USDA Forest Service Gen. Tech. Rep. PSW-GTR-168-Web. 1998. 55

Evaluating the Impacts of Logging Activities on Erosion

and Suspended Sediment Transport in the Caspar Creek

Watersheds1

Jack Lewis2

Abstract Abstract: Suspended sediment has been sampled at both the North and South Abstract

Fork weirs of Caspar Creek in northwestern California since 1963, and at 13

tributary locations in the North Fork since 1986. The North Fork gaging station

(NFC) was used as a control to evaluate the effects of logging in the South Fork,

in the 1970’s, on annual sediment loads. In the most conservative treatment of

the data, suspended loads increased by 212 percent over the total predicted for a

6-yr period commencing with the onset of logging. When the roles of the

watersheds were reversed and the same analysis repeated to evaluate harvesting

in the North Fork under California Forest Practice Rules in the 1990’s, no

significant increase was found at NFC in either annual suspended or bed load.

With the advent of automatic pumping samplers, we were able to sample

sediment concentration much more frequently in the 1980’s. This allowed storm

event loads from control watersheds in the North Fork to be used in a new

regression analysis for NFC. According to this more sensitive analysis, for the 7-

yr period commencing with the onset of logging, the sum of the suspended storm

loads at NFC was 89 percent higher than that predicted for the undisturbed

condition. The much greater increase after logging in the South Fork is too great

to be explained by differences in sampling methods and in water years, and

appears to be the result of differences in road alignment, yarding methods, and

stream protection zones.

Similar analyses of storm event loads for each of the treated subwatersheds

in the North Fork suggested increased suspended loads in all but one of the

tributaries, but effects were relatively small or absent at the main stem locations.

Of watersheds with less than 50 percent cut, only one showed a highly significant

increase. The greater increase in sediment at NFC, compared to other main-stem

stations, is largely explained by a 3,600-m3

 landslide that occurred in 1995 in a

subwatershed that drains into the main stem just above NFC. Differences among

tributary responses can be explained in terms of channel conditions.

Analysis of an aggregated model simultaneously fit to all of the data shows

that sediment load increases are correlated with flow increases after logging.

Field evidence suggests that the increased flows, accompanied by soil disruption

and intense burning, accelerated erosion of unbuffered stream banks and

channel headward expansion. Windthrow along buffered streams also appears

to be important as a source of both woody debris and sediment. All roads in the

North Fork are located on upper slopes and do not appear to be a significant

source of sediment reaching the channels.

The aggregated model permitted evaluation of certain types of cumulative

effects. Effects of multiple disturbances on suspended loads were approximately

additive and, with one exception, downstream changes were no greater than

would have been expected from the proportion of area disturbed. A tendency for

main-stem channels to yield higher unit-area suspended loads was also detected,

but after logging this was no longer the case in the North Fork of Caspar Creek.

Soil erosion and mass movement play major roles in shaping thelandscapes that surround us. These processes complement those

that build mountains and soils, resulting in landforms such as

valleys, ridges, stream channels, and flood plains. Human activities

that change the balances between these processes can have

consequences that are detrimental to humans and the ecosystems

we depend on. Human activities often lead to an acceleration of soil

movement, net soil losses from hillslopes, and increases in sediment

transport and deposition in stream channels. When soil erosion

and mass movement directly damage roads, bridges, and buildings,

the costs are immediate and obvious. Direct effects on ecosystem

function and site productivity are also serious issues in many areas.

Indirect impacts on downstream water quality and stream channel

morphology, however, are often of greater concern.

Sediment-laden water supplies reduce the capacity of storage

reservoirs and may require additional treatment to render the water

drinkable. Sediment in irrigation water shortens the life of pumps

and reduces soil infiltration capacity. Water quality is also an

important issue for recreational water users and tourism.

Impacts of water quality on fish and aquatic organisms have

motivated much of the research being presented at this conference.

High sediment concentrations can damage the gills of salmonids

and macroinvertebrates (Bozek and Young 1994, Newcombe and

MacDonald 1991). High turbidity can impair the ability of fish to

locate food (Gregory and Northcote 1993) and can reduce the depth

at which photosynthesis can take place. However, suspended

sediment is not always detrimental to fish, and indexes based on

duration and concentration are unrealistically simplistic (Gregory

and others 1993). Turbidity, can, for example, provide cover from

predators (Gregory 1993).

If stream channels cannot transport all the sediment delivered

from hillslopes, they will aggrade, resulting in increased risks for

overbank flooding and bank erosion. It was this sort of risk,

threatening a redwood grove containing the world’s tallest tree,

that motivated the expansion of Redwood National Park in 1978

(U.S. Department of Interior 1981). Accelerated delivery of

sediment to streams can result in the filling of pools (Lisle and

Hilton 1992), and channel widening and shallowing. Hence, fish

rearing habitat may be lost, and stream temperatures often increase.

Excessive filling in spawning areas can block the emergence of fry

and bury substrates that support prey organisms. Settling and

infiltration of fine sediments into spawning gravels reduces the

transport of oxygen to incubating eggs (Lisle 1989) and inhibits the

removal of waste products that accumulate as embryos develop

(Meehan 1974). If aggradation is sufficient to locally eliminate

1 An abbreviated version of this paper was presented at the Conference on Coastal

Watersheds: The Caspar Creek Story, May 6, 1998, Ukiah, California.

2 Mathematical Statistician, Pacific Southwest Research Station, USDA Forest Service,

1700 Bayview Drive, Arcata, CA 95521.
Coastal Watersheds: The Caspar Creek Story Evaluating Impacts of Logging Activities in Caspar Creek Watersheds Lewis

56 USDA Forest Service Gen. Tech. Rep. PSW-GTR-168-Web. 1998.

surface flows during the dry season, fish can lose access to good

upstream habitat or become trapped in inhospitable environments.

How Do Harvest Practices Affect

Sediment Movement?

Figure 1 displays some of the mechanisms linking harvest activities

with instream sediment transport. It is impossible to show all the

potential interactions in only two dimensions, but the figure does hint

at the complexity of controls on sediment movement. Timber harvest

activities can accelerate erosion primarily through felling, yarding,

skidding, building and using roads and landings, and burning.

