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Geostatistical model of the spatial distribution of arsenic in groundwaters in Gujarat State, India
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, 2649-2664. https://doi.org/10.1007/s10653-020-00655-7
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
Adaption to climate change: a case study of two agricultural systems from Kenya
Stefanovic, J. O., Yang, H., Zhou, Y., Kamali, B., & Ogalleh, S. A. (2017). Adaption to climate change: a case study of two agricultural systems from Kenya. Climate and Development, 11(4), 319-337. https://doi.org/10.1080/17565529.2017.1411241
Coupling predicted model of arsenic in groundwater with endemic arsenism occurrence in Shanxi Province, Northern China
Zhang, Q., Rodriguez-Lado, L., Liu, J., Johnson, C. A., Zheng, Q., & Sun, G. (2013). Coupling predicted model of arsenic in groundwater with endemic arsenism occurrence in Shanxi Province, Northern China. Journal of Hazardous Materials, 262, 1147-1153. https://doi.org/10.1016/j.jhazmat.2013.02.017
Use of qualitative environmental and phenotypic variables in the context of allele distribution models: detecting signatures of selection in the genome of Lake Victoria cichlids
Joost, S., Kalbermatten, M., Bezault, E., & Seehausen, O. (2012). Use of qualitative environmental and phenotypic variables in the context of allele distribution models: detecting signatures of selection in the genome of Lake Victoria cichlids. In F. Pompanon & A. Bonin (Eds.), Methods in molecular biology: Vol. 888. Data production and analysis in population genomics. Methods and protocols (pp. 295-314). https://doi.org/10.1007/978-1-61779-870-2_17
Predicting the risk of arsenic contaminated groundwater in Shanxi Province, Northern China
Zhang, Q., Rodríguez-Lado, L., Johnson, C. A., Xue, H., Shi, J., Zheng, Q., & Sun, G. (2012). Predicting the risk of arsenic contaminated groundwater in Shanxi Province, Northern China. Environmental Pollution, 165, 118-123. https://doi.org/10.1016/j.envpol.2012.02.020
A comparison of different rule-based statistical models for modeling geogenic groundwater contamination
Amini, M., Abbaspour, K. C., & Johnson, C. A. (2010). A comparison of different rule-based statistical models for modeling geogenic groundwater contamination. Environmental Modelling and Software, 25(12), 1650-1657. https://doi.org/10.1016/j.envsoft.2010.05.014
Modeling large scale geogenic contamination of groundwater, combination of geochemical expertise and statistical techniques
Amini, M., Johnson, A., Abbaspour, K. C., & Mueller, K. (2009). Modeling large scale geogenic contamination of groundwater, combination of geochemical expertise and statistical techniques. R. S. Anderssen, R. D. Braddock, & L. T. H. Newham (Eds.) (pp. 4100-4106). Presented at the 18th world IMACS / MODSIM congress. .
Large wood dynamics of complex Alpine river floodplains
van der Nat, D., Tockner, K., Edwards, P. J., & Ward, J. V. (2003). Large wood dynamics of complex Alpine river floodplains. Journal of the North American Benthological Society, 22(1), 35-50. https://doi.org/10.2307/1467976