skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: The Influence of Local and Nonlocal Factors on Soil Water Content in a Steep Forested Catchment
Abstract Surface topography can influence flow pathways and the location of runoff source areas and water transport in steep headwater catchments. However, the influence of topography on spatial patterns of residual soil moisture is less well understood. We measured soil volumetric water content (VWC) on 14 dates at 0–30 and 30–60 cm depth at 54 sites on a steep, 10 ha north‐facing forested slope in the west‐central Cascades Mountains of Oregon, USA. Spatial patterns in VWC were persistent over time, and contrary to expectations VWC at 30–60 cm depth was greater on divergent than convergent slopes, especially during wet periods (R2 = 0.27,p < 0.001). Vegetation characteristics were assessed for all VWC monitoring locations and soil properties were determined for 13 locations as local factors that affect spatial patterns in VWC. Mean VWC over all dates was negatively correlated to gravimetric rock content (R2 = 0.28,p = 0.03) and positively correlated to water storage at field capacity (R2 = 0.56,p < 0.01). The variability in rock content in quick‐draining soils influenced soil‐water retention, and by extension, created spatially heterogenous but temporally persistent patterns in VWC. While spatial patterns were persistent, they were not easily explained by surficial topography in a steep, mountainous landscape with rocky, well‐drained soils. Further research is needed to understand if combined soil‐terrain metrics would be a more useful proxy for VWC than terrain‐based wetness metrics alone.  more » « less
Award ID(s):
2025755
PAR ID:
10442578
Author(s) / Creator(s):
 ;  ;  
Publisher / Repository:
DOI PREFIX: 10.1029
Date Published:
Journal Name:
Water Resources Research
Volume:
57
Issue:
5
ISSN:
0043-1397
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract The heat transfer and water retention in soils, governed by soil thermal conductivity (λ) and soil water retention curve (SWRC), are coupled. Soil water content (θ) significantly affects λ. Several models have been developed to describe λ(θ) relationships for unsaturated soils. Ghanbarian and Daigle presented a percolation‐based effective‐medium approximation (P‐EMA) for λ(θ) with two parameters: scaling exponent (ts) and critical water content (θc). In this study, we explored the new insights into the correlation between soil thermal conductivity and water retention using the P‐EMA and van Genuchten models. The θcwas strongly correlated to selected soil hydraulic and physical properties, such as water contents at wilting point (θpwp), inflection point (θi), and hydraulic continuity (θhc) determined from measured SWRCs for a 23‐soil calibration dataset. The established relationships were then evaluated on a seven‐soil validation dataset to estimate θc. Results confirmed their robustness with root mean square error ranging from 0.011 to 0.015 cm3cm−3, MAE ranging from 0.008 to 0.013 cm3cm−3, andR2of 0.98. Further discussion investigated the underlying mechanism for the correlation between θcwith θhcwhich dominate both heat transfer and water flow. More importantly, this study revealed the possibility to further investigate the general relationship between λ(θ) and SWRC data in the future. 
    more » « less
  2. Abstract Exotic annual grass invasions in water‐limited systems cause degradation of native plant and animal communities and increased fire risk. The life history of invasive annual grasses allows for high sensitivity to interannual variability in weather. Current distribution and abundance models derived from remote sensing, however, provide only a coarse understanding of how species respond to weather, making it difficult to anticipate how climate change will affect vulnerability to invasion. Here, we derived germination covariates (rate sums) from mechanistic germination and soil microclimate models to quantify the favorability of soil microclimate for cheatgrass (Bromus tectorumL.) establishment and growth across 30 years at 2662 sites across the sagebrush steppe system in the western United States. Our approach, using four bioclimatic covariates alone, predicted cheatgrass distribution with accuracy comparable to previous models fit using many years of remotely‐sensed imagery. Accuracy metrics from our out‐of‐sample testing dataset indicate that our model predicted distribution well (72% overall accuracy) but explained patterns of abundance poorly (R2 = 0.22). Climatic suitability for cheatgrass presence depended on both spatial (mean) and temporal (annual anomaly) variation of fall and spring rate sums. Sites that on average have warm and wet fall soils and warm and wet spring soils (high rate sums during these periods) were predicted to have a high abundance of cheatgrass. Interannual variation in fall soil conditions had a greater impact on cheatgrass presence and abundance than spring conditions. Our model predicts that climate change has already affected cheatgrass distribution with suitable microclimatic conditions expanding 10%–17% from 1989 to 2019 across all aspects at low‐ to mid‐elevation sites, while high‐ elevation sites (>2100 m) remain unfavorable for cheatgrass due to cold spring and fall soils. 
