http://dx.doi.org/10.22541/essoar.167267811.10671930/v1

Wiebe, A.J., McKenzie, J.M. (2022) An open-source web tool for visualizing estimates of well capture zones near surface water features. American Geophysical Meeting, Chicago, United States of America, (December 12-16). http://dx.doi.org/10.22541/essoar.167267811.10671930/v1 The abstract and poster are available at http://dx.doi.org/10.22541/essoar.167267811.10671930/v1 ; the R code is available from https://github.com/ajwiebe77/theYWVC

Identifying areas of the land surface and surface water features (e.g., rivers, lakes, etc.) likely to contribute groundwater recharge to a public groundwater supply well is typically a first step toward source water protection. Identifying the contributions from these areas is important for assessing contamination sources, developing land use management strategies, and mitigating groundwater risk for drinking water supply. Simple analytical solutions that employ Darcy’s Law are unable to account for surface water boundary conditions within the flow system. Therefore, capture zone delineation is typically performed using three-dimensional, fully distributed numerical models that require considerable numbers of parameters, stratigraphic data, and user expertise. However, advanced analytical solutions exist that can provide approximations to such solutions using few parameters.In this work, the R Shiny web platform is developed to create an open-source application to allow Internet users to visualize potential flow systems near wells in the vicinity of surface water features. Assumptions include homogeneous stratigraphy and aquifer thickness, a steady state flow field, and relatively simple aquifer geometry. The web tool is currently being developed with a focus on Yukon Territory in northern Canada, where most of the population relies on groundwater, but less work has been done on the analysis of well vulnerability and source water protection than in southern Canada. The results are intended for estimation and education purposes and will be compared with numerical model results for some sites with pre-existing investigations

The abstract and poster are available at http://dx.doi.org/10.22541/essoar.167267811.10671930/v1 ; the R code is available from https://github.com/ajwiebe77/theYWVC