Rainfall simulation and overland-flow experiments enhance
understanding of surface hydrology and erosion processes, quantify runoff
and erosion rates, and provide valuable data for developing and testing
predictive models. We present a unique dataset (1021 experimental plots) of
rainfall simulation (1300 plot runs) and overland-flow (838 plot runs)
experimental plot data paired with measures of vegetation, ground cover, and
surface soil physical properties spanning point to hillslope scales. The
experimental data were collected at three sloping sagebrush (Artemisia spp.) sites in
the Great Basin, USA, each subjected to woodland encroachment and with
conditions representative of intact wooded shrublands and 1–9 years following
wildfire, prescribed fire, and/or tree cutting and shredding tree-removal
treatments. The methodologies applied in data collection and the cross-scale
experimental design uniquely provide scale-dependent, separate measures of
interrill (rain splash and sheet flow processes, 0.5 m2 plots) and
concentrated overland-flow runoff and erosion rates (∼9 m2 plots), along with collective rates for these same processes
combined over the patch scale (13 m2 plots). The dataset provides a
valuable source for developing, assessing, and calibrating/validating runoff
and erosion models applicable to diverse plant community dynamics with
varying vegetation, ground cover, and surface soil conditions. The
experimental data advance understanding and quantification of surface
hydrologic and erosion processes for the research domain and potentially for
other patchy-vegetated rangeland landscapes elsewhere. Lastly, the unique
nature of repeated measures spanning numerous treatments and timescales
delivers a valuable dataset for examining long-term landscape vegetation,
soil, hydrology, and erosion responses to various management actions, land
use, and natural disturbances. The dataset is available from the US
Department of Agriculture National Agricultural Library at
https://data.nal.usda.gov/search/type/dataset (last access: 7 May 2020) (doi: 10.15482/USDA.ADC/1504518; Pierson et al., 2019).
Introduction
Rangelands are one of the most common occurring sparsely vegetated wildland
landscapes around the world. These lands cover about half of the world's
land surface and about 31 % (>300 million ha) of the land
surface in the US (Havstad et al., 2009). The patchy vegetation structure
typical to these water-limited landscapes regulates connectivity of runoff
and erosion sources and processes and thus controls hillslope-scale runoff
and sediment transport (Pierson et al., 1994; Wainwright et al., 2000;
Wilcox et al., 2003; Ludwig et al., 2005). Runoff and erosion in isolated
bare patches on well-vegetated rangelands occur as splash–sheet (rain splash
and sheet flow) processes. Sediment entrained by raindrops and shallow
sheet flow in bare patches typically moves a limited distance downslope
before deposition immediately upslope of and within vegetated areas (Emmett,
1970; Reid et al., 1999; Puigdefábregas, 2005; Pierson and Williams,
2016). Disturbances such as intensive land use, plant community transitions,
and wildfire can alter this resource-conserving vegetation structure and
thereby facilitate increases in runoff and soil loss through enhanced
connectivity of overland-flow and sediment sources during rainfall events
(Davenport et al., 1998; Wilcox et al., 2003; Pierson et al., 2011; Williams
et al., 2014a, 2014b, 2018). The negative ramifications of woody plant
encroachment and wildfire have been extensively studied on rangelands around
the world, and this work has advanced understanding of runoff and erosion
processes for these commonly occurring ecosystems (Schlesinger et al., 1990;
Wainwright et al., 2000; Shakesby and Doerr, 2006; Shakesby, 2011; Pierson
and Williams, 2016). Recent widespread plant community transitions and
trends in wildfire activity and associated amplified runoff and erosion
rates spanning rangelands to dry forests throughout the western US (Williams
et al., 2014b) and elsewhere (Shakesby, 2011) underpin a need for compiling
data sources that further contribute to process understanding and improved
parametrization of rangeland hydrology and erosion predictive technologies.
Sagebrush rangelands in the western US are an extensive (∼300 000 km2) and important vegetation type that have undergone substantial
degradation associated with encroachment by pinyon (Pinus spp.) and juniper
(Juniperus spp.) woodlands, invasions of fire-prone annual cheatgrass (Bromus tectorum L.), and
altered fire regimes (Davies et al., 2011; Miller et al., 2011, 2019).
Pinyon and juniper woodland encroachment of sagebrush vegetation can have
negative hydrologic impacts (Miller et al., 2005; Petersen and Stringham,
2008; Pierson et al., 2007, 2010; Petersen et al., 2009;
Williams et al., 2014a, 2018). Encroaching trees outcompete understory
sagebrush and herbaceous vegetation over time and thereby increase bare
ground and connectivity of runoff and sediment sources (Miller et al., 2000; Bates et al., 2000, 2005; Petersen et al., 2009; Pierson et
al., 2010; Roundy et al., 2017). Extensive well-connected bare patches in
the later stages of woodland encroachment propagate broadscale runoff
generation and soil loss during storms events. Runoff from splash–sheet
processes during these events combines along hillslopes to form concentrated
overland flow with high sediment detachment rates and ample transport
capacity (Pierson et al., 2010; Williams et al., 2014a, 2016c). Amplified
soil loss over time perpetuates a woodland ecological state and long-term
site degradation (Petersen et al., 2009). Land managers commonly employ
various mechanical treatments and prescribed and natural fires to reduce
tree cover and reestablish sagebrush vegetation and associated
resource-conserving hydrologic function (Bates et al., 2000, 2005, 2014, 2017; Pierson
et al., 2007; Miller et al., 2014; Roundy et al., 2014;
Williams et al., 2018). However, managers are challenged
with predicting potential vegetation and ecohydrologic effects of tree
removal across diverse woodland landscapes and with determining the
appropriate type and timing of available treatment options. Invasions of
fire-prone cheatgrass following prescribed and natural fires are
particularly problematic. This annual grass commonly invades open patches on
woodlands at lower elevations or on warmer sites, subsequently increases
wildfire frequency, and potentially promotes long-term loss of surface soil
and nutrients associated with recurrent burning and fire-induced runoff
events (Pierson et al., 2011; Wilcox et al., 2012; Williams et al., 2014b).
Land managers around the world need improved understanding of runoff and
erosion processes for the various disturbances common to rangelands and need
improved tools for predicting responses to and making decisions on a host of
management alternatives. Managers rely on local understanding and conceptual
and quantitative science-based models to aid management decisions. Local
knowledge is often variable, and data necessary to populate conceptual and
science-based models are likewise limited given vast rangeland domain.
Vegetation and ground cover inventories and field-based experiments are
primary resources for informing conceptual models (Petersen et al., 2009;
Chambers et al., 2014, 2017; Williams et al., 2016a).
Rainfall simulation and overland-flow experiments likewise provide data for
developing, evaluating, and enhancing quantitative hydrology and erosion
predictive technologies (Flanagan and Nearing, 1995; Robichaud et al., 2007;
Wei et al., 2009; Nearing et al., 2011; Al-Hamdan et al., 2012a, 2012b,
2013, 2015, 2017; Hernandez et al., 2017). To address this need, we present an
ecohydrologic dataset containing 1021 experimental plots. The dataset
consists of rainfall simulation (1300 plot runs, 0.5 to 13 m2
scales) and overland-flow (838 plot runs, ∼9 m2 scale)
experimental data with paired measures of vegetation, ground cover, and
surface soil physical properties spanning point to hillslope scales (Pierson
et al., 2019). The experimental data were collected at multiple sagebrush
rangelands in the Great Basin, USA, each with woodland encroachment,
sampled in untreated conditions, and following fire and mechanical
tree-removal treatments over a 10-year period. The dataset therefore
represents diverse vegetation, ground cover, and surface soil conditions
common to undisturbed and disturbed rangelands in the western US and
elsewhere. The resulting dataset contributes to both process-based knowledge
and provision of data for populating, evaluating, and improving conceptual
and quantitative hydrology and erosion models.
Study sites and experimental design
A series of vegetation, soils, rainfall simulation (Figs. 1 and 2a–c),
and overland-flow experiments (Fig. 2d–e) were completed at three pinyon
and juniper woodlands historically vegetated as sagebrush shrublands. The
study sites were selected from a network of sites as part of a larger study
on the ecological impacts of invasive species and woodland encroachment into
sagebrush ecosystems and the effects of sagebrush restoration practices, the
Sagebrush Steppe Treatment Evaluation Project (SageSTEP, http://www.sagestep.org/, last access: 7 May 2020).
Study site climate, physical, and vegetation attributes are provided in
Table 1. All data were collected in summer months in years 2006–2015, with
sampling years varying by site and by treatment area within each site (see
Table 2). Vegetation and ground cover were patchy and sparse at the sites
when the study began in 2006 (Table 1). Tree-removal treatments (prescribed
fire, tree cutting, tree shredding (bullhog)) were applied at the Marking
Corral and Onaqui sites in 2006 (late summer and autumn) to evaluate
effectiveness of pinyon and juniper removal in reestablishing sagebrush
vegetation and ground cover, improving hydrologic function, and reducing
erosion rates. The Castlehead site burned by wildfire in summer 2007 before
tree-removal treatments could be applied, and wildfire was assessed as a
prescribed natural-fire tree-removal treatment for that site. At all three
sites, a cut tree (downed tree) treatment was placed across a subset of
large rainfall and overland-flow plot bases (Fig. 2e) within various
treatments to measure effects of downed trees on surface hydrology and
erosion processes. This additional treatment was applied in 2007 and 2015 to
some plots in cut treatment areas at Marking Corral and Onaqui and in 2008
and 2009 in unburned areas at Castlehead. Treatment applications and
descriptions and the study experimental design are explained in earlier
papers by Pierson et al. (2010, 2013, 2014, 2015) and by Williams et al. (2014a, 2019a, 2020), and all treatments for each site each year are provided
in Table 2.
