Abstract

Wastewater reuse via irrigation provides the potential for significant increases in water use efficiency; however, excessive solutes from wastewater can pollute the groundwater beneath the irrigated lands. To avoid this adverse impact and provide a mechanism for informing optimal management practices, this study develops a monitoring and modeling system to assimilate embedded sensor network measurements into a hydrologic model to provide real-time soil state and flux estimates. The feasibility of soil characterization with a data assimilation algorithm is investigated through a series of observing system simulation experiments (OSSEs) at a wastewater reuse testbed in Palmdale, California. Results show that state (i.e. soil moisture) estimation in isolation can lead to significant errors if flux estimates are a primary objective of the estimation framework and parameters are not well characterized. Overall, the OSSEs indicate that with sufficient measurement information, the system is capable of providing an accurate characterization of real-time soil state, model parameter, and flux estimates (even in the presence of biases) that could be useful in managing wastewater irrigation to avoid hazardous contamination of the underlying groundwater system.

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