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Forecasting Natural Aquifer Discharge Using a Numerical Model and Convolution
Authors:Kevin G Boggs  Gary S Johnson  Rob Van Kirk  Jerry P Fairley
Institution:1. Department of Geological Sciences, University of Idaho, , Moscow, ID, 83844 USA.;2. Department of Mathematics, Humboldt State University and Henry's Fork Foundation, , Ashton, ID, 83420
Abstract:If the nature of groundwater sources and sinks can be determined or predicted, the data can be used to forecast natural aquifer discharge. We present a procedure to forecast the relative contribution of individual aquifer sources and sinks to natural aquifer discharge. Using these individual aquifer recharge components, along with observed aquifer heads for each January, we generate a 1‐year, monthly spring discharge forecast for the upcoming year with an existing numerical model and convolution. The results indicate that a forecast of natural aquifer discharge can be developed using only the dominant aquifer recharge sources combined with the effects of aquifer heads (initial conditions) at the time the forecast is generated. We also estimate how our forecast will perform in the future using a jackknife procedure, which indicates that the future performance of the forecast is good (Nash‐Sutcliffe efficiency of 0.81). We develop a forecast and demonstrate important features of the procedure by presenting an application to the Eastern Snake Plain Aquifer in southern Idaho.
Keywords:
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