Topography, climate, soil, tree cover, and understory vegetation at
the Castlehead, Marking Corral, and Onaqui sites prior to treatments. Data
are from Pierson et al. (2010, 2015) or Williams et al. (2014a) except where
indicated by footnote.
Castlehead, Idaho, USA (42∘26′50′′ N, 116∘46′39′′ W)Marking Corral, Nevada, USA (39∘27′17′′ N, 115∘06′51′′ W)Onaqui, Utah, USA (40∘12′42′′ N, 112∘28′24′′ W)Woodland communitywestern juniper1single-leaf pinyon2/ Utah juniper3Utah juniper3Elevation (m) – aspect1750 – SE facing2250 – W to SW facing1720 – N to NE facingMean annual precip. (mm)364429942984Mean annual air temp. (∘C)7.446.949.24Slope (%)10–2510–1510–15Parent rockbasalt and welded tuff5andesite and rhyolite6sandstone and limestone7Soil associationMulshoe-Squawcreek-Gaib5Segura-Upatad-Cropper6Borvant7Depth to bedrock (m)0.5–1.050.4–0.561.0–1.57Soil surface texturesandy loam, 59 % sand, 37 % silt, 4 %claysandy loam, 66 % sand, 30 % silt, 4 %claysandy loam, 57 % sand, 37 % silt, 7 %clayTree canopy cover (%)8261152, 103263Trees per hectare815813292, 15034763Mean tree height (m)85.212.32, 2.432.43Juvenile trees per hectare92812962, 13931543Shrubs per hectare102981120654914Intercanopy bare ground (%)11886479Common understory plantsArtemisia tridentata Nutt. ssp. wyomingensis Beetle and Young; Artemisia nova A. Nelson; Artemisia tridentata Nutt. ssp. vaseyana (Rydb.) Beetle; Purshia spp.; Poa secunda J. Presl; Pseudoroegneria spicata (Pursh) A. Löve; Festuca idahoensis Elmer; and various forbs
1Juniperus occidentalis Hook.
2Pinus monophylla Torr. and Frém.
3Juniperus osteosperma [Torr.] Little.
4 Estimated from a 4 km grid for years 1989–2018 from Prism Climate
Group (2019).
5 Natural Resources Conservation Service (NRCS) (2003).
6 NRCS (2007).
7 NRCS (2006).
8 Trees >50 cm height:
values for Castlehead include data from
Williams et al. (2014a) and one additional year.
9 Trees 5 to 50 cm height: for Castlehead mean based on data from
Williams et al. (2014a) and one additional year.
10 Shrubs ≥ 5 cm height: for Castlehead mean based on data from
Williams et al. (2014a) and one additional year.
11 Intercanopy refers to the area between tree canopies consisting of
shrubs, grasses, and interspaces between plants (shrub–interspace zone).
Number of plots sampled by plot type (site characterization
vegetation plots and small-plot rainfall, large-plot rainfall, and overland-flow simulation plots) at each study site (Castlehead, Marking Corral, and
Onaqui) by treatment and microsite (small plots – tree coppice, shrub
coppice, and interspace; large plots and overland flow – tree zone and
shrub–interspace zone (intercanopy)) combination each year of the study.
Control refers to untreated areas at Marking Corral and Onaqui sites.
Unburned refers to areas immediately adjacent to, but outside of, the wildfire
area (burned treatment) at the Castlehead site. Downed tree subtreatments
(cut–downed tree and unburned–downed tree) refer to plots with a single
downed tree across each respective plot within the specified associated
treatment (cut or unburned). Tree and shrub coppice microsites are areas
underneath or previously (prior to treatment) underneath tree and shrub
canopy, respectively. Interspace microsites are areas between tree and shrub
coppice microsites. Tree zone microsites are areas underneath, or previously
underneath, and immediately adjacent (just outside canopy drip line) to a
tree canopy. Shrub–interspace zones are the areas between tree canopies,
collectively inclusive of shrub coppice and interspace microsites (the
intercanopy).
Photographs of small-plot rainfall simulator (a) and example
small rainfall plots on tree coppice (b), shrub coppice (c), and interspace
(d, e) microsites as applied in this study.
Images showing paired large rainfall plots during rainfall
simulations (a), experimental setup of paired large rainfall plot
simulation experiments (b), a fully bordered large rainfall simulation plot
on a tree coppice microsite (c), a borderless overland-flow simulation plot
and experiment on an intercanopy (shrub–interspace) microsite (d), and a
borderless overland-flow simulation plot with a cut, downed tree on an intercanopy microsite (e), all as respective examples as applied in this study.
A suite of biological and physical attributes at each site were measured at
point, small rainfall plot (0.5 m2), overland-flow plot
(∼9 m2), large rainfall plot (13 m2), and hillslope
plot (990 m2) scales. Soil bulk density of the near surface (0–5 cm
depth) was sampled as a point measure in interspace microsites between
plants, shrub coppice microsites underneath shrub canopies, and tree coppice
microsites underneath tree canopies. The bulk density sampling was
conducted by the compliant cavity method within all treatment areas 1–2 years after
respective treatments. Surface soil texture was quantified as a point
measure using grab samples (0–2 cm depth) from interspace, shrub coppice,
and tree coppice microsites within all treatment areas at Marking and Onaqui
in 2006 prior to treatments and within unburned and burned treatment areas
at Castlehead in 2008. Vegetation and ground cover were measured at
small rainfall, large rainfall, and overland-flow plot scales and at the
hillslope-scale pre- and posttreatment in all treatment areas at Marking
Corral and Onaqui as well as in unburned and burned treatment areas at Castlehead.
Vegetation and ground cover measures on rainfall simulation and overland-flow plots were used to evaluate resisting and driving forces on surface
hydrology and erosion processes and to quantify treatment effects on cover
components at those plot scales. Sampling of vegetation and ground cover on
rainfall simulation and overland-flow plots in untreated areas (control and
unburned) and treated areas varied by site and year as described in Table 2.
Vegetation and ground cover measures at the hillslope scale (site
characterization plots) were conducted to describe site level cover
conditions prior to and over time after treatment. Site characterization
plots were installed and sampled prior to treatment (2006) in all treatment
areas at Marking Corral and Onaqui and were resampled 1 year (2007) and 9 years
(2015) after treatment. Castlehead site characterization plots were
installed and sampled in unburned and burned areas 1 year after the fire
(2008) and were resampled the second year postfire (2009).
Rainfall simulations and overland-flow experiments were employed at the
different plot scales to quantify specific scale-dependent runoff and
erosion processes (Pierson et al., 2010; Williams et al., 2014a). Small-plot
rainfall simulations (Fig. 1) were applied to quantify runoff and erosion
by splash–sheet processes. Each small rainfall plot was installed, as
described by Pierson et al. (2010) and Williams et al. (2014a), to occur on
either a tree coppice, shrub coppice, or interspace microsite (Fig. 1b–e). Small plots at Marking Corral and Onaqui were installed and sampled
in control and all other treatment areas in 2006 before application of the
tree-removal treatments and were left in place for subsequent sampling 1 year
(2007), 2 years (2008), and 9 years (2015) after treatment. Small plots at
Castlehead were installed and sampled in unburned and burned areas 1 year
after the fire (2008) and left in place for subsequent sampling the second year after fire (2009). Large-plot rainfall simulations (Fig. 2a–b) were
used to quantify runoff and erosion from combined splash–sheet and
concentrated overland-flow processes. Each plot was installed, as described
by Pierson et al. (2010) and Williams et al. (2014a), on either a tree zone
(tree coppice and area just outside tree canopy drip line) or a
shrub–interspace zone (intercanopy area between tree canopies) inclusive of
shrub coppice and interspace microsites (Fig. 2). Large plots at Marking
Corral and Onaqui were installed and sampled in all treatment areas in 2006
immediately before treatment application (controls) and were extracted
following sampling. New plots were installed and sampled in treatment areas
at Marking Corral and Onaqui in 2007, 1 year posttreatment, and were then
extracted. Large rainfall plots at Castlehead were installed and sampled in
unburned and burned areas in 2008, 1 year after the fire, and were then
extracted. Overland-flow simulations (Fig. 2d–e) were conducted on large
rainfall plots (Fig. 2a–c) at Marking Corral and Onaqui in 2006 and 2007
immediately following respective rainfall simulations. Overland-flow simulations were conducted in control and treated areas at those sites in
2008 and 2015, but those plots were not subjected to rainfall simulation. Castlehead
overland-flow simulations in 2008, 1 year postfire, were run on large
rainfall simulation plots following rainfall simulations and, in 2009, 2 years
postfire, were run on newly installed plots without rainfall simulations.
