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Spreadsheet Tools for Quantifying Seepage Flux Across the GW-SW Interface

Identifying the spatial distribution and magnitude of seepage flux across the groundwater-surface water (GW-SW) interface is critical for assessing potential impairments and restoration alternatives for water bodies adjacent to sites with groundwater contamination. Measurement of the vertical distri...

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Detalles Bibliográficos
Autores principales: Ford, R. G., Lien, B. K., Acree, S. D., Ross, R. R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7970483/
https://www.ncbi.nlm.nih.gov/pubmed/33746297
http://dx.doi.org/10.1029/2019wr026232
Descripción
Sumario:Identifying the spatial distribution and magnitude of seepage flux across the groundwater-surface water (GW-SW) interface is critical for assessing potential impairments and restoration alternatives for water bodies adjacent to sites with groundwater contamination. Measurement of the vertical distribution and time-varying characteristics of temperature in sediments provides an indirect way to map out spatial and temporal patterns of seepage flux into surface water. Two spreadsheet-based calculation tools are introduced that implement four one-dimensional analytical solutions to calculate the magnitude and direction of seepage flux based on measurement of steady-state vertical temperature profiles or transient diel temperature signals at two depths within sediment. Performance of these calculation tools is demonstrated for a pond receiving contaminated groundwater discharge from an adjacent landfill. Transient versus steady-state model performance is compared, and limitations of transient modelsare illustrated for a situation with unfavorable sediment characteristics and inadequate sensor spacing. The availability of a range of analytical solutions implemented within Microsoft Excel(®) is intended to encourage practitioners to explore use of this seepage flux characterization method and develop greater insight into best practices for model selection and use.