Enhancing the spatial coverage of a regional high-quality hydraulic conductivity dataset with estimates made from domestic water-well specific-capacity tests; [Amélioration de la couverture spatiale d’un ensemble de données de haute qualité de la conductivité hydraulique à l’échelle régionale avec des estimations réalisées à partir d’essais de capacité spécifique sur des forages domestiques d’eau]; [Melhorando a cobertura espacial de dados de condutividade hidráulica de alta qualidade para estudos regionais a partir de ensaios de capacidade específica de poços domésticos de abastecimento]; [Mejora de la cobertura espacial de un conjunto regional de datos de conductividad hidráulica de alta calidad con estimaciones realizadas a partir de ensayos de la capacidad específica en pozos de agua]

The spatial coverage of hydraulic conductivity (K) values for large-scale groundwater investigations is often poor because of the high costs associated with hydraulic testing and the large areas under investigation. Domestic water wells are ubiquitous and their well logs represent an untapped resource of information that includes mandatory specific-capacity tests, from which K can be estimated. These specific-capacity tests are routinely conducted at such low pumping rates that well losses are normally insignificant. In this study, a simple and practical approach to augmenting high-quality K values with reconnaissance-level K values from water-well specific-capacity tests is assessed. The integration of lesser quality K values from specific-capacity tests with a high-quality K data set is assessed through comparisons at two different scales: study-area-wide (a 600-km2 area in Ontario, Canada) and in a single geological formation within a portion of the broader study area (200 km2). Results of the comparisons demonstrate that reconnaissance-level K estimates from specific-capacity tests approximate the ranges and distributions of the high-quality K values. Sufficient detail about the physical basis and assumptions that are invoked in the development of the approach are presented here so that it can be applied with confidence by practitioners seeking to enhance their spatial coverage of K values with specific-capacity tests. © 2017, Springer-Verlag GmbH Germany.