Overland-flow experiments conducted on large rainfall simulation plots had
borders on all sides and contained a collection trough for runoff
measurement at the plot base (Fig. 2c; Pierson et al., 2010, 2013, 2015;
Williams et al., 2014a). Overland-flow simulations run independent of
rainfall-simulation experiments were conducted on borderless plots but
contained a runoff collection trough at the downslope plot base (Fig. 2d–e; Pierson et al., 2013, 2015; Williams et al., 2014a, 2019a, 2020).
Select foliar cover and ground cover measures on hillslope-scale
site characterization plots (990 m2) in cut and burned treatment areas
at the Marking Corral and Onaqui sites 1 year prior to tree removal (2006) and
1 year (2007) and 9 years (2015) after tree-removal treatments.
1 Data from Pierson et al. (2010) but restricted to plots in areas subsequently cut or burned at the respective site × treatment
combination.
2 Data from Williams et al. (2019a).
3 Rock fragments >5 mm in diameter.
4 Data from Williams et al. (2020).
Field methodsHillslope-scale site characterization plots
Understory vegetation and ground cover and overstory tree cover at the
hillslope scale at each site were sampled on 30m×33m site
characterization plots using a suite of line–point and belt transect methods
and various tree measures (see Pierson et al., 2010; Williams et al.,
2014a). Foliar and ground cover on each site characterization plot were
recorded for 60 points (50 cm spacing) along each of five line–point
transects (30 m in length; spaced 5–8 m apart) for a total of 300 sample
points per plot. Percent cover by each sampled cover type was derived for
each plot as the number of respective cover-type hits divided by the total
number of points sampled. Multiple canopy layers were possible, and therefore
the total foliar cover across all sampled cover types potentially exceeded
100 %. The number of live tree seedlings of 5–50 cm height and shrubs
exceeding 5 cm height were quantified along three belt transects on each
plot. Each of the three belt transects on each plot were centered along a
foliar/ground cover line–point transect, sized 2 m wide × 30 m
long and spaced 6 m apart. Shrub and tree seedling densities were
calculated for each plot as the total number of respective individuals
tallied along the three belt transects divided by total belt transect area
(180 m2). The number of live trees >0.5 m in height was
quantified for each plot, and tree height and minimum and maximum crown
diameters were measured for each live tree. A crown radius for each live
tree was derived as one-half the average of measured minimum and maximum
crown diameters. Individual tree crown area (tree cover) was calculated as
equivalent to the area of a circle, derived with the respective crown
radius. Total tree cover for each plot was quantified as the sum of measured
tree cover values on the plot.
Small rainfall simulation plots and experiments
Foliar cover, ground cover, and ground surface roughness on all
small rainfall plots were quantified using point frame methods explained in
Pierson et al. (2010). Foliar and ground cover on each plot were sampled at
15 points spaced 5 cm apart along each of seven transects spaced 10 cm apart
and oriented parallel to hillslope contour (105 sample points per plot).
Percent cover for each cover type sampled on each plot was derived from the
frequency of respective cover-type hits divided by the total number of
points sampled. Multiple canopy layers were allowed, and therefore total
foliar cover across all cover types potentially exceeded 100 %. A relative
ground surface height at each sample point on each plot was determined by a metal ruler as the distance between the ground surface and a level line (top
of point frame). Ground surface roughness for each plot was then derived as
the mean of standard deviations of ground surface heights for each of the
transects sampled on the respective plot. Litter depth on each plot was
measured along the outside edge of the two plot borders located
perpendicular to the hillslope contour. Measurements were made to the
nearest 1 mm using a metal ruler at four evenly spaced points (15 cm apart)
along the two plot borders. An average litter depth was derived for each
plot as the average of the eight litter depth measures.
Soil water repellency of the mineral soil surface and at depths near the
mineral soil surface (0–5 cm depths) was measured immediately adjacent
(∼50 cm away) to each small rainfall plot immediately before
rainfall simulation using the water drop penetration time (WDPT) method (see
Pierson et al., 2010). Litter and ash cover were carefully removed from the
mineral soil surface prior to application of the WDPT. Eight water drops
(∼3 cm spacing) were then placed on the mineral soil surface,
and the time required for infiltration of each drop was recorded up to a
300 s maximum. The WDPT was then repeated at 1 cm soil depth increments
until 5 cm soil depth was reached. For each sampled depth, 1 cm of soil was
excavated immediately underneath the previously sampled area, and the WDPT
procedure was repeated with eight drops. A mean WDPT for each sampled soil
depth on each plot was recorded as the average of the eight WDPT (s) samples
at the respective depth. Soils were classified as wettable where mean WDPT
<5 s, slightly water repellent where mean WDPT ranged from 5 to 60 s,
and strongly water repellent where mean WDPT>60 s.
Surface soil moisture and aggregate stability were also sampled for each
small rainfall plot prior to rainfall simulations. Soil samples were
collected at 0–5 cm depth immediately adjacent to each small rainfall plot
and were subsequently analyzed in the laboratory for gravimetric soil water
content. Some samples were excluded from the dataset due to poor sealing of
soil cans in the field. Aggregate stability of the surface soil on each plot
was determined using a modified sieve test on six soil peds approximately
2–3 mm thick and 6–8 mm in diameter (see Pierson et al., 2010). Each soil
ped sampled on each plot was assigned to one of the following classes, as defined by Herrick et al. (2005): (1) <10 % stable aggregates, 50 % structural integrity lost within 5 s; (2) <10 % stable aggregates, 50 % structural integrity lost within 5–30 s; (3) <10 % stable aggregates, 50 % structural integrity lost within 30–300 s;
(4) 10 %–25 % stable aggregates; (5) 25 %–75 % stable aggregates; or (6) 75 %–100 % stable aggregates. An average aggregate stability was derived for
each plot as the arithmetic mean of the classes assigned to the six
aggregate samples for the respective plot.
Example infiltration (a: Marking Corral; b: Onaqui),
calculated as applied rainfall minus measured runoff, and sediment discharge
(c: Marking Corral; d: Onaqui) time series data generated from a subset
of the small-plot rainfall simulation dataset. Example subdataset is from
wet-run rainfall simulations in untreated (cont) and burned (burn)
interspace (int), shrub coppice (shr), and tree coppice (tree) microsites at
the Marking Corral and Onaqui study sites 9 years following prescribed fire.
The data illustrate the long-term impacts of burning and associated changes
in surface conditions on infiltration and sediment discharge. Figure
modified from Williams et al. (2020).
Rainfall was applied to small rainfall plots at approximate intensities of
64 mm h-1 (dry run) and 102 mm h-1 (wet run) for 45 min as
explained in Pierson et al. (2010). The dry run was applied to dry
antecedent soil conditions, and the wet run was applied to wet soil
conditions, ∼30 min after the dry run. Rainfall was applied
to small rainfall plots by a Meyer and Harmon-type portable oscillating-arm
rainfall simulator fitted with 80–100 Veejet nozzles (Fig. 1a; Meyer and
Harmon, 1979; Pierson et al. 2010, 2013, 2014; Williams et al., 2014a,
2019a, 2020). The applied rainfall kinetic energy (200 kJ ha-1 mm-1) and raindrop size (2 mm) were within approximately 70 kJ ha-1 mm-1 and 1 mm respectively of values reported for natural
convective rainfall (Meyer and Harmon, 1979). Rainfall amount applied to
each plot during rainfall simulation was estimated by integrating a pan
catch of a 5 min calibration run prior to each rainfall simulation plot run.
Total rainfall amount was estimated on plots where debris and/or vegetation
prevented placement of calibration pans. In such cases, the estimated
rainfall amount was derived as the average of all calibration runs for the
respective simulation date. Timed plot runoff samples were collected at
1–3 min intervals throughout each 45 min rainfall simulation and were
subsequently analyzed in the laboratory for runoff volume and sediment
concentration. Cumulative runoff and sediment amounts were obtained for each
runoff sample by weighing the sample before and after drying at
105 ∘C (Pierson et al., 2010). Runoff samples were not filtered at
any stage of laboratory processing. A mean runoff rate (mm h-1 and L min-1) was derived for each sample interval as the interval runoff
divided by the interval time. Sediment discharge (g s-1) for each
sample interval was calculated as the cumulative sediment for the sample
interval divided by the interval time. Sediment concentration for each
sample interval was obtained by dividing cumulative sediment by cumulative
runoff (g L-1). Some field samples were discarded from the final
dataset because of laboratory errors or various issues noted on field
data sheets (e.g., spillage and bottle overrun).
