Estimating dominant runoff modes across the conterminous United States

dc.contributor.authorBuchanan, Brianen
dc.contributor.authorAuerbach, Daniel A.en
dc.contributor.authorKnighton, Jamesen
dc.contributor.authorEvensen, Darricken
dc.contributor.authorFuka, Daniel R.en
dc.contributor.authorEaston, Zachary M.en
dc.contributor.authorWieczorek, Michaelen
dc.contributor.authorArchibald, Josephine A.en
dc.contributor.authorMcWilliams, Brandonen
dc.contributor.authorWalter, Todden
dc.contributor.departmentBiological Systems Engineeringen
dc.date.accessioned2020-06-30T13:16:11Zen
dc.date.available2020-06-30T13:16:11Zen
dc.date.issued2018-12-30en
dc.description.abstractEffective natural resource planning depends on understanding the prevalence of runoff generating processes. Within a specific area of interest, this demands reproducible, straightforward information that can complement available local data and can orient and guide stakeholders with diverse training and backgrounds. To address this demand within the contiguous United States (CONUS), we characterized and mapped the predominance of two primary runoff generating processes: infiltration-excess and saturation-excess runoff (IE vs. SE, respectively). Specifically, we constructed a gap-filled grid of surficial saturated hydraulic conductivity using the Soil Survey Geographic and State Soil Geographic soils databases. We then compared surficial saturated hydraulic conductivity values with 1-hr rainfall-frequency estimates across a range of return intervals derived from CONUS-scale random forest models. This assessment of the prevalence of IE versus SE runoff also incorporated a simple uncertainty analysis, as well as a case study of how the approach could be used to evaluate future alterations in runoff processes resulting from climate change. We found a low likelihood of IE runoff on undisturbed soils over much of CONUS for 1-hr storms with return intervals <5 years. Conversely, IE runoff is most likely in the Central United States (i.e., Texas, Louisiana, Kansas, Missouri, Iowa, Nebraska, and Western South Dakota), and the relative predominance of runoff types is highly sensitive to the accuracy of the estimated soil properties. Leveraging publicly available data sets and reproducible workflows, our approach offers greater understanding of predominant runoff generating processes over a continental extent and expands the technical resources available to environmental planners, regulators, and modellers.en
dc.description.adminPublic domain – authored by a U.S. government employeeen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1002/hyp.13296en
dc.identifier.eissn1099-1085en
dc.identifier.issn0885-6087en
dc.identifier.issue26en
dc.identifier.urihttp://hdl.handle.net/10919/99175en
dc.identifier.volume32en
dc.language.isoenen
dc.rightsCC0 1.0 Universalen
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/en
dc.subjectcontiguous United Statesen
dc.subjectinfiltration excess runoffen
dc.subjectprecipitation frequency analysisen
dc.subjectrandom foresten
dc.subjectrunoff generationen
dc.subjectsaturation excess runoffen
dc.titleEstimating dominant runoff modes across the conterminous United Statesen
dc.title.serialHydrological Processesen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.dcmitypeStillImageen

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