Developing a Spatially and Sectorally Disaggregate Water Demand Forecasting Tool for Tampa Bay Water
- Jack Kiefer - Hazen and Sawyer
Tampa Bay Water is the largest wholesale supplier of water in Florida. Over the past 15 years, the agency has funded the development of an integrated surface water, groundwater and desalinated water system. Because of these substantial permitted capacity improvements, it has focused on developing water supplies on a just in time philosophy requiring the use and update of demand forecasts with the ability to forecast various future scenarios and probabilities of water demand by various geographies and sectors of use.
As part of its long-term water supply planning process that occurs every five years, the agency has been updating and integrating its water demand forecasting models into its portfolio of models assessing both demand and supply need. The planning process requires the agency not only assess long term water supply need, it requires probability based forecasts of how demand in various sectors of water use will fluctuate based on growth in the region, the economy, rainfall and the impacts of both active and passive demand management on those forecasts.
This paper will describe the collaborative demand model development process for evaluating spatial and sectoral water demand trends in water use for the purposes of forecasting and efficiency planning. This includes:
- Development of a water demand modeling and forecasting database, using a hierarchy of geographical planning areas and water use sectors
- Exploratory data analysis, including identification of water use trends with weather and socioeconomic/policy variables and statistical characterization of data
- Formulation of forecasting equations and algorithms allowing water use to be estimated over time and geographical areas as a function of climatic, socioeconomic/policy, and water efficiency data.
- Finally, this paper will provide details on how the demand model development process is integrated into the agency’s water supply reliability assessments and estimates of levels of service.
For more information, please contact the author at email@example.com.
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