A Method of Estimating Groundwater Return Flow to Rivers from Riparian Irrigation Districts

Monday, May 5, 2014
Jianting Zhu , Department of Civil and Architectural Engineering, University of Wyoming, Laramie, WY

An improved understanding of the water budget components in floodplain aquifers is necessary to implement and support water accounting requirements for use of river water. Of critical importance is the groundwater return flow as a result of recharge from irrigated water in a typical irrigation district near a river, which is the most uncertain and difficult component to be estimated. The objectives of this study are to (1) develop an effective but simple approach to estimate the amount of groundwater return flow to the river due to irrigation recharge, and (2) conduct uncertainty and sensitivity analyses of groundwater return flow to various recharge scenarios. The approach takes advantage of comprehensive drainage network typical in irrigation districts. The approach is evaluated and tested against numerical model results. It is found that the approach is accurate in calculating groundwater return flow for practical purposes with less than 10% error. We further examine how groundwater return flow may change in response to variations in recharge distributions using the proposed approach. As long as information about river stage, drain stage, and distributions of irrigation water is available, the approach could forecast changes in the amount of return flows.

Jianting Zhu, Department of Civil and Architectural Engineering, University of Wyoming, Laramie, WY
Jianting "Julian" Zhu has been in national laboratories, research institutes, and universities in Canada and the United States for the past 20 years. He is currently a faculty member at the University of Wyoming. His research areas include: scale issues in hydrology and ecology, subsurface hydrology, upscaling of hydrological processes, uncertainty and sensitivity analysis, numerical modeling of hydrology and hydraulics, stochastic analysis and its applications, multiphase fluid flows and contaminant transport in porous media, and artificial neural network applications in hydrology and ecology. His teaching areas include: fluid dynamics, hydrometeorology, groundwater hydrology, hydrology, hydraulic engineering, geostatistics, and reservoir mechanics.