A very detailed water budget was conducted on Lake Trafford in southern Florida. The inflow was dominated by surface-water influx via five canals (61%) with groundwater influx constituting 12% and direct rainfall 27%. Lake discharge was dominated by sheet-flow (69%) and evapotranspiration (30.5%) with groundwater recharge of the hydraulically connected unconfined aquifer accounting for only 0.5%. Removal of 30 M tons (4.4 x 106 m3) of organic sediment impacted groundwater influx, causing enhanced groundwater flows into the deeper parts of the lake and mixed flows along the banks creating a rather unusual pattern. The large number of groundwater seepage meters used during the investigation led to a very reliable set of measurements with occasional failure of only a few meters. A distinctive relationship was found between the wet season lake stage, heavy rainfall events and pulses of exiting sheet-flow from the lake. Estimation of the evapotranspiration loss using data collected from a weather station on the lake allowed the use of three different models which, when averaged, produced results comparable to Lake Okeechobee (southern Florida). A limitation of the investigation was the inability to directly measure sheet-flow discharges, which had to be estimated as a residual within the calculated water budget.

Abstract: 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 are 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.