Example relationships/correlations in large rainfall plot
cumulative runoff and sediment yield for unburned (untreated (unb) and cut
(cut) treatments) and burned (burn) tree (tree) and intercanopy
(shrub–interspace, shr-int) plots at the Castlehead site (a) and bare ground
(bare soil plus rock cover) and sediment yield for unburned (unb) and cut
treatment (cut) tree and intercanopy plots across all study sites
(Castlehead, Marking Corral, and Onaqui) (b). The relationship in runoff and
sediment yield (a) demonstrates the initial (1 year) impact of burning on
sediment availability and elevated sediment delivery (for tree coppices in
this study) as commonly reported in fire studies (Pierson and Williams,
2016). The relationship in bare ground and sediment yield (b) shows the
typical increase in sediment yield where bare ground exceeds 50 %–60 % as
commonly reported for rangelands (Pierson et al., 2008, 2009; Williams et
al., 2014b). Figures modified from Pierson et al. (2013) and Williams et al. (2014a).
Example relationships/correlations in runoff and bare ground (bare
soil plus rock cover) (a), cumulative sediment and overland-flow velocity
(b), and overland-flow velocity and runoff (c) derived from a subset of the
overland-flow dataset for the Marking Corral and Onaqui sites, as presented in
Williams et al. (2019a). Data from overland-flow simulations on
untreated/control (cont) plots, cut treatment (cut) plots without and with a cut, downed tree (cut–downed tree), and bullhog plots (bullhog, Onaqui site
only) in tree (tree) and intercanopy (shrub–interspace, shr-int) microsites
9 years after respective tree-removal treatments. The data demonstrate that,
for the studied conditions, runoff is largely regulated by bare ground,
sediment delivery is controlled by flow velocity, and flow velocity is
strongly correlated with the amount or runoff.
Large rainfall simulation plots and experiments
Vegetation and ground cover were measured on large rainfall simulation plots
using line–point methods as described by Pierson et al. (2010) and Williams
et al. (2014a). Foliar cover and ground cover on large rainfall plots were
recorded for 59 points with 10 cm spacing along each of five transects (6 m
long, spaced 40 cm apart) oriented perpendicular to the hillslope contour, with 295 sample points per plot. The percentage cover by each sampled cover type
for each plot was derived as the number of point contacts or hits for each
respective life-form divided by the total number of points sampled on the
respective plot. Multiple canopy layers were allowed, and therefore total
foliar cover across all sampled cover types potentially exceeded 100 %.
Cut trees placed on a subset of rainfall simulation plots (see experimental
design above) were excluded from foliar and ground cover measurements.
However, various attributes of downed trees (e.g., length (height) and crown
width)
were measured and are reported. Ground surface roughness for
each plot was calculated as the average of the standard deviations of ground
surface heights measured across the line–point cover transects. The relative
ground surface height at each sample point was calculated as the distance
between a survey transit level line above the point and the ground surface.
Distances in excess of 20 cm between plant canopies (canopy gaps) and plant
bases (basal gaps) were measured along each of the line–point transects on
each plot. Average canopy and basal gap sizes were calculated for each plot
as the mean of all respective gaps measured in excess of 20 cm.
Additionally, maximum canopy and basal gap sizes were calculated for each
plot as the maximum of all respective gaps measured in excess of 20 cm.
Percentages of canopy gaps and basal gaps representing 50 cm incremental gap
classes (i.e., 51–100, 101–150 cm, etc.) were derived for each transect
and averaged across the transects on each plot to determine gap-class plot means.
Rainfall was applied to pairs of large rainfall plots (Fig. 2a–b) at the
same dry-run and wet-run target rates and sequence and durations as
described above for small rainfall plots (Pierson et al., 2010; Williams et
al., 2014a). Each paired rainfall simulation was run with a Colorado State
University (CSU)-type rainfall simulator (Fig. 2a–b; Holland, 1969). The
CSU-type design delivers rainfall energy at approximately 70 % of that for
a natural convective rainfall event and produces rainfall drop diameters
within approximately 1 mm of natural rainfall (Holland, 1969; Neff, 1979).
The applied simulator design consists of seven stationary sprinklers evenly
spaced along each of the outermost borders of the respective rainfall plot pair, with each sprinkler elevated 3.05 m above the ground surface. Total
rainfall applied to large rainfall plots was quantified from the average of
six plastic rainfall depth gages organized in a uniform grid within each
plot. Runoff from direct rainfall on the large-plot collection troughs
(trough catch, Fig. 2b) was quantified by sampling collection trough
runoff before plot-generated runoff occurred. Once plot runoff occurred,
timed samples of runoff were collected at 1–3 min intervals throughout each
45 min simulation run and were subsequently analyzed in the laboratory for
runoff volume and sediment concentration as with small-plot rainfall
simulation runoff samples. Sample weights were adjusted to appropriately
account for trough catch, as described by Pierson et al. (2010). Some field
samples were discarded from the final dataset because of laboratory errors
or various issues noted on field data sheets (e.g., spillage and bottle overrun). Runoff and erosion rates were determined consistent with methods for small-plot rainfall simulations.
Soil texture and bulk density variables and data structure for
those measures for all study sites. Abbreviations in the table example are
as follows: juniper_cop refers to juniper coppice microsites,
shrub_cop refers to shrub coppice microsites, and
pinyon_cop refers to pinyon coppice microsites.
Example (subset) of vegetation and ground cover variables and data
structure for measures on hillslope-scale site characterization plots (990 m2) at the study sites. Abbreviations in the table example are as
follows: Fol. Cvr. refers to foliar cover, and JUOC refers to western
juniper (Juniperus occidentalis Hook.).
Example (subset) of rainfall simulation, vegetation, ground cover,
and soil variables and data structure for measures on small rainfall
simulation plots (0.5 m2) at the study sites. Abbreviations in the
table example are as follows: Fol. Cvr. refers to foliar cover, Grd. Cvr. refers to ground cover, WDPT refers to water drop penetration time,
shrub_cop refers to shrub coppice microsites,
pinyon_cop refers to pinyon coppice microsites, and
juniper_cop refers to juniper coppice microsites.
Example (subset) of rainfall simulation, vegetation, ground cover,
and soil variables and data structure for measures on large rainfall
simulation plots (13 m2) at the study sites. Abbreviations in the table
example are as follows: Fol. Cvr. refers to foliar cover, Grd. Cvr. refers
to ground cover, Avg. refers to average, juniper_cop refers
to juniper coppice microsites, and pinyon_cop refers to
pinyon coppice microsites.
Example (subset) of overland-flow, vegetation, and ground cover
variables and data structure for measures on overland-flow simulation plots
(∼9 m2) at the study sites. Abbreviations in the table
example are as follows: Avg. refers to average, juniper_cop
refers to juniper coppice microsites, and pinyon_cop refers
to pinyon coppice microsites.
Avg.Avg.Avg.Avg.Avg.Avg.Avg.Avg.TreatedwidthwidthwidthvelocityvelocityvelocitycanopybasalTreatment(yes15 L min-130 L min-145 L min-115 L min-130 L min-145 L min-1gapgapPlot IDSiteYearareaor no)Micrositeat 3 m (cm)at 3 m (cm)at 3 m (cm)–(m s-1)(m s-1)(m s-1)(cm)(cm)RI_MC_CUT37Marking Corral2006CutNojuniper_cop21028–-9990.0290.0366792RI_MC_CUT38Marking Corral2006CutNojuniper_cop03032–0-9990.05878156RI_MC_CUT39Marking Corral2006CutNointercanopy423343–0.070.1220.1487093RI_MC_CUT40Marking Corral2006CutNointercanopy503853–0.0850.1270.13155100RI_MC_CUT41Marking Corral2006CutNointercanopy376159–0.0280.0670.10759106RI_MC_CUT42Marking Corral2006CutNointercanopy476152–0.050.0660.186109RI_MC_CUT43Marking Corral2006CutNopinyon_cop052102–0-9990.038333333RI_MC_CUT44Marking Corral2006CutNopinyon_cop0-999-999–0-999-999284292RI_MC_CUT45Marking Corral2006CutNopinyon_cop00-999–00-999131172RI_MC_CUT46Marking Corral2006CutNopinyon_cop02432–00.0330.04488175RI_MC_CUT47Marking Corral2006CutNointercanopy646452–0.0620.0980.1277985–––––––––––––––RI_ON_CUT131Onaqui2015CutYesintercanopy144148158–0.0510.0840.1824646RI_ON_CUT133Onaqui2015CutYesintercanopy016582–00.0540.0736534RI_ON_CUT134Onaqui2015CutYesintercanopy02936–00.0620.0864858Overland-flow simulation plots and experiments
Vegetation and ground cover on overland-flow plots were measured using
methods consistent with those on large rainfall simulation plots. For
overland-flow plots that underwent rainfall simulation, foliar and ground
cover measures were derived from the large rainfall plot line–point transect
data but were restricted to the lower 4 m of the respective plots. Foliar
and ground cover on overland-flow plots not subjected to rainfall
simulations were recorded at 24 points with 20 cm spacing, along each of
nine line–point transects (4.6 m in length, spaced 20 cm apart) oriented
perpendicular to the hillslope contour, for a total of 216 points per plot.
