References
Abdolrasol, M. G., Hussain, S. S., Ustun, T. S., Sarker, M. R., Hannan, M. A., Mohamed, R., Ali, J. A., Mekhilef, S., and Milad, A. (2021). Artificial neural networks based optimization techniques: A review. Electronics, 10(21), 2689. Adams, K. H., Reager, J. T., Rosen, P., Wiese, D. N., Farr, T. G., Rao, S., Haines, B. J., Argus, D. F., Liu, Z., and Smith, R. (2022). Remote sensing of groundwater: current capabilities and future directions. Water Resources Research, 58(10), e2022WR032219. Aderemi, B. A., Olwal, T. O., Ndambuki, J. M., and Rwanga, S. S. (2021). A review of groundwater management models with a focus on IoT-based systems. Sustainability, 14(1), 148. Al-Hashimi, O., Hashim, K., Loffill, E., Marolt ?ebašek, T., Nakouti, I., Faisal, A. A., and Al- Ansari, N. (2021). A comprehensive review for groundwater contamination and remediation: occurrence, migration and adsorption modelling. Molecules, 26(19), 5913. Al-Kaabi, A. (2021). Improving the Environmental Footprint of SWRO through Intake and Pretreatment Optimization Hamad Bin Khalifa University (Qatar)]. Al Atawneh, D., Cartwright, N., and Bertone, E. (2021). Climate change and its impact on the projected values of groundwater recharge: A review. Journal of Hydrology, 601, Alam, S., Borthakur, A., Ravi, S., Gebremichael, M., and Mohanty, S. K. (2021). Managed aquifer recharge implementation criteria to achieve water sustainability. Science of the Total Environment, 768, 144992. Ali, A. S. A., Jazaei, F., Babakhani, P., Ashiq, M. M., Bakhshaee, A., and Waldron, B. (2024). An Overview of Deep Learning Applications in Groundwater Level Modeling: Bridging the Gap between Academic Research and Industry Applications. Applied Computational Intelligence and Soft Computing, 2024(1), 9480522. Alizadeh, R., Allen, J. K., and Mistree, F. (2020). Managing computational complexity using surrogate models: a critical review. Research in Engineering Design, 31(3), 275-298. Allafta, H., Opp, C., and Patra, S. (2020). Identification of groundwater potential zones using remote sensing and GIS techniques: a case study of the Shatt Al-Arab Basin. Remote Sensing, 13(1), 112. Amanambu, A. C., Obarein, O. A., Mossa, J., Li, L., Ayeni, S. S., Balogun, O., Oyebamiji, A., and Ochege, F. U. (2020). Groundwater system and climate change: Present status and future considerations. Journal of Hydrology, 589, 125163. Ansarifar, M.-M., Salarijazi, M., Ghorbani, K., and Kaboli, A.-R. (2020). Simulation of groundwater level in a coastal aquifer. Marine Georesources & Geotechnology, 38(3), 257-265. Antonakos, A., and Lambrakis, N. (2021). Spatial interpolation for the distribution of groundwater level in an area of complex geology using widely available GIS tools. Environmental Processes, 8, 993-1026. Arnold, J. G., Youssef, M. A., Yen, H., White, M. J., Sheshukov, A. Y., Sadeghi, A. M., Moriasi, D. N., Steiner, J. L., Amatya, D. M., and Skaggs, R. W. (2015). Hydrological processes and model representation: impact of soft data on calibration. Transactions of the ASABE, 58(6), 1637-1660. Arun Kumar, K. C., Obi Reddy, G. P., Masilamani, P., and Sandeep, P. (2021). Spatial modelling for identification of groundwater potential zones in semi-arid ecosystem of southern India using Sentinel-2 data, GIS and bivariate statistical models. Arabian Journal of Geosciences, 14, 1-14. Asher, M. J., Croke, B. F., Jakeman, A. J., and Peeters, L. J. (2015). A review of surrogate models and their application to groundwater modeling. Water Resources Research, 51(8), 5957-5973. Aslam, R. A., Shrestha, S., Usman, M. N., Khan, S. N., Ali, S., Sharif, M. S., Sarwar, M. W., Saddique, N., Sarwar, A., and Ali, M. U. (2022). Integrated SWAT-MODFLOW modeling-based groundwater adaptation policy guidelines for lahore, Pakistan under projected climate change, and human development scenarios. Atmosphere, 