Uncertainty is a pervasive but often poorly understood factor in the delineation of wellhead protection areas (WHPAs), which can discourage water managers and practitioners from relying on model results. To make uncertainty more understandable and thereby remove a barrier to the acceptance of models in the WHPA context, we present a simple approach for dealing with uncertainty. The approach considers two spatial scales for representing uncertainty: local and global. At the local scale, uncertainties are assumed to be due to heterogeneities, and a capture zone is expressed in terms of a capture probability plume. At the global scale, uncertainties are expressed through scenario analysis, using a limited number of physically realistic scenarios. The two scales are integrated by using the precautionary principle to merge the individual capture probability plumes corresponding to the different scenarios. The approach applies to both wellhead protection and the mitigation of contaminated aquifers, or in general, to groundwater management areas. An example relates to the WHPA for a supply well located in a complex glacial aquifer system in southwestern Ontario, where we focus on uncertainty due to the spatial distributions of recharge. While different recharge scenarios calibrate equally well to the same data, they result in different capture probability plumes. Using the precautionary approach, the different plumes are merged into two types of maps delineating groundwater management areas for either wellhead protection or aquifer mitigation. The study shows that calibrations may be non-unique, and that finding a "best" model on the basis of the calibration fit may not be possible.
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http://dx.doi.org/10.1016/j.jconhyd.2013.02.004 | DOI Listing |
Sci Rep
January 2025
USDA, ARS, Sustainable Agricultural Water Systems (SAWS) Unit, UC Davis, 239 Hopkins Road, Davis, CA, 95616, USA.
This study explores innovative drywell designs for managed aquifer recharge (MAR) in agricultural settings, focusing on smaller diameter and deeper drywells, including the repurposing of dried or abandoned wells. Numerical simulations assessed the impact of drywell diameter (5-120 cm), depth (15-55 m), screen height, and subsurface heterogeneity on infiltration (I) and recharge (R) volumes over a one-year period under constant head conditions. Results indicate that smaller diameter drywells can effectively infiltrate and recharge significant water volumes.
View Article and Find Full Text PDFJ Environ Manage
January 2025
Savannah River Ecology Laboratory, University of Georgia, Aiken, SC 29802, USA. Electronic address:
The primary approach to assessing monitored natural attenuation (MNA) is currently based on a conceptual model utilizing the total contaminant concentrations, assuming a single aqueous species. However, many contaminants, such as metals and radionuclide - including iodine, can exist in multiple species that behave chemically differently in the environment and can exist simultaneously. For example, radioiodine often occurs concurrently as three major aqueous species: iodide (I), iodate (IO), and organo-I, which undergo distinct attenuation pathways and exhibit markedly different mobility and geochemical behavior.
View Article and Find Full Text PDFIntegr Environ Assess Manag
January 2025
Department of Medicine, Division of Occupational, Environmental and Climate Medicine, University of California, San Francisco; San Francisco, California, 94158United States.
Water scarcity is projected to affect half of the world's population, gradually exacerbated by climate change. This article elaborates from a panel discussion at the 2023 United Nations Water Conference on Addressing Water Scarcity to Achieve Climate Resilience and Human Health. Understanding and addressing water scarcity goes beyond hydrological water balances to also include societal and economic measures.
View Article and Find Full Text PDFChemosphere
January 2025
, School of Water Resources Engineering, Jadavpur University, Kolkata 700032, West Bengal, India. Electronic address:
Groundwater toxicity and water level depletion are serious concerns today. Assessing groundwater quality (GWQ) is crucial for effective planning and management due to increasing demands for drinking and irrigation water. Therefore, this study aims to analyze groundwater hydrochemistry, variability, and factors influencing quality for drinking and irrigation purposes using indices and models.
View Article and Find Full Text PDFSci Total Environ
January 2025
Geological Survey of Denmark and Greenland (GEUS), Department of Hydrology, Copenhagen, Denmark.
Machine learning (ML) methods continue to gain traction in hydrological sciences for predicting variables at large scales. Yet, the spatial transferability of these ML methods remains a critical yet underexamined aspect. We present a metamodel approach to obtain large-scale estimates of drain fraction at 10 m spatial resolution, using a ML algorithm (Gradient Boost Decision Tree).
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