T157 Advances in Understanding at the Groundwater–Surface Water Interface and Challenges for the Future: A Reflection on Tom Winter’s Legacy
Tuesday, 11 October 2011
8:00 AM - 12:00 PM
Room M101AB
THE NEED FOR MULTI-SCALE HEAT AS A TRACER AND SEMI-QUANTITATIVE METHODS TO CHARACTERIZE GROUNDWATER SURFACE-WATER INTERACTIONS
Paper number: T157-13
Program: Technical Sessions
Time: 11:00 AM – 11:15 AM
Authors
Abstract
Numerical studies by Winter (1976) highlighted the complexities of groundwater flow paths and groundwater discharge and recharge patterns associated with lakes. Woessner (2000) subsequently illustrated groundwater surface-water interactions for streams and rivers can be even more complex than lakes over a wide range of scales. Although groundwater discharge can be quite spatially variable, it is important to identify and delineate these areas for studies involving the: locating of critical habitat for fish; characterizing contaminated groundwater plume discharges to surface water; and targeted geochemical sampling of groundwater discharge. Conventional methods of locating groundwater discharges tend to be labor intensive and are not practical for obtaining fine-scale spatial resolution over large areas (e.g. seepage meters and mini-piezometers). There is a need for low cost, multi-scale techniques that can characterize the heterogeneities in discharge or identify significant discharge zones over large spatial scales (even if it is only semi-quantitative data) and temperature as a tracer methods can provide this information. This paper presents the benefits of the sequential implementation of low- altitude infrared surveys, lake bottom (or river bottom) drag probe temperature (or water quality) surveys, and lakebed bed (or riverbed) temperature surveys to delineate groundwater discharge zones. One main advantage of this type of approach is one can have confidence that large or high flux discharge areas are identified (i.e., not missed) and the most significant discharge zones can be targeted for sampling or further characterization rather than relying on sparse random sampling of locations or out-of-context grid sampling and which can result in not knowing how representative those random samples are of the overall area of interest.