A scenario-based water conservation planning support system (SB-WCPSS)

In this study a water consumption model is built into a scenario-based planning support system (SB-WCPSS). The SB-WCPSS consists of four components—(1) a model input graphic user interface, (2) a community spatial database, (3) a set of drinking water consumption models, and (4) output display. The SB-WCPSS is implemented with a commercial planning support system software package—CommunityViz. The model is applied using data in Cincinnati, Ohio, USA to demonstrate the scenario development. In the application, water consumption consists of land use based indoor, turf, and pool water usages. Climate change is reflected in monthly temperature and precipitation. By specifying anticipated future land uses and associated water consumption rates, temperature, and precipitation, SB-WCPSS users can analyze and compare water consumptions under various scenarios, using maps, graphs, and tables. Parcel-based daily water consumptions were computed and summarized spatially by neighborhood, block group, or land use type. The results demonstrate that water conservation strategies, such as xeriscape, can reduce turf water usage. Indoor water consumption depends on the number of people who use water and how they use water. The study shows that the SB-WCPSS structure is sound and user friendly. Future improvement will be on enhancing various components, such as using parcel-based data and more robust water consumption models. The system may be used by water resource managers and decision makers to adapt water resources (e.g., watersheds and infrastructure) to climate change and demographic and economic development.

[1]  R. Klosterman.  Planning Support Systems: A New Perspective on Computer-Aided Planning , 1997 .

[2]  Zhongwei Liu,et al.  Using HSPF to Model the Hydrologic and Water Quality Impacts of Riparian Land-Use Change in a Small Watershed , 2011 .

[3]  R. Cohen.  Handbook of Water Use and Conservation , 2002 .

[4]  Brownstein Hyatt Farber Schreck.  A Water Supply Crisis or a Water Management Crisis , 2009 .

[5]  Ping Guo,et al.  Two-stage fuzzy chance-constrained programming: application to water resources management under dual uncertainties , 2009 .

[6]  R. T. James,et al.  Application of MIKE SHE/MIKE 11 Model to Structural BMPs in S191 Basin, Florida , 2012 .

[7]  S. Guhathakurta,et al.  The Impact of the Phoenix Urban Heat Island on Residential Water Use , 2007 .

[8]  Amy G. Burgess.  Promoting Domestic Water Conservation through the Utilization of a Scenario-Based Planning Support System , 2010 .

[9]  John Stillwell,et al.  Planning Support Systems in Practice , 2003 .

[10]  Richard E. Klosterman,et al.  Planning Support Systems: Integrating Geographic Information Systems,Models,and Visualization Tools , 2001 .

[11]  G. Huang,et al.  An interval-valued fuzzy linear programming with infinite α-cuts method for environmental management under uncertainty , 2011 .

[12]  J. Randolph.  Environmental Land Use Planning and Management , 2003 .

[13]  Patricia Gober,et al.  Climate Variability and Residential Water Use in the City of Phoenix, Arizona , 2007 .

[14]  Doug Bennett,et al.  An in‐depth investigation of Xeriscape as a water conservation measure , 2006 .

[15]  Gordon H. Huang,et al.  Planning water resources management systems using a fuzzy-boundary interval-stochastic programming method , 2010 .

[16]  John Stillwell,et al.  Planning Support Systems: An Introduction , 2003 .

[17]  Darren Holloway,et al.  The use of residential water consumption as an urban planning tool: a pilot study in Adelaide , 2004 .

[18]  Graeme C. Dandy,et al.  Estimating Residential Water Demand in the Presence of Free Allowances , 1997 .

[19]  Nancy L. Barber,et al.  Estimated use of water in the United States in 2005 , 2009 .

[20]  Ana Deletic,et al.  Data Requirements for Integrated Urban Water Management , 2009 .

[21]  Yong Li,et al.  A robust modeling approach for regional water management under multiple uncertainties , 2011 .

[22]  Ted Knowlton Aicp.  Engaging the Future: Forecasts, Scenarios, Plans, and Projects , 2009 .

[23]  Karen C. Rice,et al.  Evaluation of Bayesian Estimation of a Hidden Continuous-Time Markov Chain Model with Application to Threshold Violation in Water-Quality Indicators , 2012 .

[24]  Guohe Huang,et al.  Multistage scenario-based interval-stochastic programming for planning water resources allocation , 2009 .