10653-020-00655-7
Groundwater Assessment Platform (GAP): a new GIS tool for risk forecasting and mitigation of geogenic groundwater contamination
Berg, M., & Podgorski, J. E. (2019). Groundwater Assessment Platform (GAP): a new GIS tool for risk forecasting and mitigation of geogenic groundwater contamination. In Y. G. Zhu, H. Guo, P. Bhattacharya, J. Bundschuh, A. Ahmad, & R. Naidu (Eds.), Arsenic in the environment - proceedings. Environmental arsenic in a changing world (pp. 5-6). https://doi.org/10.1201/9781351046633-2
Effect of arsenic risk assessment in Pakistan on mitigation action
Podgorski, J. E., Eqani, S. A. M. A. S., & Berg, M. (2019). Effect of arsenic risk assessment in Pakistan on mitigation action. In Y. G. Zhu, H. Guo, P. Bhattacharya, J. Bundschuh, A. Ahmad, & R. Naidu (Eds.), Arsenic in the environment - proceedings. Environmental arsenic in a changing world (pp. 541-542). https://doi.org/10.1201/9781351046633-211
Isotope mapping of groundwater pollution and renewal
Podgorski, J., Berg, M., & Kipfer, R. (2019). Isotope mapping of groundwater pollution and renewal. IAEA Bulletin, 60(1), 31-32.
Prediction modeling and mapping of groundwater fluoride contamination throughout India
Podgorski, J. E., Labhasetwar, P., Saha, D., & Berg, M. (2018). Prediction modeling and mapping of groundwater fluoride contamination throughout India. Environmental Science and Technology, 52(17), 9889-9898. https://doi.org/10.1021/acs.est.8b01679
Prediction model for cyanide soil pollution in artisanal gold mining area by using logistic regression
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. https://doi.org/10.1016/j.catena.2017.11.018
Persistent organic pollutant emission via dust deposition throughout Pakistan: spatial patterns, regional cycling and their implication for human health risks
Sohail, M., Eqani, S. A. M. A. S., Podgorski, J., Bhowmik, A. K., Mahmood, A., Ali, N., … 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. https://doi.org/10.1016/j.scitotenv.2017.08.224
Modelling groundwater arsenic contamination in China with the groundwater assessment platform (GAP)
Arnheiter, R. (2017). Modelling groundwater arsenic contamination in China with the groundwater assessment platform (GAP) [Bachelor thesis].
Groundwater arsenic contamination in Burkina Faso, West Africa: predicting and verifying regions at risk
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, 584-585, 958-970. https://doi.org/10.1016/j.scitotenv.2017.01.147
Extensive arsenic contamination in high-pH unconfined aquifers in the Indus Valley
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 (10 pp.). https://doi.org/10.1126/sciadv.1700935
Using helicopter TEM to delineate fresh water and salt water zones in the aquifer beneath the Okavango Delta, Botswana
Podgorski, J. E., Kinzelbach, W. K. H., & 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. https://doi.org/10.1016/j.advwatres.2017.06.021
Joint inversions of three types of electromagnetic data explicitly constrained by seismic observations: results from the Central Okavango Delta, Botswana
Kalscheuer, T., Blake, S., Podgorski, J. E., Wagner, F., Green, A. G., Maurer, H., … Tshoso, G. (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. https://doi.org/10.1093/gji/ggv184