Water level time series from groundwater production wells offer a transient dataset that can be used to estimate aquifer properties in areas with active groundwater development. This article describes a new parameter estimation method to infer aquifer properties from such datasets. Specifically, the method analyzes long-term water level measurements from multiple, interacting groundwater production wells and relies on temporal water level derivatives to estimate the aquifer transmissivity and storativity. Analytically modeled derivatives are compared to derivatives calculated directly from the observed water level data; an optimization technique is used to identify best-fitting transmissivity and storativity values that minimize the difference between modeled and observed derivatives. We demonstrate how the consideration of derivative (slope) behavior eliminates uncertainty associated with static water levels and well-loss coefficients, enabling effective use of water level data from groundwater production wells. The method is applied to time-series data collected over a period of 6 years from a municipal well field operating in the Denver Basin, Colorado (USA). The estimated aquifer properties are shown to be consistent with previously published values. The parameter estimation method is further tested using synthetic water level time series generated with a numerical model that incorporates the style of heterogeneity that occurs in the Denver Basin sandstone aquifers.
Colorado Groundwater