Percentage cover for each cover type sampled on each plot was derived from
the number of point contacts or hits for each respective cover type divided
by the total number of points sampled within the plot. As on large rainfall
plots, total foliar cover across all cover types potentially exceeded
100 % given multiple canopy layers were allowed. Cut trees placed on a
subset of overland-flow plots (see experimental design above) were excluded
from foliar and ground cover measurements. However, various attributes of
downed trees (e.g., length (height) and crown width) were measured and
are reported. The ground surface roughness for each overland-flow plot was
calculated as the average of the standard deviations of the ground surface
heights across the foliar/ground cover line–point transects. The relative
ground surface height at each cover sample point was calculated as the
distance between a survey transit level line above the respective sample
point and the ground surface. Canopy and basal gaps exceeding 20 cm on
overland-flow plots were recorded along each line–point transect. Average
and maximum canopy and basal gaps were derived consistent with methods for
large rainfall simulation plots. Percentages of canopy and basal gaps
representing 50 cm incremental gap classes (i.e., 51–100, 101–150 cm,
etc.) were derived for each transect and averaged across the transects on
each plot to determine gap-class plot means, similar to large rainfall plots.
Datalogger-controlled flow regulators (see Pierson et al., 2010, 2013, 2015;
Williams et al., 2014a, 2019a, 2020) were used to apply concentrated flow
release rates of 15, 30, and 45 L min-1 to each overland-flow plot.
Flow was routed into and through a metal box filled with Styrofoam pellets
and was released through a 10 cm wide mesh-screened opening at the box base
(Fig. 2d; see Pierson et al., 2010). Each flow release on each plot was
applied for 12 min from a single release point located 4 m upslope of the
collection trough apex. Flow release rate progression on each plot was
consecutive from 15 to 30 to 45 L min-1. Flow
samples were collected at various time intervals (usually 1 to 2 min)
for each 12 min simulation at each release rate. As with rainfall simulation
samples, runoff samples were taken to the laboratory, weighed, oven-dried at
105 ∘C, and then reweighed to determine the runoff rate and
sediment concentration. Also as noted above for rainfall simulation runoff
samples, a small number of runoff samples were discarded because of
laboratory errors or various issues noted on field data sheets (e.g.,
spillage and bottle overrun). Runoff and sediment variables for each flow
release rate were calculated for an 8 min time period starting at runoff
initiation. The resulting 8 min runoff and sediment variables were derived
as explained for the 45 min rainfall simulations. The velocity of overland
flow was measured using a concentrated salt tracer applied into the flow and
electrical conductivity probes to track the mean transit time of the tracer
over a set flow path length (usually 2 m; Pierson et al., 2010, 2013, 2015;
Williams et al., 2014a, 2019a, 2020). The width, depth, and a total rill
area width (TRAW) of overland flow were measured along flow cross sections 1, 2, and 3 m downslope from the flow release point (Pierson et al.,
2010). The TRAW variable represents the total width between the outermost
edges of the outermost flow paths at the respective cross section (see
Pierson et al., 2008). Overland-flow simulations conducted on large rainfall
simulation plots at Marking Corral and Onaqui in 2006 and 2007 and at
Castlehead in 2008 were run approximately 2 h after respective
rainfall simulations. Overland-flow simulations on plots not subjected to
rainfall simulation at Marking Corral and Onaqui in 2008 and 2015 and at
Castlehead in 2008 were conducted on soils prewet with a gently misting
sprinkler (see Pierson et al., 2013, 2015; Williams et al., 2014a, 2019a, 2020).
Example (subset) of time series runoff and sediment data from
small-plot rainfall simulations (0.5 m2) at the study sites.
Abbreviations in the table example are as follows: Conc. refers to
concentration, and shrub_cop refers to shrub coppice
microsites.
Example (subset) of time series runoff and sediment data from
large-plot rainfall simulations (13 m2) at the study sites.
Abbreviations in the table example are as follows: Conc. refers to
concentration, and juniper_cop refers to juniper coppice
microsites.
RainfallRunoffSampleDowned–ratestartSimulationfillSedimentSedimentTreatmentTreatedcut treeRun(mmtimetimetimeRunoffconc.RunoffdischargePlot IDSiteYeararea(yes or no)Microsite(yes or no)typeh-1)(mm:ss)(mm:ss)(s)(L min-1)(g L-1)(mm h-1)(g s-1)LP_MC_CUT37Marking Corral2006CutNojuniper_copNoDry_run5208:1500:0000000LP_MC_CUT37Marking Corral2006CutNojuniper_copNoDry_run5208:1508:1400000LP_MC_CUT37Marking Corral2006CutNojuniper_copNoDry_run5208:1509:05200.29419.081.3570.094LP_MC_CUT37Marking Corral2006CutNojuniper_copNoDry_run5208:1510:08150.46414.562.1420.113LP_MC_CUT37Marking Corral2006CutNojuniper_copNoDry_run5208:1512:08150.6278.742.8940.091LP_MC_CUT37Marking Corral2006CutNojuniper_copNoDry_run5208:1514:08160.47611.112.1960.088LP_MC_CUT37Marking Corral2006CutNojuniper_copNoDry_run5208:1516:08150.62510.692.8830.111LP_MC_CUT37Marking Corral2006CutNojuniper_copNoDry_run5208:1518:08150.55410.472.5560.097LP_MC_CUT37Marking Corral2006CutNojuniper_copNoDry_run5208:1520:08150.60912.212.8120.124––––––––––––––––LP_CH_BURN30Castlehead2008BurnYesintercanopyNoWet_run11001:0930:081515.6474.6872.2161.22LP_CH_BURN30Castlehead2008BurnYesintercanopyNoWet_run11001:0933:081513.8194.4163.7811.015LP_CH_BURN30Castlehead2008BurnYesintercanopyNoWet_run11001:0936:081514.1985.7865.5291.368LP_CH_BURN30Castlehead2008BurnYesintercanopyNoWet_run11001:0939:081516.6665.6576.9191.569LP_CH_BURN30Castlehead2008BurnYesintercanopyNoWet_run11001:0942:081514.2825.4865.9151.305
Example (subset) of time series runoff and sediment data from overland-flow simulations (∼9 m2) at the study sites.
Abbreviations in the table example are as follows: Conc. refers to
concentration, and juniper_cop refers to juniper coppice
microsites.
PlotAppliedSampleborderedRunoffRunoffRunoffoverlandSimulationfillSedimentTreatmentTreatedall sides15 L min-130 L min-145 L min-1flow ratetimetimeRunoffconc.Plot IDSiteYeararea(yes or no)Microsite(yes or no)(yes or no)(yes or no)(yes or no)(L min-1)(mm:ss)(s)(L min-1)(g L-1)RI_MC_CUT37Marking Corral2006CutNojuniper_copYesYesYesYes1500:00300.18113.49RI_MC_CUT37Marking Corral2006CutNojuniper_copYesYesYesYes1500:41150.471.62RI_MC_CUT37Marking Corral2006CutNojuniper_copYesYesYesYes1501:11150.6280.7RI_MC_CUT37Marking Corral2006CutNojuniper_copYesYesYesYes1502:31151.2650.66RI_MC_CUT37Marking Corral2006CutNojuniper_copYesYesYesYes1503:06151.6621.04RI_MC_CUT37Marking Corral2006CutNojuniper_copYesYesYesYes1503:41151.9760.2RI_MC_CUT37Marking Corral2006CutNojuniper_copYesYesYesYes3000:001511.18115.97RI_MC_CUT37Marking Corral2006CutNojuniper_copYesYesYesYes3000:451514.5510.61RI_MC_CUT37Marking Corral2006CutNojuniper_copYesYesYesYes3002:401518.7950.29–––––––––––––––RI_ON_CUT134Onaqui2015CutYesintercanopyNoNoYesYes4504:052014.55.51RI_ON_CUT134Onaqui2015CutYesintercanopyNoNoYesYes4504:552015.2155.56RI_ON_CUT134Onaqui2015CutYesintercanopyNoNoYesYes4505:452015.6945.49RI_ON_CUT134Onaqui2015CutYesintercanopyNoNoYesYes4508:352017.4265.41RI_ON_CUT134Onaqui2015CutYesintercanopyNoNoYesYes4510:352018.6785.44Data application
Subsets of the dataset have been used to improve understanding of rangeland
hydrologic and erosion processes, assess the ecohydrologic impacts of
wildland fire and management practices on sagebrush rangelands, and improve
and enhance rangeland hydrology and erosion models. Examples of data use for
such applications are presented in Figs. 3–5. Pierson et al. (2010)
applied pretreatment data across all plot scales and experiment types from
Marking Corral and Onaqui to evaluate the ecohydrologic impacts of woodland
encroachment on sagebrush rangelands. Studies by Pierson et al. (2014, 2015)
assessed the initial (first and second year) effects of prescribed fire
and mechanical tree-removal treatments on vegetation, ground cover, and
hydrology and erosion processes at Marking Corral and Onaqui. Williams et al. (2014a) applied vegetation, ground cover, rainfall simulation, and overland-flow experiments from unburned and burned areas at Castlehead to
evaluate the utility of fire to reverse the negative ecohydrologic impacts
of juniper encroachment on rangelands and to frame conceptual concepts on
process connectivity for burned and degraded rangelands (Fig. 4). Pierson
et al. (2013, 2015) evaluated the immediate effects of cut–downed trees
on runoff and erosion processes on woodlands. Williams et al. (2019a, 2019b,
2020) applied data from all experimental plot scales and methods in
untreated and treated areas at Marking Corral and Onaqui to evaluate the
long-term ecohydrologic impacts of prescribed fire and mechanical
tree-removal treatments on woodland-encroached sagebrush steppe (Table 3, Fig. 5).