Felling

Removing trees reduces evapotranspiration and rainfall interception,

thus resulting in wetter soils (Keppeler and others 1994, Ziemer

1968). Loss of root strength and wetter soils can decrease slope

stability (O’Loughlin and Ziemer 1982, Ziemer 1981). Trees near

clearcut edges face increased wind exposure and become more

susceptible to blowdown (Reid and Hilton, these proceedings),

disrupting soils if trees become uprooted. Addition of woody debris

to channels can cause scouring of the banks and channel, but also can

reduce sediment transport by increasing channel roughness and

trapping sediment (Lisle and Napolitano, these proceedings). The

effects of felling upon erosion can be altered by controlling the

quantity and the spatial and temporal patterns of cutting.

Yarding and Skidding

Heavy equipment compacts soils, decreasing infiltration and

percolation rates and increasing surface water. If vegetation and

duff are removed, the underlying soils become vulnerable to surface

erosion. The pattern of yarding and skidding can alter drainage

paths and redirect water onto areas that may be more likely to erode

than naturally evolved channels. Damage from yarding and

skidding is controlled primarily by the type of equipment, the care

exercised by the equipment operator, timing of operations, landing

location, and yarding direction.

Roads and Landings

Roads and landings have similar, but usually more pronounced,

impacts as yarding and skidding, and their presence can greatly

increase landslide risk. Compaction of the road bed can impede

subsurface drainage from upslope areas, resulting in increased pore

water pressures (Keppeler and Brown, these proceedings). Road

cuts and fills are vulnerable to accelerated runoff and surface

erosion, and are particularly vulnerable to slumping, especially on

steep slopes or if the fill or sidecast material has not been properly

compacted. Although roads and landings may be only a small part

of the total forest area, they are responsible for a disproportionate

amount of the total erosion (McCashion and Rice 1983, Swanson

and Dyrness 1975), often more than half. The erosional impact of

roads and landings can be managed through road alignment, design

and construction, drainage systems, type and timing of traffic, and

maintenance.

Burning

Burning can increase erodibility by creating bare ground, and hot

burns can delay revegetation by killing sprouting vegetation. In

some cases, burning can accelerate revegetation by releasing or

scarifying seeds and preparing a seed bed. Burning in areas with

sandy soils can create water-repellent soils and increase surface

runoff (DeBano 1979). The effect of burning on erosion depends

primarily on the temperature of the burn, soil cover, and soil and

vegetation types. Soil moisture, wind, air temperature, humidity,

slope steepness, and fuel abundance and distribution are the major

factors affecting burn temperatures.

Site Factors

Some sites are particularly vulnerable to mass wasting, and these

sites, while occupying a small part of the landscape, have been

found to be responsible for a large proportion of the total erosion in

Felling Burning Yarding

Skidding

Altered

InfiltrationExfiltration

Altered

Drainage

Patterns

Disturbed

Banks

Reduced

Transpiration

& Interception

Loss of 

Root

Strength

Blowdown

and

Debris

Bare

Ground

Roads

Landings

Soil

Compaction

Unstable

Fills

Cut Banks

OverSteepened

Landslides

Channel & Bank

Morphology

Water Quantity

and Movement

Slope Stability

and Erodibility

Bank

Erosion

Hillslope

Sediment

Storage

Sediment

Delivery to

Channels

Fluvial

Sediment

Transport

Storage in

Channels

Storage in 

Weir Pond

Transport to 

Ocean

Surface

Erosion

Debris

Torrents

Figure 1—Conceptual diagram showing the major pathways through which

logging activities influence fluvial sediment transport.
Coastal Watersheds: The Caspar Creek Story Evaluating Impacts of Logging Activities in Caspar Creek Watersheds Lewis

USDA Forest Service Gen. Tech. Rep. PSW-GTR-168-Web. 1998. 57

northwestern California (Dodge and others 1976, Rice and

Datzman 1981). In the Critical Sites Erosion Study, an evaluation of

157 mass failure sites (>153 m3) and 326 randomly selected control

sites from logged areas in northwestern California, Durgin and

others (1989) concluded that management and site factors played

an equal role in road failures. In contrast, management factors were

secondary to site factors on hillslopes. The primary site factors

associated with mass failures were steep slopes, noncohesive soils

and fill materials, and incompetent underlying regolith. Most

failures were associated with the concentration of subsurface water,

as evidenced by perennial seeps, poorly drained soils, phreatic

vegetation, and locations in swales, inner gorges, and lower slope

positions. Previous slope failures were also evident at many of the

sites. The primary management factors associated with mass

failures were steep or overloaded fill slopes, steep cut banks, and

inadequate maintenance of roads and drainage systems. A field

procedure for estimating the probability of mass failure was also

developed (Lewis and Rice 1990, Rice and Lewis 1991) from the

Critical Sites Erosion Study.

Connecting Forest Practices with Water Quality

It is often difficult to identify the causes of erosion. Factors such as

increased soil water or reduced root strength are not directly

observable. Landslides are normal, stochastic, geomorphic events

in many undisturbed areas. Therefore, it may be impossible to show

that a landslide in a logged area would not have occurred had the

area been treated differently.

There is usually a great deal of uncertainty in determining when

and how much sediment from an erosion feature was delivered to a

stream channel. And it is even more difficult to determine the origin

of suspended sediment that has been measured at a gaging station.

Hence, many studies are correlative and rely on statistics to

identify relations between disturbance and water quality. In

environmental research, it is difficult to execute an experimental

design that permits wide inference. The best designs require

randomly assigning the treatments of interest to a large number of

similar experimental units. The random assignment reduces the

likelihood of associations between treatments and characteristics

that might affect the response of some subset of experimental units.

When studying a highly variable response such as sediment

transport, large sample sizes are needed to detect changes even

when the changes are substantial.

When the experimental unit is a watershed, it is usually

impractical to randomly assign treatments or monitor a large number

of watersheds. Instead, we use watersheds with similar physical

characteristics and subject to similar environmental influences, and

we repeat measurements before and after treatments are applied,

maintaining at least one watershed as an untreated control

throughout the study. If the relationship between measurements in

the treated and control watersheds changes after treatment, then we

can reason that the change is probably due to the treatment, unless

some chance occurrence (unrelated to the treatments) affected only

one of the watersheds. In reality, we have little control over such

chance occurrences. For example, there is no guarantee that rainfall

intensities will be uniform over the entire study area.

