Clogging of an Effluent Dominated Semiarid River: A Conceptual Model of Stream-Aquifer Interactions1

Water managers in arid and semiarid regions increasingly view treated wastewater (effluent) as an important water resource. Artificial recharge basins allow effluent to seep into the ground relieving stressed aquifers, however these basins frequently clog due to physical, chemical, and biological processes. Likewise effluent is increasingly used to maintain perennial base flow for dry streambeds, however, little is known about the impact of effluent on streambed hydraulic conductivity and stream-aquifer interactions. We address this issue by investigating: if a clogging layer forms, how the formation of a clogging layer alters stream-aquifer connections, and what hydrologic factors control the formation and removal of clogging layers. We focused on the Upper Santa Cruz River, Arizona where effluent from the Nogales International Waste Water Treatment Plant sustains perennial flow. Monthly sampling, along a 30 km river reach, was done with two foci: physical streambed transformations and water source identification using chemical composition. Historical dataset were included to provide a larger context for the work. Results show that localized clogging occurs in the Upper Santa Cruz River. The clogging layers perch the stream and shallow streambed causing desaturation below the streambed. With these results, a conceptual model of clogging is established in the context of a semiarid hydrologic cycle: formation during the hot premonsoon months when flow is nearly constant and removal by large flood flows (> 10 m(3)/s) during the monsoon season. However, if the intensity of flooding during the semiarid hydrologic cycle is lessened, the dependent riparian area can experience a die off. This conceptual model leads us to the conclusion that effluent dominated riparian systems are inherently unstable due to the clogging process. Further understanding of this process could lead to improved ecosystem restoration and management.