View in EDS HTML Full Text PDF Full Text

Continental-scale prediction of hydrologic signatures and processes.

Saved in:
Bibliographic Details
Title: Continental-scale prediction of hydrologic signatures and processes.
Authors: Araki, Ryoko1,2 (AUTHOR) raraki8159@sdsu.edu, Holt, Anne2 (AUTHOR), Hammond, John C.3 (AUTHOR), Husic, Admin4 (AUTHOR), Coxon, Gemma5 (AUTHOR), McMillan, Hilary K.2 (AUTHOR) hmcmillan@sdsu.edu
Source: Hydrology & Earth System Sciences. 2026, Vol. 30 Issue 11, p3647-3673. 27p.
Subject Terms: *Watersheds, *Random forest algorithms, *Hydrologic models, *Soils, *Environmental engineering, *Water management, *Continents, *Hydrologic cycle
Geographic Terms: United States
Abstract: Understanding how dominant hydrologic processes and their drivers vary across diverse continental-scale landscapes is critical for hydrologic modeling and water management applications. Our research addresses this question by synthesizing large-sample watershed datasets, Caravan and GAGES-II, and developing random forest models to identify patterns in hydrologic function. We assessed dominant processes by examining hydrologic signatures – summary indicators of watershed function derived from hydroclimatic time series and random forest models across 14 146 gauged United States watersheds. The results reveal clear continental-scale gradients in hydrologic processes, including baseflow, overland flow, storage, and water balance losses. Our map of dominant processes highlights, for example, the transition from baseflow to fast responses and back to baseflow along the elevation gradient from the Appalachian spine, through the Piedmont, to the Eastern Coastal Plain; a distinct outer ring around the Great Lakes region; and sharp contrasts between coastal and inland processes in the West. Variable importance analysis from random forest models show that processes in the western U.S. are primarily controlled by climate, whereas in the eastern U.S., soil, geology, and topography play larger roles, with distinct human influences apparent in urban areas. Our approach of estimating dominant processes and their drivers facilitates extending process knowledge from research watersheds to the continental scale, assessing current hydrological understanding, and evaluating hydrological model structures. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: enr
DbLabel: Energy & Power Source
An: 194731021
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Continental-scale prediction of hydrologic signatures and processes.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Araki%2C+Ryoko%22">Araki, Ryoko</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> raraki8159@sdsu.edu</i><br /><searchLink fieldCode="AR" term="%22Holt%2C+Anne%22">Holt, Anne</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hammond%2C+John C%2E%22">Hammond, John C.</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Husic%2C+Admin%22">Husic, Admin</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Coxon%2C+Gemma%22">Coxon, Gemma</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22McMillan%2C+Hilary K%2E%22">McMillan, Hilary K.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> hmcmillan@sdsu.edu</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Hydrology+%26+Earth+System+Sciences%22">Hydrology & Earth System Sciences</searchLink>. 2026, Vol. 30 Issue 11, p3647-3673. 27p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Watersheds%22">Watersheds</searchLink><br />*<searchLink fieldCode="DE" term="%22Random+forest+algorithms%22">Random forest algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22Hydrologic+models%22">Hydrologic models</searchLink><br />*<searchLink fieldCode="DE" term="%22Soils%22">Soils</searchLink><br />*<searchLink fieldCode="DE" term="%22Environmental+engineering%22">Environmental engineering</searchLink><br />*<searchLink fieldCode="DE" term="%22Water+management%22">Water management</searchLink><br />*<searchLink fieldCode="DE" term="%22Continents%22">Continents</searchLink><br />*<searchLink fieldCode="DE" term="%22Hydrologic+cycle%22">Hydrologic cycle</searchLink>
– Name: SubjectGeographic
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22United+States%22">United States</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Understanding how dominant hydrologic processes and their drivers vary across diverse continental-scale landscapes is critical for hydrologic modeling and water management applications. Our research addresses this question by synthesizing large-sample watershed datasets, Caravan and GAGES-II, and developing random forest models to identify patterns in hydrologic function. We assessed dominant processes by examining hydrologic signatures – summary indicators of watershed function derived from hydroclimatic time series and random forest models across 14 146 gauged United States watersheds. The results reveal clear continental-scale gradients in hydrologic processes, including baseflow, overland flow, storage, and water balance losses. Our map of dominant processes highlights, for example, the transition from baseflow to fast responses and back to baseflow along the elevation gradient from the Appalachian spine, through the Piedmont, to the Eastern Coastal Plain; a distinct outer ring around the Great Lakes region; and sharp contrasts between coastal and inland processes in the West. Variable importance analysis from random forest models show that processes in the western U.S. are primarily controlled by climate, whereas in the eastern U.S., soil, geology, and topography play larger roles, with distinct human influences apparent in urban areas. Our approach of estimating dominant processes and their drivers facilitates extending process knowledge from research watersheds to the continental scale, assessing current hydrological understanding, and evaluating hydrological model structures. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=194731021
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.5194/hess-30-3647-2026
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 27
        StartPage: 3647
    Subjects:
      – SubjectFull: Watersheds
        Type: general
      – SubjectFull: Random forest algorithms
        Type: general
      – SubjectFull: Hydrologic models
        Type: general
      – SubjectFull: Soils
        Type: general
      – SubjectFull: Environmental engineering
        Type: general
      – SubjectFull: Water management
        Type: general
      – SubjectFull: Continents
        Type: general
      – SubjectFull: Hydrologic cycle
        Type: general
      – SubjectFull: United States
        Type: general
    Titles:
      – TitleFull: Continental-scale prediction of hydrologic signatures and processes.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Araki, Ryoko
      – PersonEntity:
          Name:
            NameFull: Holt, Anne
      – PersonEntity:
          Name:
            NameFull: Hammond, John C.
      – PersonEntity:
          Name:
            NameFull: Husic, Admin
      – PersonEntity:
          Name:
            NameFull: Coxon, Gemma
      – PersonEntity:
          Name:
            NameFull: McMillan, Hilary K.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 06
              Text: 2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 10275606
          Numbering:
            – Type: volume
              Value: 30
            – Type: issue
              Value: 11
          Titles:
            – TitleFull: Hydrology & Earth System Sciences
              Type: main
ResultId 1