Such a paired-watershed design can provide a basis for

concluding whether a change occurred (Chow 1960, Wilson 1978)

and can be used to estimate the magnitude of changes. If chance

occurrences can be eliminated, effects can be attributed to the

overall treatment. If multiple watersheds are included in the design,

it may be useful to relate the magnitude of response to disturbances

such as proportion of area logged, burned, compacted by tractors,

etc. But, without additional evidence, nothing can be concluded

about specific causative mechanisms. Conclusions should be

consistent with the statistical evidence, but cause and effect must be

inferred non-statistically, by relating the results to concurrent

studies of other responses and physical processes, field

observations, and similar observations made elsewhere by others.

Study Area

The Caspar Creek Experimental Watersheds are located about 7 km

from the Pacific Ocean in the Jackson Demonstration State Forest,

Mendocino County, California (Preface, fig. 1, these proceedings).

Until the 1970’s, both the 424-ha South Fork and 473-ha North Fork

watersheds were covered by second-growth redwood forests,

originally logged between 1860 and 1904. Both watersheds are

underlain by sandstones and shales of the Franciscan assemblage.

Rainfall averages about 1,200 mm yr-1, 90 percent of which falls during

October through April, and snow is rare. The location, topography,

soils, climate, vegetation, and land use history are described in detail

by Henry (these proceedings). The geology and geomorphology are

described by Cafferata and Spittler (these proceedings).

Methods

South Fork Treatment

The South Fork of Caspar Creek was roaded in the summer of 1967

and selectively logged in 1971-1973, before Forest Practice Rules

were mandated in California by the Z’Berg Nejedly Forest Practice

Act of 1973. About 65 percent of the stand volume was removed. In

contrast with later logging in the North Fork, 75 percent of the

roads in the South Fork were located within 60 m of a stream, all

yarding was done by tractor, ground disturbance amounted to 15

percent of the area, and there were no equipment exclusion zones.

Details are provided by Henry (these proceedings) and by Rice and

others (1979). The North Fork was used as a control watershed to

evaluate the effects of logging in the South Fork until the North Fork

phase of the study was begun in 1985.

North Fork Treatments

The subwatershed containing units Y and Z (Preface, fig. 2, these

proceedings) of the North Fork was logged between December 1985

and April 1986. At the time, this area was thought to have different

soils than the remainder of the North Fork, so it was omitted from

the study plan that specified logging would begin in 1989. The

remainder of the North Fork logging took place between May 1989

and January 1992. Three subwatersheds (HEN, IVE, and MUN)

were left uncut throughout the study for use as controls. Henry
Coastal Watersheds: The Caspar Creek Story Evaluating Impacts of Logging Activities in Caspar Creek Watersheds Lewis

58 USDA Forest Service Gen. Tech. Rep. PSW-GTR-168-Web. 1998.

(these proceedings) summarizes the logging sequence. Briefly, 48

percent of the North Fork (including units Y and Z) was clearcut, 80

percent of this by cable yarding. Tractor yarding was restricted to

upper slopes, as were haul roads, spur roads, and landings. Ground

disturbance from new roads, landings, skid trails, and firelines in

the North Fork amounted to 3.2 percent of the total area. Streams

bearing fish or aquatic habitat were buffered by selectively logged

zones 23-60 m in slope width, and heavy equipment was excluded

from these areas.

Suspended Sediment and Turbidity Measurements

Accurate suspended sediment load estimation in small raindominated watersheds like Caspar Creek depends upon frequent

sampling when sediment transport is high. Sediment

concentrations are highly variable and inconsistently or poorly

correlated with water discharge (Colby 1956, Rieger and Olive

1984). Since the 1960’s, manual sampling methods have been

standardized by the U.S. Geological Survey. However, adequate

records are rare because it is inconvenient to sample at all hours of

the night and weekends. Errors of 50-100 percent are probably

typical when sampling is based on convenience (Thomas 1988,

Walling and Webb 1988).

In the South Fork phase of the study from 1963 to 1975,

sediment sampling was semi-automated by rigging bottles in the

weir ponds at different heights. These single-stage samplers (InterAgency Committee on Water Resources 1961) filled at known stages

during the rising limb of the hydrograph, but the much lengthier

falling limb was sampled using DH-48 depth-integrating hand

samplers (Federal Inter-Agency River Basin Committee 1952) and,

in most cases, was not well-represented. In 1974 and 1975, the

number of DH-48 samples was increased greatly and, in 1976, the

single-stage samplers were replaced by pumping samplers. The

average number of samples collected was 58 per station per year in

1963-1973 and 196 per station per year in 1974-1985.

During the North Fork phase of the study, in water years 1986-

1995, the North Fork weir (NFC), the South Fork weir (SFC) and 13

other locations in the North Fork were gaged for suspended

sediment and flow (Preface, fig. 2, these proceedings). Pumping

samplers were controlled using programmable calculators and

circuit boards that based sampling decisions on real-time stage

information (Eads and Boolootian 1985). Sampling times were

randomly selected using an algorithm that increased the average

sampling rate at higher discharges (Thomas 1985, Thomas 1989).

Probability sampling permitted us to estimate sediment loads and

the variance of those estimates without bias. We also sent crews out

to the watershed 24 hours a day during storm events to replace

bottles, check equipment, and take occasional, simultaneous,

manual and pumped samples. The average number of samples

collected in 1986-1995 was 139 per station per year.

In water year 1996, we began using battery-operated turbidity

sensors and programmable data loggers to control the pumping

samplers at eight gaging stations, and monitoring was discontinued

at the remaining seven stations. Although turbidity is sensitive to

particle size, composition, and suspended organics, it is much better

correlated with suspended sediment concentration than is water

discharge. A continuous record of turbidity provides temporal

detail about sediment transport that is currently impractical to

obtain by any other means, while reducing the number of pumped

samples needed to reliably estimate sediment loads (Lewis 1996).

However, because these turbidity sensors remain in the stream

during measurement periods, they are prone to fouling with debris,

aquatic organisms, and sediment, so it was still necessary to

frequently check the data and clean the optics. The average number

of samples collected in 1996 was 49 per station per year.

Suspended Sediment Load Estimation

The basic data unit for analysis was the suspended sediment load

measured at a gaging station during a storm event or hydrologic

year. Annual loads were estimated only for NFC and SFC and, to

facilitate comparisons with the South Fork study, these were

computed by Dr. Raymond Rice using the same methods as in an

earlier analysis (Rice and others 1979). This involved fitting

sediment rating curves by eye, multiplying the volume of flow in

each of 19 discharge classes by the fitted suspended sediment

concentration at the midpoint of each class, and summing. As

technology has improved over the years, our methods of sample

selection have improved. Thus, although the computational scheme

for estimating annual loads was repeated in both studies, the

sampling bias has changed, and caution must be used when

comparing the sediment loads from the two studies.