    more » « less
  3. Abstract Debris flows are powered by sediment supplied from steep hillslopes where soils are often patchy and interrupted by bare‐bedrock cliffs. The role of patchy soils and cliffs in supplying sediment to channels remains unclear, particularly surrounding wildfire disturbances that heighten debris‐flow hazards by increasing sediment supply to channels. Here, we examine how variation in soil cover on hillslopes affects sediment sizes in channels surrounding the 2020 El Dorado wildfire, which burned debris‐flow prone slopes in the San Bernardino Mountains, California. We focus on six headwater catchments (<0.1 km2) where hillslope sources ranged from a continuous soil mantle to 95% bare‐bedrock cliffs. At each site, we measured sediment grain size distributions at the same channel locations before and immediately following the wildfire. We compared results to a mixing model that accounts for three distinct hillslope sediment sources distinguished by local slope thresholds. We find that channel sediment in fully soil‐mantled catchments reflects hillslope soils (D50 = 0.1–0.2 cm) both before and after the wildfire. In steeper catchments with cliffs, channel sediment is consistently coarse prior to fire (D50 = 6–32 cm) and reflects bedrock fracture spacing, despite cliffs representing anywhere from 5% to 95% of the sediment source area. Following the fire, channel sediment size reduces most (5‐ to 20‐fold) in catchments where hillslope sources are predominantly soil covered but with patches of cliffs. The abrupt fining of channel sediment is thought to facilitate postfire debris‐flow initiation, and our results imply that this effect is greatest where bare‐bedrock cliffs are present but not dominant. A patchwork of bare‐bedrock cliffs is common in steeplands where hillslopes respond to channel incision by landsliding. We show how local slope thresholds applied to such terrain aid in estimating sediment supply conditions before two destructive debris flows that eventually nucleated in these study catchments in 2022. 
    more » « less
  4. Abstract Background and aimsPlant interactions with soil microbial communities are critical for understanding plant health, improving horticultural and agricultural outcomes, and maintaining diverse natural communities. In some cases, disease suppressive soils enhance plant survival in the presence of pathogens. However, species-specific differences and seasonal variation complicate our understanding of the drivers of soil fungal communities and their consequences for plants. Here, we aim to describe soil fungal communities acrossRhododendronspecies and seasons as well as the test for fungal indicators ofRhododendronspecies in the soil. Further, we test possible mechanisms governing disease suppressive soils to the oomycete pathogenPhytophthora cinnamomi. Variation in disease susceptibility to this pathogen across species and clades allows us to test for possible fungal drivers of disease suppressive soils. MethodsWe conducted high throughput sequencing of the fungal communities found in soil collected under 14Rhododendronspecies and across 2 seasons (April, October) at two sites in Ohio, USA. Phylogenetic analyses were used to ask whether fungal community composition correlated with increased plant survival with the addition of whole soil communities from a prior greenhouse experiment. ResultsEffects ofRhododendronspecies (R2 = 0.13), season (R2 = 0.01) and their interaction on fungal communities (R2 = 0.11) were statistically significant. Fungal community composition negatively correlated with survival following exposure to whole soil microbial communities, though this result depended on the presence ofR. minus. Forty-fiveTrichodermataxa were identified across our soil samples, and someTrichodermawere significantly associated with particularRhododendronspecies (e.g.Trichoderma atroviridewas associated withR. molle) in indicator species analyses. ConclusionThe correlation between plant responses to soil biotic communities and fungal community composition, as well as the presence of potential beneficial taxa such asTrichodermaand mycorrhizal fungi, are consistent with fungal-mediated survival benefits from the pathogenPhytophthora cinnamomi. 
    more » « less
  5. Soil nitrogen (N) is an important driver of plant productivity and ecosystem functioning; consequently, it is critical to understand its spatial variability from local-to-global scales. Here we provide a quantitative assessment of the three-dimensional spatial distribution of soil N across the conterminous United States (CONUS) using a digital soil mapping (DSM) approach. We used a random forest-regression kriging algorithm to predict soil N concentrations and associated uncertainty across six soil depths (0-5, 5-15, 15-30, 30-60, 60-100, 100-200 cm) at 5 km spatial grids. Across CONUS, there is a strong spatial dependence of soil N, where soil N concentrations decrease but uncertainty increases with soil depth. Soil N was higher in Pacific Northwest, Northeast, and Great Lakes National Ecological Observatory Network (NEON) ecoclimatic domains. Model uncertainty was higher in Atlantic Neotropical, Southern Rockies/Colorado Plateau and Southeast NEON domains. We also compared our soil N predictions with satellite-derived gross primary production (GPP) and forest biomass from the National Biomass and Carbon Dataset. Finally, we used uncertainty information to propose optimized locations for designing future soil surveys and found that the Atlantic Neotropical, Pacific Northwest, Pacific Southwest, and Appalachian/Cumberland Plateau NEON domains may require larger survey efforts. We highlight the need to increase knowledge of biophysical factors regulating soil processes at deeper depths to better characterize the three-dimensional space of soils. Our results provide a national benchmark regarding the spatial variability and uncertainty of soil N and reveal areas in need of a better representation.</p></p>This dataset includes all covariates used for modeling soil Nitrogen, the training data, and the modeling output. The output represents raster files at 5km resolution of soil N at different depths and associated model uncertainty.</p></p>Main reference:</p>Smith EM, Guevara M, Tarin T, Pouyat R, Vargas R. Spatial variability and uncertainty of soil nitrogen across the conterminous United States (in review). Ecosphere.</p> 
    more » « less