Monday, 8 January 2018: 2:15 PM
Room 7 (ACC) (Austin, Texas)
Fatemeh Habibi Ardekani, Univ. of Texas, Arlington, TX; and J. lee, S. Noh, and D. J. Seo
Lawn irrigation accounts for by far the largest usage of tap water in the Dallas-Fort Worth Metroplex area where freshwater is becoming an increasingly scarce resource. Rule-based irrigation decisions such as irrigating twice a week are likely to use more water than necessary. If lawn irrigation scheduling can be optimized location-specifically and adaptively to the changing and forecast environmental conditions, one may expect significant reductions in water use. Whereas rainwater harvesting is of limited effectiveness in reducing runoff for extreme rainfall, if practiced over a large area in concert, one may expect significant benefits in reducing peak flow and improving water quality for smaller but more frequent rainfall events. In addition, the
rainwater stored can be used for outdoor irrigation thereby providing dual benefits. In this presentation, we describe a prototype cyber-physical system, referred to herein as i2Water, that utilizes weather-soil-vegetation modeling, rainwater harvesting and control, environmental sensing, and medium-range ensemble forecasting of precipitation and temperature for integrated control of rainwater harvesting and lawn irrigation. We apply the system in a simulation mode to areas in DFW for quantitative assessment of its potential impact via multi-year hindcasting using high-resolution precipitation estimates from NEXRAD, and medium-range ensemble forecasts of precipitation and temperature based on the Global Ensemble Forecast System reforecast dataset. We share the preliminary results and identify issues and challenges.
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