For estimating storm loads in 1986-1995, the concentrations

between samples were computed using interpolations relating

concentration to either time or stage. Concentration was first

adjusted to obtain cross-sectional mean concentrations using

regressions based on the paired manual and pumped samples. For

those events in which probability sampling was employed, loads

and variances were also estimated using appropriate sampling

formulae (Thomas 1985, Thomas 1989). However, Monte Carlo

simulations (Lewis and others 1998), showed that the interpolation

methods were more accurate (lower mean square error). Based on

the variance estimates and simulations, the median error of our

estimates for storm events was less than 10 percent.

 For estimating storm loads in 1996, concentration was

predicted using linear regressions, fit to each storm, of

concentration on turbidity. This method produced load estimates

with the same or better accuracy than before, while substantially

reducing the number of samples collected (Lewis 1996). Time or

stage interpolation was employed for periods when turbidity

information was unavailable.

Total Sediment Load Estimation

The bedload and roughly 40 percent of the suspended load settle in

the weir ponds, and thus are not measured at NFC and SFC. The

weir ponds are surveyed annually to estimate total sediment load

(suspended plus bedload) by summing the pond accumulations

and sediment loads measured at the weirs. Pond volumes are

converted to mass based on a density of 1,185 kg m-3. In some of the
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USDA Forest Service Gen. Tech. Rep. PSW-GTR-168-Web. 1998. 59

drier years of record (1972, 1976, 1987, 1991, 1992, and 1994),

negative pond accumulations have been recorded. These values may

result from settling or measurement errors, but some of the values

were too large in magnitude to have resulted from settling alone, so

negative values were converted to zero before adding pond

accumulations to suspended loads. In the results below, only those

that explicitly refer to total sediment load include any sediment

that settled in the weir ponds.

Erosion Measurements

Starting in 1986, a database of failures exceeding 7.6 m3 (10 yd3)

was maintained in the North Fork. This inventory was updated

from channel surveys at least once a year. Road and hillslope failures

were recorded when they were observed, but an exhaustive search

was not conducted. Volume estimates were made using tape

measurements of void spaces left by the failures, except in a few

cases where more accurate survey methods were used. For each

failure, crews recorded void volume, volume remaining at the site

(starting in 1993), location, distance to nearest channel, and any

association with windthrow, roads, or logging disturbance.

Discrete failures such as those included in the failure database

are relatively easy to find and measure. In contrast, surface erosion

is difficult to find and sample because it is often dispersed or

inconspicuous. To obtain an estimate of dispersed erosion sources,

erosion plots were randomly selected and measured in each

subwatershed. Rills, gullies, sheet erosion, and mass movements

were measured on independent samples of road plots and 0.08-ha

circular hillslope plots. Road plots consisted of 1.5-m wide bands

oriented perpendicular to the right-of-way, plus any erosion at the

nearest downslope diversion structure (water bar, rolling dip, or

culvert). A total of 175 hillslope plots and 129 road plots were

measured. These data were collected for a sediment delivery study

and are summarized in a separate report by Rice (1996).

Analyses and Results

Annual Sediment Loads after Logging

the South Fork

Linear regressions between the logarithms of the annual suspended

sediment loads at the two weirs were used to characterize (1) the

relationship of SFC to NFC before the 1971-1973 logging in the

South Fork and (2) the relationship of NFC to SFC before the 1989-

1992 logging in the North Fork.

The calibration water years used in the South Fork analysis

were 1963-1967, before road construction. The sediment load in

1968, after road construction, did not conform to the pretreatment

regression (fig. 2a), but the data from the years 1969-1971 were not

significantly different from the 1963-1967 data (Chow test, p = 0.10).

In 1968, the increase in suspended load was 1,475 kg ha-1, an

increase of 335 percent over that predicted for an undisturbed

condition. The years 1972-1978 (during and after logging) again

differed from the pretreatment regression. Water year 1977 was

missing owing to instrument malfunction. By 1979, the suspended

sediment load at SFC had returned to pretreatment levels. The

increased suspended load after logging amounted to 2,510 kg ha-1yr-1,

or an increase of 212 percent over that predicted for the 6-yr period

by the regression. (Predictions were corrected for bias when

backtransforming from logarithms to original units.) The greatest

absolute increases occurred in the years 1973 and 1974, followed by

1975 (fig. 2b).

A pair of large landslides (one in each watershed) occurred

during hydrologic year 1974, complicating the analysis by Rice and

others (1979), where the North Fork’s sediment load was adjusted

downward because most of the North Fork slide reached the stream,

while most of the South Fork slide did not. However, that year did

not appear anomalous in my analysis, and I did not make any

adjustments. But the unadjusted prediction requires extrapolation

of the regression line well beyond the range of the pretreatment

Annual load at NFC (kg ha-1)

Annual load at SFC (kg ha-1)

50 100 500 1000 5000

500 5000

63

64

65 66

67

68 69

70

71

72

73

74

75

76

78

79

80

81

82

83

84

85

Pretreatment

Water year

Departure (kg ha-1)

65 70 75 80

0 1000 3000 5000

Pretreatment

Roaded

Logged

a) b)

Figure 2—(a) Relation between estimated annual suspended sediment loads at South Fork Caspar Creek (SFC)

and North Fork Caspar Creek (NFC) from 1963 to 1985. Pretreatment regression line is fit to the water years

before roading and logging activity in the South Fork. (b) Time series of departures from the regression line.
Coastal Watersheds: The Caspar Creek Story Evaluating Impacts of Logging Activities in Caspar Creek Watersheds Lewis

60 USDA Forest Service Gen. Tech. Rep. PSW-GTR-168-Web. 1998.

data, so it is still suspect. If the adjustment of Rice and others (1979)

is applied in my analysis, the revised increase in suspended

sediment load is 2,835 kg ha-1yr-1, or an increase of 331 percent over

that predicted for the 6-yr period. The adjusted figure reported for

the 5-yr period (1972-1976) by Rice and others was 3,245 kg ha-1yr-1,

an increase of 354 percent over that predicted.

