Li et al. (2025) Ubiquity and Causes of Soil Water Preferential Flow Across 17 Ecoregions

Identification

• Journal: Geophysical Research Letters
• Year: 2025
• Date: 2025-10-10
• Authors: Bonan Li, Matthias Sprenger, Briana M. Wyatt, Daniel Giménez, Daniel R. Hirmas, Hoori Ajami, Inge Wiekenkamp, Jannis Groh, John R. Nimmo, Maria Pia Amato, Nitin K. Singh, Octavia Crompton, Ryoko Araki, Tianfang Xu, Pamela Sullivan
• DOI: 10.1029/2025gl118045

Research Groups

• College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR, USA
• Consortium of Universities for the Advancement of Hydrologic Science, Inc., Arlington, MA, USA
• Lawrence Berkeley National Laboratory, Earth and Environmental Sciences Area, Berkeley, CA, USA
• Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC, USA
• Department of Soil and Crop Sciences, Texas A&M University, College Station, TX, USA
• Department of Environmental Sciences, Rutgers University, New Brunswick, NJ, USA
• Department of Plant and Soil Science, Texas Tech University, Lubbock, TX, USA
• Department of Environmental Sciences, University of California Riverside, Riverside, CA, USA
• GFZ Helmholtz Centre for Geosciences, Potsdam, Germany
• Department of Soil Science and Soil Ecology, Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany
• Agrosphere Institute (IBG‐3), Forschungszentrum Jülich (FZJ), Jülich, Germany
• Isotope Biogeochemistry and Gas Fluxes, Research Area 1 “Landscape Functioning”, Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany
• U.S. Geological Survey, Menlo Park, CA, USA
• Department of Crop, Soil and Environmental Sciences, Auburn University, Auburn, AL, USA
• Hydrology and Remote Sensing Laboratory, USDA Agricultural Research Service, Beltsville, MD, USA
• Department of Geography, San Diego State University, San Diego, CA, USA
• Department of Geography, University of California, Santa Barbara, CA, USA
• School of Sustainable Engineering & the Built Environment, Arizona State University, Tempe, AZ, USA

Short Summary

This study quantifies the ubiquity and drivers of soil water preferential flow (PF) across 17 diverse ecoregions in the USA using high-frequency soil moisture data. It reveals that PF is widespread, occurring in up to 60% of rainfall events, and is primarily driven by peak rainfall intensity, soil texture, antecedent soil moisture variability, humid climate, and net primary productivity.

Objective

• To quantify the spatiotemporal occurrence of preferential flow (PF) across 17 ecoregions in the USA.
• To identify the main factors determining PF occurrence, such as rainfall intensity, vegetation cover, and soil texture, across large environmental gradients.

Study Configuration

• Spatial Scale: 40 National Ecological Observatory Network (NEON) terrestrial sites across 17 ecoregions in the USA (including Puerto Rico), utilizing approximately 1,500 soil moisture sensors.
• Temporal Scale: Four to seven years of data collection per site, specifically between 2016 and 2022.

Methodology and Data

• Models used:
  • Random Forest regression model for predicting PF occurrence.
  • Rosetta3 pedotransfer model for estimating saturated hydraulic conductivity (Ksat).
• Data sources:
  • High-frequency (1-minute) volumetric soil moisture data from Sentek–EnviroSCAN TriSCAN sensors at up to 8 depths (6–200 cm) from NEON sites.
  • Precipitation data (10-minute intervals) from tipping buckets or weighing gauges at NEON sites.
  • Site characteristic data (e.g., soil texture) directly from NEON.
  • Annual net primary productivity (NPP) and evapotranspiration (ET) data from remotely sensed products (MODIS).
  • Two PF detection methods: Non-Sequential Response (NSR) and Velocity Threshold (VT) criteria.

Main Results

• Preferential flow (PF) is ubiquitous across all 40 study sites in the USA, occurring in up to 60% of rainfall events greater than or equal to 2 mm.
• PF occurrence is generally higher in the more humid eastern USA compared to semi-arid regions in the western USA.
• Key drivers consistently identified by multiple PF detection approaches include peak rainfall intensity, soil texture (specifically clay content), antecedent soil moisture variability, humid climate, and higher net primary productivity (NPP).
• A critical threshold-like behavior was observed for rainfall intensity, with a steep increase in PF likelihood between 5 and 12 mm/h, and a plateau at intensities greater than 13 mm/h.
• Higher clay content in soils increases the likelihood of PF occurrence, attributed to enhanced soil structural development and macroporosity.
• Lower variability (coefficient of variation between 30%–45%) in antecedent soil moisture conditions increases the likelihood of PF, with wetter mean antecedent conditions also promoting PF.
• PF occurrence generally decreases with increasing aridity, particularly from sub-humid to semi-arid regions.
• Higher NPP values (indicating greater vegetation productivity) are associated with an increased likelihood of PF, potentially due to increased biopore abundance, aggregate formation, and soil organic matter.
• The relationships between PF occurrence and its drivers were robust and consistent across both the Velocity Threshold (VT) and Non-Sequential Response (NSR) identification methods, despite differences in the absolute number of detected PF events (VT detected PF four times more often than NSR).

Contributions

• This is the first study to quantify the spatiotemporal occurrence and controls of preferential flow across large environmental gradients (17 ecoregions in the USA) using high-frequency, multi-depth soil moisture data.
• It provides robust, continental-scale evidence for the ubiquity of PF and identifies consistent drivers, addressing a significant data scarcity gap in understanding PF occurrence and its mechanisms.
• The study advances process-understanding of PF by demonstrating critical threshold behaviors for drivers like rainfall intensity and antecedent soil moisture variability.
• It highlights the critical importance of incorporating PF processes into hydrological and biogeochemical models, especially given projected climate and land-use changes that could alter rainfall intensity and NPP, impacting groundwater recharge, water quality, and streamflow generation.

Funding

• AI4PF Working Group (Using a network of networks for high‐frequency multi‐depth soil moisture observations to infer spatial and temporal drivers of subsurface preferential flow)
• Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI)
• John Wesley Powell Center for Analysis and Synthesis (funded by the U.S. Geological Survey)
• U.S. Department of Energy Office of Science (contract DE‐AC02‐05CH11231) as part of Lawrence Berkeley National Laboratory Watershed Function Science Focus Area (for Matthias Sprenger)
• Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, project no. 460817082) (for Jannis Groh)
• CUAHSI (for open access publication)

Citation

@article{Li2025Ubiquity,
  author = {Li, Bonan and Sprenger, Matthias and Wyatt, Briana M. and Giménez, Daniel and Hirmas, Daniel R. and Ajami, Hoori and Wiekenkamp, Inge and Groh, Jannis and Nimmo, John R. and Amato, Maria Pia and Singh, Nitin K. and Crompton, Octavia and Araki, Ryoko and Xu, Tianfang and Sullivan, Pamela},
  title = {Ubiquity and Causes of Soil Water Preferential Flow Across 17 Ecoregions},
  journal = {Geophysical Research Letters},
  year = {2025},
  doi = {10.1029/2025gl118045},
  url = {https://doi.org/10.1029/2025gl118045}
}