Nutrients loads in aquatic systems are dynamic and highly influenced by changing the land, soil, and atmospheric conditions. This study enhances water quality modeling by providing novel nitrate transport models using remotely-sensed geospatial data, allowing for dynamic predictions of nitrate loads in watersheds. One factor at a time, sensitivity analysis was employed in the classical nitrate transport model to incorporate the impacts of 1) nitrates in the soil moisture profiles 2) wet deposition of nitrates and 3) the synergistic effects of multiple atmospheric and soil effects on nitrate-nitrogen in catchments. The study found that the effects of soil moisture profiles were dominant than the wet deposition in the evaluation of nitrate-nitrogen in catchments. The addition of nitrates from soil moisture profile, wet deposition and both together effectively increased the annual average nitrates in the Fish River catchment from 0.180 kg/ha to 0.187 kg/ha, 0.396 kg/ha and 0.381 kg/ha respectively. Their additions consistently increased the nitrate loads from spring to winter seasons but exhibited different seasonal trends for soils such as silty sand and fine sand. The models developed in this study can be utilized in water quality assessment tools for effective dynamic predictions of nutrients loads into water bodies.

Climate change continues to exacerbate water scarcity by altering global weather patterns and intensifying extreme climatic events. This review examines the potential of atmospheric water generation technologies to mitigate water scarcity under such conditions. By leveraging a multidisciplinary approach, we review advancements in fog harvesting, sorption-based systems, membrane technologies, radiative sky cooling, and cloud seeding. A special emphasis is placed on passive systems utilizing renewable energy to address challenges of high energy demands. Predictive tools such as machine learning, climate models, and geographic information systems are explored to optimize atmospheric water generation deployment under shifting climatic conditions. This review article outlines critical innovations in materials, economic considerations, and policy frameworks required for atmospheric water generation to transition from niche to mainstream water solutions. These findings aim to inform sustainable strategies for tackling water scarcity in the context of global climate challenges.

This study implemented a coupled SWAT-FEM simulation model to evaluate the impacts of land use land cover and climate change scenarios (LCS) on the water resources of river catchments in Chennai, India. The land use land cover data were obtained by merging the source data from National Remote Sensing Centre (NRSC) and International Water Management Institute (IWMI). Climate change simulations were obtained from four global climate models (GCM), including GFDL Baseline Scenario (1981–2000), GFDL A1B Scenario (2081–2100), CCSM4 Baseline Scenario (1986–2005), and CCSM4 A1B Scenario (2081–2100). The LCS predicted temperature increases of 2.32 °C and 1.74 °C for GFDL and CCSM4, respectively, by the end of the century. The water use predictions suggested increases above 20% in the utilization of water by 2100, inferring the noticeable dynamics of inter-annual as well as inter-month variability in water resources in the river basins of Chennai soon. The study is novel through its implementation of a coupled modeling approach to improve the practicality of the SWAT-FEM model and to deliver useful projections of land and climate change impacts on hydrological responses. The results provide useful insights into how the variability in climate conditions alters the spatiotemporal water responses in catchment scales.