Although no statistically significant logging effect on pond

accumulation was detected, regression analysis using total sediment

load (including data from 1974) revealed a similar pattern of

impacts as that of the suspended load. The increased total sediment

load after logging of the South Fork amounted to 2,763 kg ha-1yr-1,

or an increase of 184 percent over that predicted for the 6-yr period

by the regression.

Annual Sediment Loads after Logging

the North Fork

The calibration period used in the North Fork analysis includes

1979-1985, the years after the South Fork’s apparent recovery, as

well as 1963-1967. The years 1986-1989 were not included in the

calibration period because the Y and Z units were logged in 1985

and 1986. Applying the Chow test, neither 1986-1989 (p = 0.43) nor

1990-1995 (p = 0.53) was found to differ significantly from the

suspended sediment calibration regression (fig. 3a). The

(nonsignificant) departures from the regression predictions

averaged 118 kg ha-1yr-1, amounting to just 28 percent above that

predicted for the 6-yr period by the regression (fig. 3b). No effect

was detected for pond accumulation by itself or total sediment load.

For total sediment load, the (nonsignificant) departures from the

regression predictions averaged -80 kg ha-1yr-1, or 8 percent below

that predicted for the 6-yr period by the regression.

The absolute numbers reported in the above and earlier analyses

of the South Fork logging (Rice and others 1979) must be viewed with

reservation. The suspended load estimates were based on hand-drawn

sediment rating curves describing the relation between the

concentration of samples collected in a given year to the discharge

levels at which they were collected. In several years, samples were not

available from all discharge classes, so it was necessary to extrapolate

the relation between concentration and discharge to higher or lower

unrepresented classes. Also, a majority of the samples from the years

1963-1975 were collected using single-stage samplers that are filled

only during the rising limb of hydrographs. In most storm events we

have measured at Caspar Creek, the concentrations are markedly

higher on the rising limb of the hydrograph than for equivalent

discharges on the falling limb (e.g., fig. 4). Therefore, the fitted

concentrations were likely too high. A plot of estimated sediment

loads at NFC against annual water yield for the pre-logging years

(fig. 5) suggests that there may be a positive bias during the singlestage years. The error associated with this method certainly varies

from year to year, depending on the numbers of single-stage and

manual samples and their distribution relative to the hydrographs.

However, the plot indicates that loads were overestimated by a factor

of between 2 and 3 in the range where most of the data occur. A

comparison of the annual loads for the years 1986-1995 with annual

sums of storm loads (the most accurate) shows very little bias,

indicating that bias in the early years resulted mainly from sampling

protocols rather than the computational method, which was the same

for all years in this analysis.

North Fork Analysis Using Unlogged

Subwatersheds as Controls

Because of improved and more intensive sampling methods, the

suspended sediment loads for storm events beginning in 1986 are

known far more accurately than the annual loads used in the NFC/

SFC contrasts presented above. Four unlogged control watersheds

were available (HEN, IVE, MUN, and SFC) for the analysis of storm

loads. Unfortunately, only one large storm was available before

logging. That storm was missed at SFC because of pumping sampler

problems. Because of various technical difficulties, not all storms

Annual load at SFC (kg ha-1)

Annual load at NFC (kg ha-1)

50 100 500 1000

50 500

63 64

65 66

67

79

80

81

82

83

84

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Pretreatment 95

Water year

Departure (kg ha-1)

65 70 75 80 85 90 95

-500 0 500 1000

Pretreatment

YZ logged

ARF logged

a) b)

Figure 3—(a) Relation between estimated annual suspended sediment loads at North Fork Caspar Creek (NFC)

and South Fork Caspar Creek (SFC) from 1963 to 1967 and 1979 to 1995, excluding years when sediment was

elevated following logging in the South Fork. Pretreatment regression line is fit to the water years before roading and

logging activity in the North Fork. (b) Time series of departures from the regression line.
Coastal Watersheds: The Caspar Creek Story Evaluating Impacts of Logging Activities in Caspar Creek Watersheds Lewis

USDA Forest Service Gen. Tech. Rep. PSW-GTR-168-Web. 1998. 61

were adequately sampled at each station. However, the sample size

for analyses was increased by using the mean of available data from

the three tributary control watersheds, HEN, IVE, and MUN, in

each storm. (SFC was eliminated because it had lower pretreatment

correlations with the North Fork stations.) This mean (denoted

HIM) provided a pretreatment sample size of 17 storms. The more

accurate sediment loads, better controls, and larger sample size

gave this analysis greater reliability and increased power to detect

changes than the annual load analysis.

A weakness in analyses of logging effects at NFC was the need

to use 1986-1989 as a calibration period even though 12 percent of

the area had been clearcut. The clearcut area might be expected to

somewhat diminish the size of the effect detected. The occurrence

of only one large storm event before logging is mitigated by the fact

that it was thoroughly sampled at both NFC and the three controls.

An average of 59 sample bottles were collected at each of the four

stations, and all the standard errors were less than 10 percent of the

estimated loads, so there is little doubt about this point’s validity.

Figure 6 shows regression lines fit to the suspended storm

loads at NFC versus those at HIM before and after logging began in

the spring of 1989. There was clearly an increase in suspended loads

in small storms after logging began. In large storms there also seems

to be an effect, although some post-treatment points are very close

to the one large pretreatment point. The Chow test for a change

after logging was significant with p = 0.006. The increases over

predicted load, summed over all storms in the post-treatment

period, average 188 kg ha-1yr-1, and amount to an 89 percent increase

over background. The storms in this analysis represent 41 percent

of the 1990-1996 streamflow at NFC, but carried approximately 90

percent of the suspended sediment that passed over the weir (based

on figure 2 of Rice and others 1979).

A 3,600-m3 landslide that occurred in the Z cut unit (Preface,

fig. 2, these proceedings) increased sediment loads at the NFC

gaging station starting in January 1995. NFC was the only gage

downstream from this slide. The sum of suspended loads from

storms preceding the landslide was 47 percent higher (64 kg ha-1yr-1)

than predicted. The sum of suspended loads from storms after the

landslide was 164 percent higher (150 kg ha-1yr-1) than predicted.