Al-Hamdan et al. (2012a, 2012b, 2013, 2015, 2017) applied subsets of the
data to develop, test, and enhance various parameter estimation equations
for flow hydraulics and erodibility parameters in the Rangeland Hydrology
and Erosion Model (RHEM). Collectively, these studies have improved
understanding of rangeland hydrology and erosion processes and informed both
conceptual and quantitative models applicable to assessment and management
of diverse rangelands (McIver et al., 2014; Pierson and Williams, 2016;
Williams et al., 2016a, 2016b, 2016c, 2018; Hernandez et al., 2017).
Data availability
The full dataset is available from the US Department of Agriculture National Agricultural Library website at
https://data.nal.usda.gov/search/type/dataset (last access: 7 May 2020) (doi: 10.15482/USDA.ADC/1504518; Pierson et al., 2019). The
suite of files therein includes an abbreviated description and field
methods; a data dictionary; geographic information for study sites;
photographs of the study sites, field experiments, and experimental plots;
and data files for vegetation, ground cover, soils, and hydrology and erosion
time series measures spanning the associated plots scales. Subset examples
of the data files are shown in Tables 4 (site level soil particle size and
bulk density), 5 (site characterization plots), 6 (small rainfall plot
attributes), 7 (large rainfall plot attributes), 8 (overland-flow plot
attributes), 9 (small-plot rainfall simulation time series), 10 (large-plot
rainfall simulation time series), and 11 (overland-flow simulation time
series). Time series runoff and sediment data provided for rainfall
simulations and overland-flow experiments do not account for carryover
effects from one plot run to the next on a given plot in a given year (i.e.,
dry-run effects on wet-run simulations; effects of 15 L min-1 overland
flow releases on subsequent 30–45 L min-1 overland flow releases). Data
users should consider whether carryover effects impact respective
applications and make applicable adjustments to acquired data.
Summary and conclusions
Rangelands are uniquely managed using ecological principles. As such, our
functional understanding of regulating ecohydrologic processes, such as soil
conservation and runoff moderation, is limited by our ability to track
these processes in the context of interdependent land management decisions.
Pinyon–juniper encroachment into sagebrush shrublands and the resulting
management actions provide a model system for observing hydrologic processes
under disturbances and interventions typical of extensively managed
rangelands. To provide detailed understanding of ecohydrologic processes
under realistic management conditions, we collected long-term data at
multiple sites, spatial scales, and treatments. The combined dataset
includes 1021 experimental plots and contains vegetation, ground cover,
soils, hydrology, and erosion data spanning multiple spatial scales and
diverse vegetation, ground cover, and surface soil conditions from three
study sites and five different study years. The dataset includes 57
hillslope-scale vegetation plots (site characterization), 528 small rainfall
simulation plots, 146 large rainfall simulation plots, and 290 overland-flow
simulation plots. The hydrology and erosion experiments provide time series
data for small rainfall plot, large rainfall plot, and overland-flow plot
simulations. After excluding some time series rainfall and overland-flow
simulation data due to various lab and equipment failures, the final time
series dataset contains 1020 small rainfall, 280 large rainfall, and 838
overland-flow plot-run hydrographs and sedigraphs if plots without runoff
are retained. Retaining only plots that generated runoff results in a time
series dataset of 749 small rainfall, 251 large rainfall, and 719
overland-flow plot simulation hydrographs and sedigraphs. Overall, the
hydrology and erosion time series dataset totals to 2138
hydrographs/sedigraphs including plots with no runoff and 1719
hydrographs/sedigraphs for plots that generated runoff. The methodology
employed and resulting experimental data improve understanding of and
provide quantification of separate scale-dependent (e.g., rain splash and
sheet flow) and combined (e.g., interrill and concentrated flow/rill) surface
hydrology and erosion processes for sagebrush rangelands and pinyon and
juniper woodlands in the Great Basin before and after tree removal and for
sparsely vegetated sites elsewhere. This separate and combined experimental
approach yields a valuable data source for testing and improving isolated
process parameterizations in quantitative hydrology and erosion models. The
long-term nature of the dataset is unique and provides a substantial
database for populating conceptual ecological models of changes in
vegetation, ground cover conditions, and surface soils resulting from
management practices and disturbances. Likewise, the combined data on
short-term and long-term ecohydrologic impacts of management practices and
fire provide valuable insight on trends in ecohydrologic recovery of
rangeland ecosystems.
Author contributions
FBP, CJW, PRK, and OZA-H participated in the experimental design, data
collection and reduction, and compilation of the dataset and manuscript.
JCJ contributed to data reduction and compilation of the
dataset and manuscript. All authors contributed to revisions of the
submitted manuscript.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
This paper is contribution number 135 of the Sagebrush
Steppe Treatment Evaluation Project (SageSTEP, http://www.sagestep.org/, last access: 7 May 2020), funded by
the US Joint Fire Science Program, US Department of Interior (USDI) Bureau
of Land Management, and US National Interagency Fire Center. The authors thank the USDI Bureau of Land Management
and the US Department of Agriculture (USDA) Forest Service for implementation of the land management
treatments and site access in collaboration with the SageSTEP study. We are
also grateful for land access and infrastructural support provided by Mike
and Jeannie Stanford during our field experiments at the Castlehead site. We
thank Barry Caldwell and Zane Cram of the USDA Agricultural Research Service (ARS) Northwest Watershed
Research Center, Boise, ID, USA, for field support throughout the study. We
likewise thank Steve Van Vactor of the USDA ARS Northwest Watershed Research
Center for database support. We are grateful for field supervision of data
collection and laboratory work provided by Jaime Calderon, Matthew Frisby,
Kyle Lindsay, and Samantha Vega over various years of the research study. We
thank Ben Rau and the Desert Research Institute, Reno, Nevada, USA, for
assistance with processing soil samples. The USDA is an equal opportunity
provider and employer. Mention of a proprietary product does not constitute
endorsement by USDA and does not imply its approval to the exclusion of the
other products that may also be suitable.
Financial support
This research has been supported by the US Joint Fire Science Program; the US Department of Interior, Bureau of Land Management; the US National Interagency Fire Center; and the US Department of Agriculture, Agricultural Research Service.
Review statement
This paper was edited by Alexander Gelfan and reviewed by three anonymous referees.
References
Al-Hamdan, O. Z., Pierson, F. B., Nearing, M. A., Stone, J. J., Williams, C.
J., Moffet, C. A., Kormos, P. R., Boll, J., and Weltz, M. A.:
Characteristics of concentrated flow hydraulics for rangeland ecosystems:
Implications for hydrologic modeling, Earth Surf. Process. Landf.,
37, 157–168, 2012a.Al-Hamdan, O. Z., Pierson, F. B., Nearing, M. A., Williams, C. J., Stone, J.
J., Kormos, P. R., Boll, J., and Weltz, M. A.: Concentrated flow erodibility
for physically based erosion models: Temporal variability in disturbed and
undisturbed rangelands, Water Resour. Res., 48, W07504, 10.1029/2011WR011464, 2012b.
Al-Hamdan, O. Z., Pierson, F. B., Nearing, M. A., Williams, C. J., Stone, J.
J., Kormos, P. R., Boll, J., and Weltz, M. A.: Risk assessment of erosion
from concentrated flow on rangelands using overland flow distribution and
shear stress partitioning, Trans. ASABE, 56, 539–548, 2013.
Al-Hamdan, O. Z., Hernandez, M., Pierson, F. B., Nearing, M. A., Williams,
C. J., Stone, J. J., Boll, J., and Weltz, M. A.: Rangeland Hydrology and
Erosion Model (RHEM) enhancements for applications on disturbed rangelands,
Hydrol. Process., 29, 445–457, 2015.
Al-Hamdan, O. Z., Pierson, F. B., Nearing, M. A., Williams, C. J.,
Hernandez, H., Boll, J., Nouwakpo, S. K., Weltz, M. A., and Spaeth, K. E.:
Developing a parameterization approach for soil erodibility for the Rangeland Hydrology and Erosion Model (RHEM), Trans. Am.
Soc. Agr. Biol. Eng., 60, 85–94, 2017.
Bates, J. D., Miller, R. F., and Svejcar, T. J.: Understory dynamics in cut
and uncut western juniper woodlands, J. Range Manage., 53,
119–126, 2000.
Bates, J. D., Miller, R. F., and Svejcar, T.: Long-term successional trends
following western juniper cutting, Range. Ecol. Manage., 58,
533–541, 2005.Bates, J. D., Sharp, R. N., and Davies, K. W.: Sagebrush steppe recovery
after fire varies by development phase of Juniperus occidentalis woodland,
Int. J. Wildl. Fire, 23, 117–130, 2014.