13(12), Bachmann, N., Tripathi, S., Brunner, M., and Jodlbauer, H. (2022). The contribution of data- driven technologies in achieving the sustainable development goals. Sustainability, 14(5), 2497. Badham, J., Elsawah, S., Guillaume, J. H., Hamilton, S. H., Hunt, R. J., Jakeman, A. J., Pierce, S. A., Snow, V. O., Babbar-Sebens, M., and Fu, B. (2019). Effective modeling for Integrated Water Resource Management: A guide to contextual practices by phases and steps and future opportunities. Environmental Modelling & Software, 116, 40-56. Bansal, M. A., Sharma, D. R., and Kathuria, D. M. (2022). A systematic review on data scarcity problem in deep learning: solution and applications. ACM computing surveys (CSUR), 54(10s), 1-29. Bansal, S., Sindhi, V., and Singla, B. S. (2024). Future Directions and Innovations in Computational Water Management. In Integrated Management of Water Resources in India: A Computational Approach: Optimizing for Sustainability and Planning (pp. 473-492). Springer. Basack, S., Loganathan, M., Goswami, G., and Khabbaz, H. (2022). Saltwater intrusion into coastal aquifers and associated risk management: Critical review and research directives. Journal of Coastal Research, 38(3), 654-672. Becker, B., Reichel, F., Bachmann, D., and Schinke, R. (2022). High groundwater levels: Processes, consequences, and management. Wiley Interdisciplinary Reviews: Water, 9(5), e1605. Bedi, S., Samal, A., Ray, C., and Snow, D. (2020). Comparative evaluation of machine learning models for groundwater quality assessment. Environmental Monitoring and Assessment, 192, 1-23. Braune, E., and Xu, Y. (2010). The role of ground water in Sub?Saharan Africa. Groundwater, 48(2), 229-238. Brown, C. M., Lund, J. R., Cai, X., Reed, P. M., Zagona, E. A., Ostfeld, A., Hall, J., Characklis, G. W., Yu, W., and Brekke, L. (2015). The future of water resources systems analysis: Toward a scientific framework for sustainable water management. Water Resources Research, 51(8), 6110-6124. Brunner, P., Hendricks Franssen, H.-J., Kgotlhang, L., Bauer-Gottwein, P., and Kinzelbach, W. (2007). How can remote sensing contribute in groundwater modeling? Hydrogeology Journal, 15, 5-18. Cao, G., Zheng, C., Scanlon, B. R., Liu, J., and Li, W. (2013). Use of flow modeling to assess sustainability of groundwater resources in the North China Plain. Water Resources Research, 49(1), 159-175. Carlson, T., and Cohen, A. (2018). Linking community-based monitoring to water policy: Perceptions of citizen scientists. Journal of Environmental Management, 219, 168-177. Carothers, C., Ferscha, A., Fujimoto, R., Jefferson, D., Loper, M., Marathe, M., Mosterman, P., Taylor, S. J., and Vakilzadian, H. (2017). Computational challenges in modeling and simulation. Research Challenges in Modeling and Simulation for Engineering Complex Systems, 45-74. Castilla-Rho, J. C., Mariethoz, G., Rojas, R., Andersen, M. S., and Kelly, B. F. (2015). An agent-based platform for simulating complex human–aquifer interactions in managed groundwater systems. Environmental Modelling & Software, 73, 305-323. Chen, M., Izady, A., Abdalla, O. A., and Amerjeed, M. (2018). A surrogate-based sensitivity quantification and Bayesian inversion of a regional groundwater flow model. Journal of Hydrology, 557, 826-837. Chopra, A., Pathak, C., and Prasad, G. (2009). Scenario of heavy metal contamination in agricultural soil and its management. Journal of Applied and Natural Science, 1(1), 99- Chowdhury, A., Jlia, M., and Machinal, D. (2003). Application of remote sensing and GIS in groundwater studies: an overview. Ground water pollution: proceedings of the international conference on water and environment (WE-2003), Chuenchum, P., Meneesrikum, C., Teerapanuchaikul, C., and Sriariyawat, A. (2024). Community participation and effective water management: A study on water user organizations (WUOs)