Individual Regressions for Subwatersheds

Similar analyses for each of the subwatersheds in the North Fork

(fig. 7 and table 1) indicate increased suspended sediment loads in

all the clearcut tributaries except KJE. Sediment loads in the KJE

watershed appear to have decreased after logging. The only partly

clearcut watershed on a tributary (DOL) also showed highly

significant increases in sediment loads. The upper main-stem

stations (JOH and LAN) showed no effect after logging, and the

lower main-stem stations (FLY and ARF) experienced increases only

in smaller storms. Summing suspended sediment over all storms,

the four main-stem stations all showed little or no change (table 1).

Discharge (m3 s-1)

SSC (mg L-1)

1.0 1.5 2.0 2.5 3.0

100 200 300 400

rising discharge

falling discharge

Figure 4—Storm event at lower main-stem station ARF, January 13-14, 1995,

with water discharge and laboratory sediment concentrations (SSC) at 10-

minute intervals.

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Annual streamflow (m3 ha-1)

Estimated load (kg ha-1)

3000 4000 6000

50 500 5000

single-stage years

pumping sampler years

9000 12000

Figure 5—Relations between estimated annual suspended sediment loads

and annual streamflow at North Fork Caspar Creek (NFC) prior to logging.

Illustrates that load estimates based on sediment rating curves depend

systematically on sampling protocols.

1 5 10 50 100

5 10 50 100 500

Sediment load at HIM (kg ha-1)

Sediment load at NFC (kg ha-1)

pre-treatment

post-treatment

Figure 6—Relation between storm suspended sediment loads at North Fork

Caspar Creek (NFC) and HIM control (mean suspended load of unlogged

tributaries HEN, IVE, and MUN) from 1986 to 1995. Pretreatment regression

line is based on storms in water years 1986-1989, before the major logging

activity began.
Coastal Watersheds: The Caspar Creek Story Evaluating Impacts of Logging Activities in Caspar Creek Watersheds Lewis

62 USDA Forest Service Gen. Tech. Rep. PSW-GTR-168-Web. 1998.

BAN KJE GIB CAR EAG

1 10 100 1000JOH

1 10 100

DOL LAN

1 10 100

FLY ARF

1 10 100

Suspended sediment load at HIM (kg ha-1)

Suspended load at logged station (kg ha-1)

pre-logging post-logging

1 10 100 1 10 100

1 10 100 1000

Figure 7—Relations between storm suspended sediment loads at logged subwatersheds in the

North Fork and HIM control (mean suspended load of unlogged tributaries HEN, IVE, and MUN)

from 1986 to 1995. Pre-logging regression lines are based on pretreatment years that are specific

to each subwatershed. Post-logging relations are not assumed to be linear, hence were fitted by

locally weighted regression (Cleveland 1993).

Treated

watershed

Number of

years

Observed

(kg ha -1 yr-1 )

Predicted

(kg ha -1 yr-1 )

Change

(kg ha -1 yr-1 )

Change

(%)

ARF 4 505 591 -86 -15

BAN 4 85 28 57 203

CAR 5 240 108 132 123

DOL 5 1130 306 824 269

EAG 5 710 210 500 238

FLY 5 536 555 -19 -3

GIB 4 358 119 239 200

JOH 5 667 865 -198 -23

KJE 5 821 1371 -551 -40

LAN 5 420 400 20 5

NFC 6 465 246 219 89

Table 1—Summary of changes in suspended sediment load (summed over storms) after logging in North Fork Table 1

subwatersheds. Predicted loads are computed from pre-treatment linear regressions between the logarithms of the storm

sediment load in the treated watershed and the mean of the storm sediment loads at the control watersheds HEN, IVE,

and MUN. Predictions were corrected for bias when back-transforming from logarithmic units. The number of years in

the post-logging period varies from 4 to 6, depending upon when the watershed was logged and whether or not monitoring

was discontinued in water year 1996.
Coastal Watersheds: The Caspar Creek Story Evaluating Impacts of Logging Activities in Caspar Creek Watersheds Lewis

USDA Forest Service Gen. Tech. Rep. PSW-GTR-168-Web. 1998. 63

Aggregated Regression Model for Subwatersheds

To evaluate the relationships between suspended sediment load

increases and possible explanatory variables, an aggregated

regression model was fit simultaneously to all the subwatershed

storms. The model utilized 367 estimated loads from 51 storms

when HIM was used as the control or 333 estimated loads from 43

storms when HI (the mean of HEN and IVE) was used. Two

regression coefficients were fitted for each watershed. A number of

disturbance measures were considered (table 2), as well as an area

term designed to describe cumulative effects, and a term explaining

sediment increases in terms of flow increases. A great deal of effort

went into developing a model that would permit valid tests of

hypotheses concerning cumulative watershed effects. Therefore, the

response model is coupled with a covariance model that describes

variability in terms of watershed area and correlation among

subwatershed responses as a function of distance between

watersheds. These models were solved using the method of

maximum likelihood and will be described in detail in a separate

publication (Lewis and others 1998).

Departures from sediment loads predicted by the aggregated

model for undisturbed watersheds were modest. The median

increase in storm sediment load was 107 percent in clearcuts and 64

percent in partly clearcut watersheds. The median annual increase

was 109 percent (58 kg ha-1yr-1) from clearcut watersheds and 73

percent (46 kg ha-1yr-1) from partly clearcut watersheds. The

absolute flux values are underestimated somewhat because they

include only sediment measured in storms, and no effort has been

made to adjust for missing data. However, the major storms have

been included, and virtually all of the sediment is transported

during storms. Uncertainty due to year-to-year variability is

certainly a much greater source of error.

The most important explanatory variable identified by the

model was increased volume of streamflow during storms. Storm

flow predictions (Ziemer, these proceedings) were based on an

aggregated model analogous to that used for predicting sediment

loads. The ratio of storm sediment produced to that predicted for

an unlogged condition was positively correlated to the ratio of storm

flow produced to that predicted for an unlogged condition (fig. 8).

This result is not unexpected because, after logging, increased storm

flows in the treated watersheds provide additional energy to deliver

and transport available sediment and perhaps to generate

additional sediment through channel and bank erosion.

Whereas individual watersheds show trends indicating

increasing or decreasing sediment loads, there is no overall pattern

of recovery apparent in a trend analysis of the residuals from the

model (fig. 9a). This is in contrast with the parallel model for storm

flow volume (fig. 9b), and suggests that some of the sediment

increases are unrelated to flow increases.

