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Zaeri, A., Mohammadi, Z., & Rezanezhad, F. (2023). Determining the source and mechanism of river salinity: An integrated regional study. Journal of Hydrology: Regional Studies, 47, 101411.
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YI, Z. -ji, LIAN, B., YANG, Y. -qun, & ZOU, J. -ling. (2009). Treatment of simulated wastewater from in situ leaching uranium mining by zerovalent iron and sulfate reducing bacteria. Transactions of Nonferrous Metals Society of China, 19, 840.
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Yabusaki, S. B., Fang, Y., Long, P. E., Resch, C. T., Peacock, A. D., Komlos, J., et al. (2007). Uranium removal from groundwater via in situ biostimulation: Field-scale modeling of transport and biological processes. Journal of Contaminant Hydrology, 93(1), 216–235.
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Xu, W. D., Burns, M. J., Cherqui, F., Duchesne, S., Pelletier, G., & Fletcher, T. D. (2022). Real-time controlled rainwater harvesting systems can improve the performance of stormwater networks. Journal of Hydrology, 614, 128503.
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Xie, T., Lian, B., Chen, C., Qian, T., Liu, X., Shang, Z., et al. (2023). Leaching behaviour and mechanism of U, 226Ra and 210Pb from uranium tailings at different pH conditions. Journal of Environmental Radioactivity, 270, 107300.
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Xiao, L., Robinson, M., & O’Connor, M. (2022). Woodland’s role in natural flood management: Evidence from catchment studies in Britain and Ireland. Science of The Total Environment, 813, 151877.
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Wilson, G. B., & McNeill, G. W. (1997). Noble gas recharge temperatures and the excess air component. Applied Geochemistry, 12(6), 747–762.
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Weerahewa, J., Timsina, J., Wickramasinghe, C., Mimasha, S., Dayananda, D., & Puspakumara, G. (2023). Ancient irrigation systems in Asia and Africa: Typologies, degradation and ecosystem services. Agricultural Systems, 205, 103580.
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Wang, W., Liang, X., Niu, Q., Wang, Q., Zhuo, J., Su, X., et al. (2023). Reformability evaluation of blasting-enhanced permeability in in situ leaching mining of low-permeability sandstone-type uranium deposits. Nuclear Engineering and Technology, 55(8), 2773–2784.
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Wang, B., Luo, Y., Qian, J. -zhong, Liu, J. -hui, Li, X., Zhang, Y. -hong, et al. (2023). Machine learning–based optimal design of the in-situ leaching process parameter (ISLPP) for the acid in-situ leaching of uranium. Journal of Hydrology, 626, 130234.
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