Publications and Research
Document Type
Article
Publication Date
2019
Abstract
Water table fluctuation (WTF) methods are a primary and well-established way to determine groundwater recharge based on the direct response of the water table to precipitation input. An emerging complexity of recharge is whether it occurs as an episodic and transient process, or a continuous steady-state process, however most studies have not focused on these short-term vs long-term timescales, in part because of a lack of data resolution. Here, high-resolution (subhourly) precipitation and water level data are analyzed for wells in the suburbs of New York City using two contrasting WTF approaches, with a common mathematical basis, that are suited to episodic and continuous processes. The resulting hourly recharge results, like the individual water level records from comparable wells, are sensitive indicators of subtle differences in 2 aquifer conditions such as thickness of the unsaturated zone, position in the flow system and localized preferential flow. While the episodic, transient approach excludes diffuse recharge by design, the continuous, steady-state approach is influenced by short term precipitation events, and therefore integrates transient processes to some extent. However, the continuous, steady state approach is subject to its own limitations relating to position in the aquifer system, and may overestimate recharge if aquifer conditions are not well understood. More widespread use of higher resolution data as well as understanding aquifer conditions and refining aquifer parameters would improve WTF recharge estimation.
Comments
This is the peer reviewed version of the following article: Eaton, Timothy. "Episodic and Continuous Recharge Estimation from High-Resolution Well Records." Groundwater, 2019. doi: 1111/gwat.12950.
This article has been published in final form at https://doi.org/10.1111/gwat.12950
This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.