Current models in design of urban water management systems and their corresponding infrastructure using centralized designs have commonly failed from the perspective of cost effectiveness and inability to adapt to the future changes. These challenges are driving cities towards using decentralized systems. While there is great consensus on the benefits of decentralization; currently no methods exist which guide decision-makers to define the optimal boundaries of decentralized water systems. A new clustering methodology and tool to decentralize water supply systems (WSS) into small and adaptable units is presented. The tool includes two major components: (i) minimization of the distance from source to consumer by assigning demand to the closest water source, and (ii) maximization of the intra-cluster homogeneity by defining the cluster boundaries such that the variation in population density, land use, socio-economic level, and topography within the cluster is minimized. The methodology and tool were applied to Arua Town in Uganda. Four random cluster scenarios and a centralized system were created and compared with the optimal clustered WSS. It was observed that the operational cost of the four cluster scenarios is up to 13.9 % higher than the optimal, and the centralized system is 26.6% higher than the optimal clustered WSS, consequently verifying the efficacy of the proposed method to determine an optimal cluster boundary for WSS. In addition, optimal homogeneous clusters improve efficiency by encouraging reuse of wastewater and stormwater within a cluster and by minimizing leakage through reduced pressure variations.

Stormwater control is an urgent concern in cities where the increased impervious surface has disrupted natural hydrology, particularly causing a reduction in groundwater recharge which is the source of potable water supply for many communities. Water managers are increasingly turning towards infiltration-based stormwater management options (ISMOs) to help minimize flooding and mitigate the impact of urbanization on the local hydrologic systems. This paper offers a unique hydrologic and hydraulic (H&H) modeling approach using the Geographic Information System (GIS) and Interconnected Pond and Channel Routing (ICPR) software to help quantify the associated flood stage and groundwater recharge benefits of using ISMOs. The proposed approach incorporated ICPR percolation links and utilization of the curve number and Green-Ampt infiltration methods into the case study design, as well as an analysis of the effectiveness of including low-impact development practices. This analysis shows a 13–36% reduction in stormwater volume leaving the proposed site when percolation links were utilized to account for percolation from the proposed ISMOs. These reduction provides an indirect estimate of groundwater recharge benefits. The conversion from impervious parking to a pervious one and inclusion of rainwater harvesting from the roof area resulted in a further reduction in peak stages ranging from 1.20 to 7.62 cm.

Flooding poses a severe global threat, necessitating advanced methodologies to assess and manage its risks effectively. This study introduces a novel approach that integrates Geographic Information System (GIS) with hydrologic-hydraulic modeling to evaluate the combined drivers of current and future flood risks. The method is applied to the development Bonita Bay in southwest Florida. It occurs in a region highly susceptible to flooding due to its low elevation and proximity to tidal waters. The innovative integration of GIS with hydrologic-hydraulic models enables detailed assessment and visualization of flood inundation areas under multiple flood drivers including design storms, land use changes, groundwater rise, and sea-level rise. This allows for the seamless simulation of complex flood interactions with only minor adjustments to the model for the identified drivers. The results indicate significant increases in initial water storage caused by sea and groundwater level rise and amplified storm runoff from land use changes. A 2% increase in flooded areas is projected with stronger design storms, and a 5% increase by 2,100 compared to 2024. This approach provides a robust framework for developing tailored flood mitigation strategies and can be adapted to various coastal regions globally.

Mercury (Hg) is a toxic metal that is easily released into the atmosphere as a gas or a particulate. Since Hg has serious health impacts based on human exposure, it is a major concern where it accumulates. Southern Florida is a region of high Hg deposition in the United States. It has entered the southern Florida environment for over 56 MY. For the past 3000 to 8000 years, Hg has accumulated in the Everglades peatlands, where approximately 42.3 metric tons of Hg was deposited. The pre-industrial source of mercury that was deposited into the Everglades was from the atmosphere, consisting of combined Saharan dust and marine evasion. Drainage and the development of the Everglades for agriculture, and other mixed land uses have caused a 65.7% reduction in the quantity of peat, therefore releasing approximately 28 metric tons of Hg into the southern Florida environment over a period of approximately 133 years. Both natural and man-made fires have facilitated the Hg release. The current range in mercury release into the southern Florida environment lies between 994.9 and 1249 kg/yr. The largest source of Hg currently entering the Florida environment is from combined atmospheric sources, including Saharan dust, aerosols, sea spray, and ocean flux/evasion at 257.1–514.2 kg/yr. The remobilization of Hg from the Everglades peatlands and fires is approximately 215 kg/yr. Other large contributors include waste to energy incinerators (204.1 kg/yr), medical waste and crematory incinerators (159.7+ kg/yr), and cement plant stack discharge (150.6 kg/yr). Minor emissions include fuel emissions from motorized vehicles, gas emissions from landfills, asphalt plants, and possible others. No data are available on controlled fires in the Everglades in sugar farming, which is lumped with the overall peatland loss of Hg to the environment. Hg has impacted wildlife in southern Florida with recorded excess concentrations in fish, birds, and apex predators. This bioaccumulation of Hg in animals led to the adoption of regulations (total maximum loads) to reduce the impacts on wildlife and warnings were given to consumers to avoid the consumption of fish that are considered to be contaminated. The deposition of atmospheric Hg in southern Florida has not been studied sufficiently to ascertain where it has had the greatest impacts. Hg has been found to accumulate on willow tree leaves in a natural environment in one recent study. No significant studies of the potential impacts on human health have been conducted in southern Florida, which should be started based on the high rates of Hg fallout in rainfall and known recycling for organic sediments containing high concentrations of Hg.

Intensified agriculture practices contribute to nutrient enrichment in freshwater lakes, causing eutrophication, algal blooms, and water hyacinth infestations. Eutrophication in Lake Tana, the source of the Blue Nile in Ethiopia, necessitates effective monitoring due to rapid infestation of water hyacinths. While traditional monitoring is costly and limited in spatial and temporal coverage, remote sensing offers a promising alternative. This study develops a regression model to estimate Chlorophyll-a (Chl-a) concentration using in situ and remote sensing reflectance data. Field measurements from 143 locations across Lake Tana were used to validate the correlation equations. Results show that the Moderate Resolution Imaging Spectroradiometer (MODIS) in near-infrared reflectance exhibits the strongest linear relationship with in situ Chl-a measurements for August 2016 ( r ² = 0.53), December 2016 ( r ² = 0.56) and March 2017 ( r ² = 0.61). The developed models were validated with a root-mean-square error of 2.76 μg/L, 5.89 μg/L, and 8.04 μg/L for August, December, and March, respectively. Applying the developed model from 2008–2018, the Chl-a concentration of the lake indicated an increasing trend, likely driven by non-point sources from surrounding watersheds, causing infestation of the lake by hyacinths since 2011. The agreement between MODIS and in situ Chl-a data, coupled with the satisfactory performance of the linear regression model, underscores that developing a regression model for Chl-a estimation from remote sensing in water hyacinth-infested lakes is a useful method in tracking spatiotemporal variations. This study will serve as a foundation for future Chl-a variation studies in Lake Tana and other similar lakes.