Evaluating Climate Variability and Pumping Effects in Statistical Analyses
Article first published online: 1 NOV 2007
No claim to original US government works
Volume 46, Issue 2, pages 212–227, March–April 2008
How to Cite
Mayer, T. D. and Congdon, R. D. (2008), Evaluating Climate Variability and Pumping Effects in Statistical Analyses. Groundwater, 46: 212–227. doi: 10.1111/j.1745-6584.2007.00381.x
- Issue published online: 1 NOV 2007
- Article first published online: 1 NOV 2007
- Received March 2007, accepted August 2007.
As development of ground water resources reaches the limits of sustainability, it is likely that even small changes in inflow, outflow, or storage will have economic or environmental consequences. Anthropogenic impacts of concern may be on the scale of natural variability, making it difficult to distinguish between the two. Under these circumstances, we believe that it is important to account for effects from both ground water development and climate variability. We use several statistical methods, including trend analysis, cluster analysis, and time series analysis with seasonal decomposition, to identify climate and anthropogenic effects in regional ground water levels and spring discharge in southern Nevada. We discuss the parameterization of climate and suggest that the relative importance of various measures of climate provides information about the aquifer system response to climate. In our system, which may be characteristic of much of the arid southwestern United States, ground water levels are much more responsive to wet years than to dry years, based on the importance of selected climate parameters in the regression. Using cluster analysis and time series seasonal decomposition, we relate differences in amplitude and phase in the seasonal signal to two major forcings—climate and pumping—and distinguish between a regional recharge response to an extremely wet year and a seasonal pumping/evapotranspiration response that decays with distance from the pumping center. The observed spring discharge data support our hypothesis that regional spring discharge, particularly at higher elevation springs, is sensitive to relatively small ground water level changes.