Bates, J. D., Svejcar, T., Miller, R., and Davies, K. W.: Plant community
dynamics 25 years after juniper control, Range. Ecol. Manage.,
70, 356–362, 2017.
Chambers, J. C., Miller, R. F., Board, D. I., Pyke, D. A., Roundy, B. A.,
Grace, J. B., Schupp, E. W., and Tausch, R. J.: Resilience and resistance of
sagebrush ecosystems: implications for state and transition models and
management treatments, Range. Ecol. Manage., 67, 440–454, 2014.
Chambers, J. C., Maestas, J. D., Pyke, D. A., Boyd, C. S., Pellant, M., and
Wuenschel, A.: Using resilience and resistance concepts to manage persistent
threats to sagebrush ecosystems and greater sage-grouse, Range. Ecol.
Manage., 70, 149–164, 2017.
Davenport, D. W., Breshears, D. D., Wilcox, B. P., and Allen, C. D.: Viewpoint: Sustainability of pinon-juniper ecosystems – A unifying perspective of soil erosion thresholds, J. Range Manage., 51, 231–240, 1998.
Davies, K. W., Boyd, C. S., Beck, J. L., Bates, J. D., Svejcar, T. J., and
Gregg, M. A.: Saving the sagebrush sea: An ecosystem conservation plan for
big sagebrush plant communities, Biol. Conserv., 144, 2573–2584,
2011.
Emmett, W. W.: The hydraulics of overland flow on hillslopes, US Government
Printing Office, Washington, D.C., 69 pp., 1970.
Flanagan, D. C. and Nearing, M. A. USDA-Water Erosion Prediction Project
(WEPP) hillslope profile and watershed model documentation, NSERL Report No.
10, National Soil Erosion Research Laboratory, USDA-Agricultural Research
Service, West Lafayette, IN, USA, 298 pp., 1995.
Havstad, K. M., Peters, D. C., Allen-Diaz, B., Bartolome, J., Betelmeyer, B.
T., Briske, D., Brown, J., Brunsun, M., Herrick, J. E., Huntsinger, L.,
Johnson, P., Joyce, L., Pieper, R., Svejcar, A. J., and Yao, J.: The western
United Sates rangelands, a major resource, in: Grassland: Quietness and
Strength for a New American Agriculture, edited by: Wedin, W. F. and Fales,
S. L., American Society of Agronomy Inc., Crop Science Society of America
Inc., and Soil Science Society of America, Inc., Madison, WI, USA, 75–93,
2009.Hernandez, M., Nearing, M. A., Al-Hamdan, O. Z., Pierson, F. B., Armendariz,
G., Weltz, M. A., Spaeth, K. E., Williams, C. J., Nouwakpo, S. J., Goodrich,
D. C., Unkrich, C.L., Nichols, M. H., and Holifield Collins, C. D.: The Rangeland Hydrology and Erosion Model: A dynamic approach for predicting
soil loss on rangelands, Water Resour. Res., 53, 9368–9391,
10.1002/2017WR020651, 2017.
Herrick, J. E., Van Zee, J. W., Havstad, K. M., Burkett, L. M., and
Whitford, W. G.: Monitoring manual for grassland, shrubland, and savanna
ecosystems, Volume 1: Quick Start, USDA-Agricutural Research Service, Las
Cruces, NM, USA, 36 pp., 2005.
Holland, M. E.: Colorado State University experimental rainfall-runoff facility, design and testing of a rainfall system, Technical Report CER 69-70 MEH, Fort Collins, CO, USA, Colorado
State University, Colorado State University Experimental Station, 21 p., 1969.
Ludwig, J. A., Wilcox, B. P., Breshears, D. D., Tongway, D. J., and Imeson,
A. C.: Vegetation patches and runoff-erosion as interacting ecohydrological
processes in semiarid landscapes, Ecology, 86, 288–297, 2005.
McIver, J., Brunson, M., Bunting, S., Chambers, J., Doescher, P., Grace, J.,
Hulet, A., Johnson, D., Knick, S., Miller, R., Pellant, M., Pierson, F.,
Pyke, D., Rau, B., Rollins, K., Roundy, B., Schupp, E., Tausch, R., and
Williams, J.: A synopsis of short-term response to alternative restoration
treatments in sagebrush-steppe: The SageSTEP Project, Range. Ecol.
Manage., 67, 584–598, 2014.
Meyer, L. D. and Harmon, W. C.: Multiple-intensity rainfall simulator for erosion research on row sideslopes, Trans. ASAE, 22, 100–103, 1979.
Miller, R. F., Svejcar, T. J., and Rose, J. A.: Impacts of western juniper
on plant community composition and structure, J. Range Manage.,
53, 574–585, 2000.
Miller, R. F., Bates, J. D., Svejcar, T. J., Pierson, F. B., and Eddleman,
L. E.: Biology, ecology, and management of western juniper, Oregon State
University Agricultural Experiment Station Technical Bulletin 152, Oregon
State University, Oregon State University Agricultural Experiment Station,
Corvallis, OR, USA, 82 pp., 2005.
Miller, R. F., Knick, S. T., Pyke, D. A., Meinke, C. W., Hanser, S. E.,
Wisdom, M. J., and Hild, A. L.: Characteristics of sagebrush habitats and
limitations to long-term conservation, in: Greater Sage-grouse: Ecology and
Conservation of a Landscape Species and Its Habitats. Studies in Avian
Biology, Vol. 38, edited by: Knick, S. T. and Connelly, J. W., University
of California Press, Berkeley, CA, USA, 145–184, 2011.
Miller, R. F., Ratchford, J., Roundy, B. A., Tausch, R. J., Hulet, A., and
Chambers, J.: Response of conifer-encroached shrublands in the Great Basin
to prescribed fire and mechanical treatments, Range. Ecol.
Manage., 67, 468–481, 2014.
Miller, R. F., Chambers, J. C., Evers, L., Williams, C. J., Snyder, K. A.,
Roundy, B. A., and Pierson, F. B.: The ecology, history, ecohydrology, and
management of pinyon and juniper woodlands in the Great Basin and Northern
Colorado Plateau of the western United States, General Technical Report
RMRS-GTR-403, US Department of Agriculture, Forest Service, Rocky Mountain
Research Station, Fort Collins, CO, USA, 2019.
Nearing, M. A., Wei, H., Stone, J. J., Pierson, F. B., Spaeth, K. E., Weltz,
M. A., Flanagan, D. C., and Hernandez, M.: A rangeland hydrology and erosion
model, Trans. ASABE, 54, 901–908, 2011.
Neff, E. L.: Performance characteristics and field operation of two rainfall simulators, Washington D.C., USA, US Department of Agriculture, Agricultural Research Service, 42 p., 1979.
NRCS (Natural Resources Conservation Service), Soil survey of Owyhee County
area, Idaho, US Department of Agriculture, Natural Resources Conservation
Service, Washington, DC, USA, 2003.
NRCS (Natural Resources Conservation Service), Soil Survey Geographic
(SSURGO) database for Tooele Area, Utah – Tooele County and Parts of Box
Elder, Davis, and Juab Counties, Utah, White Pine and Elko Counties, Nevada,
US Department of Agriculture, Natural Resources Conservation Service, Fort
Worth, TX, USA, 2006.
NRCS (Natural Resources Conservation Service), Soil Survey Geographic
(SSURGO) database for Western White Pine County Area, Nevada, Parts of White
Pine and Eureka Counties, US Department of Agriculture, Natural Resources
Conservation Service, Fort Worth, TX., USA, 2007.
Petersen, S. L. and Stringham, T. K.: Infiltration, runoff, and sediment
yield in response to western juniper encroachment in southeast Oregon,
Range. Ecol. Manage., 61, 74–81, 2008.Petersen, S. L., Stringham, T. K., and Roundy, B. A.: A process-based
application of state-and-transition models: A case study of western juniper
(Juniperus occidentalis) encroachment, Range. Ecol. Manage., 62, 186–192, 2009.
Pierson, F. B. and Williams, C. J.: Ecohydrologic impacts of rangeland fire
on runoff and erosion: A literature synthesis, General Technical Report
RMRS-GTR-351, US Department of Agriculture, Forest Service, 110 pp., 2016.
Pierson Jr., F. B., Van Vactor, S. S., Blackburn, W. H., and Wood, J. C.:
Incorporating small scale spatial variability into predictions of hydrologic
response on sagebrush rangelands, in: Variability in rangeland water erosion
processes (Soil Science Soceity of America Special Publication 38), edited
by: Blackburn, W. H., Pierson, F. B., Schuman, G. E., and Zartman, R., Soil
Science Society of America, Madison, WI, USA, 23-34, 1994.
Pierson, F. B., Bates, J. D., Svejcar, T. J., and Hardegree, S. P.: Runoff
and erosion after cutting western juniper, Range. Ecol. Manage.,
60, 285–292, 2007.
Pierson, F. B., Robichaud, P. R., Moffet, C. A., Spaeth, K. E., Hardegree,
S. P., Clark, P. E., and Williams, C. J.: Fire effects on rangeland
hydrology and erosion in a steep sagebrush-dominated landscape, Hydrol.
Process., 22, 2916–2929, 2008.
