2008 Joint Meeting of The Geological Society of America, Soil Science Society of America, American Society of Agronomy, Crop Science Society of America, Gulf Coast Association of Geological Societies with the Gulf Coast Section of SEPM

Paper No. 10
Presentation Time: 4:15 PM

Simulation-Optimization of Soil-Aquifer Treatment System Release Patterns

DE LARA BASHULTO, Josue and UDDAMERI, Venkatesh, Environmental Engineering, Texas A&M University-Kingsville, 700 University Blvd. MSC 213, Kingsville, TX 78363, jdelara@eng.tamuk.edu

Artificial recharge technologies aim to store or replenish water in an aquifer using surficial sources. Soil-aquifer treatment (SAT) is a special type of artificial recharge method in which a low quality water, such as treated wastewater, is used for recharge. This type of treatment has the combined objectives of improving water quality by the filtering capabilities of the vadoze zone and to replenish the underlying aquifer. SATs have been used in various locations around the globe; this work addresses the need to enhance the efficiency of these systems by increasing the infiltrated water while maintaining strict quality constraints. A simulation-optimization model representing a SAT artificial recharge system of an interconnected storage basin, vadoze, and aquifer system is developed in this study. The movement of water through the soil is modeled using mass balance principles and Darcy’s law applied on finite segments. Having evaluated the model, qualitative and quantitative simulations were carried out of an artificial recharge system receiving an effluent with a predefined biochemical oxygen demand (BOD). A period of 45 days was selected for a simulation having a basin inflow associated to each day. Maximizing the amount of recycled water was the main objective while maintaining recharged BOD concentration below a standard, and not exceeding the recharge basin capacity were the optimization constraints; additionally, a defined soil moisture content was required at the end of the simulation period. Given the non-linear nature of the system, the optimization was solved using evolutionary and non-linear solvers. The output from the model provides optimal release patterns into the SAT system and helps manage its operation.