Date of Completion
5-11-2013
Embargo Period
5-10-2013
Advisors
Glenn S. Warner; Lanbo Liu
Field of Study
Environmental Engineering
Degree
Master of Science
Open Access
Open Access
Abstract
The University of Connecticut relies on the Fenton River water supply wells to support 25% of their overall water supply. Low stream flow can commonly be seen from June - October, in which the University must reduce pumping based on stream flow thresholds to prevent adverse effects to fish habitat. The objective of this study was to investigate the stream/aquifer interaction in order to increase water withdrawals while minimizing adverse impacts to in- stream flow. A groundwater flow model was developed using MODFLOW to investigate the influence of well location and pump timing on in-stream flow in the vicinity of the water supply wells. A numerical model was modified to include improved geophysical data and hydrologic data from 2000-2009 to assess well placement, rest periods and cyclical pumping. The movement of Well A up to 750 ft from the river had a positive but minimal improvement to stream flow losses (<0.1 cfs). When the well field was shut off for more than 45 days, stream flow returned to its no pumping condition with only slight impact at 30 days. A 30 day rest period gave 4 weeks of dampened pumping influence on stream flows. A management scenario of 1 week cyclical pumping between Wells A and D following a 45 day rest period can allow for current thresholds at Old Turnpike Rd to be reduced by 1.0 cfs with minimal impact to stream flow losses (0.26 cfs) and would allow additional water to be pumped in nine out of ten years analyzed. The thresholds could also be reduced by 0.5 cfs with minimal impact to stream flow losses (0.16 cfs) and would allow additional water to be pumped in eight out of ten years analyzed.
Recommended Citation
Payne, David W., "Management Alternatives to Reduce Pumping Effects in the Fenton River during Periods of Low Stream Flow" (2013). Master's Theses. 413.
https://digitalcommons.lib.uconn.edu/gs_theses/413
Major Advisor
Amvrossios C. Bagtzoglou