Pierson, F. B., Moffet, C. A., Williams, C. J., Hardegree, S. P., and Clark,
P. E.: Prescribed-fire effects on rill and interrill runoff and erosion in a
mountainous sagebrush landscape, Earth Surf. Process. Landf., 34,
193–203, 2009.Pierson, F. B., Williams, C. J., Kormos, P. R., Hardegree, S. P., Clark, P.
E., and Rau, B. M.: Hydrologic vulnerability of sagebrush steppe following
pinyon and juniper encroachment, Range. Ecol. Manage., 63,
614–629, 10.2111/REM-D-09-00148.1, 2010.
Pierson, F. B., Williams, C. J., Hardegree, S. P., Weltz, M. A., Stone, J.
J., and Clark, P. E.: Fire, plant invasions, and erosion events on western
rangelands, Range. Ecol. Manage., 64, 439–449, 2011.Pierson, F. B., Williams, C. J., Hardegree, S. P., Clark, P. E., Kormos, P.
R., and Al-Hamdan, O. Z.: Hydrologic and erosion responses of sagebrush
steppe following juniper encroachment, wildfire, and tree cutting, Range.
Ecol. Manage., 66, 274–289,
10.2111/REM-D-12-00104.1, 2013.Pierson, F. B., Williams, C. J., Kormos, P. R., and Al-Hamdan, O. Z.:
Short-term effects of tree removal on infiltration, runoff, and erosion in
woodland-encroached sagebrush steppe, Range. Ecol. Manage., 67,
522–538, 10.2111/REM-D-13-00033.1, 2014.Pierson, F. B., Williams, C. J., Kormos, P. R., Al-Hamdan, O. Z., Hardegree,
S. P., and Clark, P. E.: Short-term impacts of tree removal on runoff and
erosion from pinyon- and juniper-dominated sagebrush hillslopes, Range.
Ecol. Manage., 68, 408–422,
10.1016/j.rama.2015.07.004, 2015.Pierson, F. B., Williams, C. J., Kormos, P. R., Al-Hamdan, O. Z., and
Johnson, J. C.: Vegetation, rainfall simulation, and overland flow
experiments before and after tree removal in woodland-encroached sagebrush
steppe: the SageSTEP hydrology study, Ag Data Commons,
10.15482/USDA.ADC/1504518, 2019.Prism Climate Group: Oregon State University, Prism Climate Group,
available at: http://www.prism.oregonstate.edu, last access: 20 September 2019.
Puigdefábregas, J.: The role of vegetation patterns in structuring runoff
and sediment fluxes in drylands, Earth Surf. Process. Landf., 30,
133–147, 2005.
Reid, K. D., Wilcox, B. P., Breshears, D. D., and MacDonald, L.: Runoff and
erosion in a pinon-juniper woodland: Influence of vegetation patches, Soil
Sci. Soc. Am. J., 63, 1869–1879, 1999.
Robichaud, P. R., Elliot, W. J., Pierson, F. B., Hall, D. E., and Moffet, C.
A.: Predicting postfire erosion and mitigation effectiveness with a
web-based probabilistic erosion model, Catena, 71, 229–241, 2007.
Roundy, B. A., Young, K., Cline, N., Hulet, A., Miller, R. F., Tausch, R.
J., Chambers, J. C., and Rau, B.: Piñon-juniper reduction increases soil
water availability of the resource growth pool, Range. Ecol.
Manage., 67, 495–505, 2014.Roundy, B. A., Farmer, M., Olson, J., Petersen, S., Nelson, D. R., Davis,
J., and Vernon, J.: Runoff and sediment response to tree control and seeding
on a high soil erosion potential site in Utah: evidence for reversal of an
abiotic threshold, Ecohydrology, 10, e1775, 10.1002/eco.1775, 2017.
Schlesinger, W. H., Reynolds, J. F., Cunningham, G. L., Huenneke, L. F.,
Jarrell, W. M., Virginia, R. A., and Whitford, W. G.: Biological feedbacks
in global desertification, Science, 247, 1043–1048, 1990.
Shakesby, R. A.: Post-wildfire soil erosion in the Mediterranean: Review and
future research directions, Earth-Sci. Rev., 105, 71–100, 2011.
Shakesby, R. A. and Doerr, S. H.: Wildfire as a hydrological and
geomorphological agent, Earth-Sci. Rev., 74, 269–307, 2006.
Wainwright, J., Parsons, A. J., and Abrahams, A. D.: Plot-scale studies of
vegetation, overland flow and erosion interactions: Case studies from
Arizona and New Mexico, Hydrol. Process., 14, 2921–2943, 2000.
Wei, H., Nearing, M. A., Stone, J. J., Guertin, D. P., Spaeth, K. E.,
Pierson, F. B., Nichols, M. H., and Moffett, C. A.: A new splash and sheet
erosion equation for rangelands, Soil Sci. Soc. Am. J.,
73, 1386–1392, 2009.
Wilcox, B. P., Breshears, D. D., and Allen, C. D.: Ecohydrology of a
resource-conserving semiarid woodland: Effects of scale and disturbance,
Ecol. Monogr., 73, 223–239, 2003.
Wilcox, B. P., Turnbull, L., Young, M. H., Williams, C. J., Ravi, S.,
Seyfried, M. S., Bowling, D. R., Scott, R. L., Germino, M. J., Caldwell, T.
G., and Wainwright, J.: Invasion of shrublands by exotic grasses:
Ecohydrological consequences in cold versus warm deserts, Ecohydrology, 5,
160–173, 2012.Williams, C. J., Pierson, F. B., Al-Hamdan, O. Z., Kormos, P. R., Hardegree,
S. P., and Clark, P. E.: Can wildfire serve as an ecohydrologic
threshold-reversal mechanism on juniper-encroached shrublands, Ecohydrology,
7, 453–477, 10.1002/eco.1364, 2014a.
Williams, C. J., Pierson, F. B., Robichaud, P. R., and Boll, J.: Hydrologic
and erosion responses to wildfire along the rangeland-xeric forest continuum
in the western US: A review and model of hydrologic vulnerability,
Int. J. Wildland Fire, 23, 155–172, 2014b.
Williams, C. J., Pierson, F. B., Spaeth, K. E., Brown, J. R., Al-Hamdan, O.
Z., Weltz, M. A., Nearing, M. A., Herrick, J. E., Boll, J., Robichaud, P.
R., Goodrich, D. C., Heilman, P., Guertin, D. P., Hernandez, M., Wei, H.,
Hardegree, S. P., Strand, E. K., Bates, J. D., Metz, L. J., and Nichols, M.
H.: Incorporating hydrologic data and ecohydrologic relationships into Ecological Site Descriptions, Range. Ecol. Manage., 69, 4–19,
2016a.
Williams, C. J., Pierson, F. B., Spaeth, K. E., Brown, J. R., Al-Hamdan, O.
Z., Weltz, M. A., Nearing, M. A., Herrick, J. E., Boll, J., Robichaud, P.
R., Goodrich, D. C., Heilman, P., Guertin, D. P., Hernandez, M., Wei, H.,
Polyakov, V. O., Armendariz, G., Nouwakpo, S. K., Hardegree, S. P., Clark,
P. E., Strand, E. K., Bates, J. D., Metz, L. J., and Nichols, M. H.:
Application of ecological site information to transformative changes on
Great Basin sagebrush rangelands, Rangelands, 38, 379–388, 2016b.
Williams, C. J., Pierson, F. B., Robichaud, P. R., Al-Hamdan, O. Z., Boll,
J., and Strand, E. K.: Structural and functional connectivity as a driver of
hillslope erosion following disturbance, Int. J. Wildland
Fire, 25, 306–321, 2016c.Williams, C. J., Snyder, K. A, and Pierson, F. B.: Spatial and temporal
variability of the impacts of pinyon and juniper reduction on hydrologic and
erosion processes across climatic gradients in the western US: A regional
synthesis, Water, 10, 1607, 10.3390/w10111607, 2018.Williams, C. J., Pierson, F. B., Kormos, P. R., Al-Hamdan, O. Z., Nouwakpo,
S. K., and Weltz, M. A.: Vegetation, hydrologic, and erosion responses of sagebrush steppe 9 years following mechanical tree removal, Range.
Ecol. Manage., 72, 47–68,
10.1016/j.rama.2018.07.004, 2019a.Williams, C. J., Pierson, F. B., Nouwakpo, S. K., Kormos, P. R., Al-Hamdan,
O. Z., and Weltz, M. A.: Long-term evidence for fire as an ecohydrologic
threshold-reversal mechanism on woodland-encroached sagebrush shrublands,
Ecohydrology, 12, e2086, 10.1002/eco.2086, 2019b.Williams, C. J., Pierson, F. B., Nouwakpo, S. K., Al-Hamdan, O. Z., Kormos,
P. R., and Weltz, M. A.: Effectiveness of prescribed fire to re-establish
sagebrush steppe vegetation and ecohydrologic function on
woodland-encroached sagebrush rangelands, Great Basin, USA: Part I:
Vegetation, hydrology, and erosion responses, Catena, 185, 103477,
10.1016/j.catena.2018.02.027, 2020.