Other variables found to be significant were road cut and fill

area, and, in models using the HI control, the length of unbuffered

stream channel, particularly in burned areas. Under California

Forest Practice Rules in effect during the North Fork logging, buffers

were not required for stream channels that do not include aquatic

life and are not used by fish within 1,000 feet downstream except in

confluent waters. As discussed earlier, one must be cautious about

drawing conclusions about cause and effect when treatments are

not randomly assigned to experimental units and replication is

limited. Increases in sediment load in one or two watersheds can

create associations with any variable that happens to have higher

values in those watersheds, whether or not those variables are

physically related to the increases. In this study, the contrast in

response is primarily between watershed KJE, where sediment loads

decreased, versus watersheds BAN, CAR, DOL, EAG, and GIB.

Watershed KJE was unburned and also had the smallest amount of

unbuffered stream of all the cut units. Watersheds EAG and GIB

were burned and had the greatest amount of unbuffered stream in

burned areas. Watershed EAG experienced the largest sediment

increases and also had the greatest proportion of road cut and fill

area. Because EAG was not unusually high in road surface area, the

large road cut and fill area indicates that the roads in EAG are on

steeper hillslopes.

There is little field evidence of sediment delivery from roads in

Mean unit area suspended load from control watersheds

Excess storm flow volume relative to that of control watersheds

Time since logging completed

Timber removed per unit watershed area

Areas of various disturbances as proportion of watershed:

Cable, tractor yarding

Stream protection zones, thinned areas

Burning (low intensity, high intensity)

Road cuts, fills, running surfaces

Skid trail cuts, fills, operating surfaces

Landing cuts, fills, operating surfaces

Areas of above disturbances within 46 m (150 ft) of a stream channel

Length of impacted stream in above disturbances per unit watershed area

Length of cabled corridors per unit watershed area

Watershed area

Table 2—Explanatory variables considered in modeling storm sediment loads in North Fork Table 2

subwatersheds.

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Sediment ratio (observed:predicted)

0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.4

r = 0.64

Figure 8—Relation between post-logging ratios of observed to predicted

storm flow and suspended sediment load for all North Fork subwatersheds.

Predictions are for undisturbed watersheds based on aggregated regression

models using HI control (mean response of unlogged tributaries HEN and IVE).
Coastal Watersheds: The Caspar Creek Story Evaluating Impacts of Logging Activities in Caspar Creek Watersheds Lewis

64 USDA Forest Service Gen. Tech. Rep. PSW-GTR-168-Web. 1998.

the North Fork watershed. In the inventory of failures greater than

7.6 m3, only 8 of 96 failures, and 1,686 of 7,343 m3 of erosion were

related to roads. Nearly all of this road-related erosion was recorded

as remaining on-site, and none of the road-related failures occurred

in the EAG watershed. Based on the 129 random erosion plots (Rice

1996), the road erosion in EAG was 9.3 m3ha-1, compared to 34.5

m3ha-1 for KJE and 16.6 m3ha-1 for all roads in the North Fork. Thus

it seems that the appearance of road cuts and fills in the model

resulted from a spurious correlation.

On the other hand, channel reaches subjected to intense

broadcast burns did show increased erosion from the loss of woody

debris that stores sediment and enhances channel roughness

(Keppeler, electronic communication). And increased flows,

accompanied by soil disruption and burning in headwater swales,

may have accelerated channel headward expansion, and soil pipe

enlargements and collapses observed in watershed KJE (Ziemer

1992) and in EAG, DOL, and LAN.

Based on the 175 random erosion plots in harvest areas (Rice

1996), the average hillslope erosion rates in the burned watersheds

EAG and GIB were 153 m3

ha-1 and 77 m3ha-1, respectively, the

highest of all the watersheds. The average rate for the unburned

clearcut watersheds BAN, CAR, and KJE was 37 m3ha-1. These figures

include estimates of sheet erosion, which is difficult to measure and

may be biased towards burned areas because it was easier to see the

ground where the slash had been burned (Keppeler, verbal

communication). About 72 percent of EAG and 82 percent of GIB

were judged to be thoroughly or intensely burned, and the

remainder was burned lightly or incompletely. It is unknown how

much of this hillslope erosion was delivered to stream channels, but

the proportion of watershed burned was not a useful explanatory

variable for suspended sediment transport.

The failure inventory identified windthrow as another fairly

important source of sediment. Of failures greater than 7.6 m3

, 68

percent were from windthrow. While these amounted to only 18

percent of the failure volume measured, 91 percent of them were

within 15 m of a stream, and 49 percent were in or adjacent to a

stream channel. Because of the proximity of windthrows to streams,

sediment delivery from windthrow is expected to be

disproportionate to the erosion volume. Windthrows are also

important as contributors of woody debris to channels (Reid and

Hilton, these proceedings), and play a key role in pool formation

(Lisle and Napolitano, these proceedings). Because woody debris

traps sediment in transport, it is unknown whether the net effect of

windthrow on sediment transport was positive or negative.

Cumulative Effects

A full explanation of the rationale and methods of testing for

cumulative watershed effects is beyond the scope of this paper, and

final results on this topic will be reported by Lewis and others

(1998). Preliminary results will simply be stated here.

I have considered three types of information that the

aggregated model provides about the cumulative effects of logging

activity on suspended sediment loads:

1. Were the effects of multiple disturbances additive in

a given watershed?

2. Were downstream changes greater than would be

expected from the proportion of area disturbed?

3. Were sediment loads in the lower watershed elevated to

higher levels than in the tributaries?

The response being considered in all of these questions is the

suspended sediment load per unit watershed area for a given storm

event. Watershed area was used in the model to represent distance

downstream.

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Sediment residual (log[kg ha-1])

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Figure 9—Relation between post-logging residuals from aggregated models and time (difference in water years)

since harvesting. (a) model for storm suspended sediment loads, and (b) model for storm flow volumes. Curves

were fitted by locally weighted regression (Cleveland 1993).
Coastal Watersheds: The Caspar Creek Story Evaluating Impacts of Logging Activities in Caspar Creek Watersheds Lewis

USDA Forest Service Gen. Tech. Rep. PSW-GTR-168-Web. 1998. 65

The first question may be answered partly by looking at the

forms of the storm flow and sediment models. Analyses of the

residuals and covariance structures provide good evidence that the

models are appropriate for the data, including the use of a

logarithmic response variable. This implies a multiplicative effect

for predictors that enter linearly and a power function for predictors

that enter as logarithms. It turns out that the flow response to

logged area is multiplicative, and the sediment response to flow

increases is a power function. These effects, however, are

approximately additive within the range of data observed for

watersheds receiving flow from multiple cut units.

