Assessment of the impact of optimal irrigation scheduling with rainwater harvesting for water conservation and runoff reduction in large urban areas

Due to population growth, demand for freshwater is increasing in large urban areas such as the Dallas-Fort Worth Metroplex (DFW). Because lawn irrigation uses by far the largest amount of water, many municipalities impose restrictions in times of drought or water scarcity. Such restrictions, however, do not account for the site-specific environmental conditions. As such, over the course of an irrigation season, the amount of water used may be significantly more than what is necessary in order to keep the vegetation healthy. If lawn irrigation in large urban areas can be optimized adaptively to the changing environmental conditions, one may expect significant reductions in water use from household to regional scales. The objective of this work is to assess the value of optimal irrigation scheduling with rainwater harvesting for water conservation and runoff reduction in large urban areas. The intelligent system for precision irrigation consists of three components: 1) advanced wireless sensing of soil moisture, temperature, humidity and solar radiation, 2) high-resolution site-specific modeling of the weather-soil-vegetation system, and 3) adaptive optimal control of irrigation. The health of the grass is assessed based on the normalized vegetation index from time lapse images as obtained from the Raspberry Pi camera module. In this presentation, we describe the approach and share the initial results.