Sentence examples for water supply models from inspiring English sources

Hydrologic models and the associated flooding models, water pollutants transportation models and water supply models are usually integrated in Geographic Information System (GIS) for distributed hydrologic stimulations (Fairfield and Leymarie 1991; Konadu and Fosu 2009; Moharana and Kar 2002; Wu et al. 2008).

Several water supply models are already established, tested and proven effective in the developed world.

Within DANUBIA the water supply model ('WaterSupply') forms the link between various physical models determining water quality and availability and several socio-economic models determining water consumption and demand.

The research group "Groundwater and Water Supply" at the Institute of Hydraulic Engineering (IWS), Universitaet Stuttgart, contributes a three-dimensional groundwater flow model and a large-scale water supply model which simulate both water availability and quality and water supply and the related costs for global change scenarios.

The hierarchical order of perception of safety in Nigerian water supply model is presented in Figure 2. The public perception safety in favour of packaged water in Nigeria stems out partly from the inadequate attempts of previous governments to provide potable piped water.

The improvement in regularity of water supply (model C) was associated with an MP of the overall effect of 5.4% and 3.5% (for A. lumbricoides and T. trichuria, respectively), and road and sidewalk paving (model E) appeared to account for 14.6% of the reduction in the prevalence of A. lumbricoides.

Well designed case studies could be utilized to generate valuable learning about the water supply management models, as well governance models.

A micro CHP system composed of a biomass boiler (200 °C heat source), an ORC power cycle and a cooling water line (20 °C cooling water supply) was modeled in four variants depending on whether post-heater and IHE were applied or not.

Average day (AD), peak day (PD) and mean day maximum month (MDMM) demand curves, often used in water supply network modelling, were developed from the herein created methodology using both individual end-use level and hourly demand patterns from the smart meters.

GANetXL's utility is demonstrated on two examples from water engineering practice, a simple water supply reservoir operation model with two objectives and a large combinatorial optimisation problem of pump scheduling in water distribution systems.

Incidence rates were determined for residents by water supply zone and modeled by Poisson regression using the number of cases as the predictor variable and the number of person-years of observation as the offset (11, 12 ).