Forecasting the probability of future groundwater levels declining below specified low thresholds in the conterminous U.S.

Journal of the American Water Resources Association
By: , and 

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Abstract

We present a logistic regression approach for forecasting the probability of future groundwater levels declining or maintaining below specific groundwater-level thresholds. We tested our approach on 102 groundwater wells in different climatic regions and aquifers of the United States that are part of the U.S. Geological Survey Groundwater Climate Response Network. We evaluated the importance of current groundwater levels, precipitation, streamflow, seasonal variability, Palmer Drought Severity Index, and atmosphere/ocean indices for developing the logistic regression equations. Several diagnostics of model fit were used to evaluate the regression equations, including testing of autocorrelation of residuals, goodness-of-fit metrics, and bootstrap validation testing. The probabilistic predictions were most successful at wells with high persistence (low month-to-month variability) in their groundwater records and at wells where the groundwater level remained below the defined low threshold for sustained periods (generally three months or longer). The model fit was weakest at wells with strong seasonal variability in levels and with shorter duration low-threshold events. We identified challenges in deriving probabilistic-forecasting models and possible approaches for addressing those challenges.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Forecasting the probability of future groundwater levels declining below specified low thresholds in the conterminous U.S.
Series title Journal of the American Water Resources Association
DOI 10.1111/1752-1688.12582
Volume 53
Issue 6
Year Published 2017
Language English
Publisher Wiley
Contributing office(s) New England Water Science Center
Description 13 p.
First page 1424
Last page 1436