The second question was addressed by testing terms formed

from the product of disturbance and watershed area. If the

coefficient of this term were positive, it would imply that the effect

of a given disturbance proportion increases with watershed size. A

number of disturbance measures were considered, including road

cut and fill area and length of unbuffered stream channels. None of

the product terms were found to have coefficients significantly

greater than zero, indicating that suspended load increases were

not disproportionately large in larger watersheds. To the contrary,

the sum of the observed sediment loads at the four main-stem

stations were all within 25 percent of the sum of the loads predicted

for undisturbed watersheds (table 1). Apparently, much of the

sediment measured in the tributaries has been trapped behind

woody debris or otherwise stored in the channels, so that much of it

has not yet been measured downstream.

There is, however, one subwatershed where this second type of

cumulative effect may be occurring. Watershed DOL, only 36

percent cut, includes the 100 percent cut watershed EAG, yet the

sediment increases (269 percent at DOL versus 238 percent at EAG)

have been similar. The increases in DOL seem to be related to

channel conditions created in the historic logging (1900-1904) and,

possibly, to increased flows from recent logging. At the turn of the

century, the channel between the DOL and EAG gaging stations was

used as a “corduroy road” for skidding logs by oxen. Greased logs

were half-buried in the ground at intervals equal to the step length

of the oxen (Napolitano 1996), and an abundance of sediment is

stored behind them today (Keppeler, electronic communication).

Energy available during high flows may be mobilizing sediment

stored behind these logs. In the lower reach, the channel has a low

width:depth ratio and is unable to dissipate energy by overflowing

its banks. The high banks in this reach would be particularly

vulnerable to increased peak flows, and have failed in a number of

places in the years since EAG was logged.

The third question was addressed by testing watershed area as

a linear term in the model. The coefficient of watershed area was

positive (p = 0.0023), implying that the response, suspended

sediment transport per unit watershed area, tends to increase

downstream in the absence of disturbance. This tendency (with the

exception of watershed KJE) is apparent in the pretreatment lines fit

by least squares (fig. 10a), and could be reflecting the greater

availability of fine sediment stored in these lower gradient channels.

The relevance to cumulative effects is that downstream locations

might reach water quality levels of concern with a smaller

proportion of watershed disturbance than upstream locations.

To the extent that larger watersheds reflect average disturbance

rates and therefore have smaller proportions of disturbance than the

smallest disturbed watersheds upstream, one might expect sediment

loads downstream to increase by less than those in the logged

tributaries, reducing the overall variability among watersheds. In

addition, as mentioned before, some of the sediment may be stored

for several years before reaching the lower stations. That is what we

observed in this study—the post-treatment regression lines (fig. 10b)

were much more similar among watersheds than the pretreatment

lines, and the main-stem stations no longer transported the highest

sediment loads relative to watershed area.

Discussion

North Fork versus South Fork

My analysis of the South Fork logging data used a different model

than was used by Rice and others (1979). However, the estimated

increases in sediment loads were similar. For example, they

reported suspended load increases of 1,403 kg ha-1yr-1 in the year

after road construction and 3,254 kg ha-1yr-1 for the 5-yr period

after logging. For the same periods, I estimated increases of 1,475

and 2,877 kg ha-1yr-1. Reversing the roles of the two watersheds for

the later North Fork logging, the same analysis was unable to

detect an effect. However, analysis of storm event loads from 1986

to 1996, using smaller subwatersheds within the North Fork as

controls that had similar 19th-century logging histories as the

whole North Fork, indicated that storm loads at NFC had

increased by 188 kg ha-1yr-1. When comparing these figures, one

should consider the differences between the water years 1972-

1978 and 1990-1996, as well as differences in sampling

methodologies that could have biased the estimated sediment

loads. The mean annual unit area streamflow in the control (NFC)

was 63 percent higher in 1972-1978 than that in the control (SFC)

in 1990-1996. There is a surprisingly good relation between

annual excess sediment load (departures from the pre-treatment

regression) and water discharge in each of the studies (fig. 11). For

equivalent flows, excess sediment loads in the South Fork analysis

were six to seven times those in the North Fork analysis. It is

probable that the sampling methods in the 1960’s and 1970’s

resulted in overestimation of sediment loads in the South Fork

analysis by a factor of 2 or 3. Therefore, comparisons between

relative increases are more appropriate. Excess suspended load

was 212 percent to 331 percent (depending on whether an

adjustment is made for the 1974 North Fork landslide) after

logging the South Fork, and 89 percent after logging the North

Fork, suggesting that the effect of logging on suspended sediment

load was 2.4 to 3.7 times greater in the South Fork than in the

North Fork. These estimates approximately agree with estimates

(Rice 1996) that both erosion and the sediment delivery ratio in

the South Fork were about twice that in the North Fork.

Subwatersheds and KJE Anomaly

Analyses of the 10 treated subwatersheds in the North Fork drainage

show suspended load increases at the gaging stations located
Coastal Watersheds: The Caspar Creek Story Evaluating Impacts of Logging Activities in Caspar Creek Watersheds Lewis

66 USDA Forest Service Gen. Tech. Rep. PSW-GTR-168-Web. 1998.

number of organic steps in the buffered stream above KJE nearly

doubled. Farther upstream, the channel was no longer shaded by

the forest canopy and became choked with new redwood sprouts,

horsetails, berry vines, and ferns, as well as slash that was

introduced during logging. Although small storm flows did increase

after logging, it is possible that channel roughness could have

increased enough to reduce the energy available for sediment

transport. An energy-limited stream would respond to increased

sediment supply and reduced energy by reducing sediment

transport. On the other hand, tributaries in a supply-limited

sediment regime would have responded to a combination of

increased sediment supply and reduced energy by increasing

sediment transport. At some point, the increased supply probably

converted these channels to an energy-limited regime, at which

point stream power became the primary factor controlling variation

in the increased transport levels. Rice and others (1979) concluded

that is what happened after logging in the South Fork.

The aggregated regression for storm flow volumes (Lewis and

others 1998; Ziemer, these proceedings) showed that flow increases

Suspended sediment load (kg ha-1)

1 5 50

0.5 5.0 50.0 500.0

a) pre-logging

A

A

B

B

C

C

D

D

E

E

F

F

G

G

J

J

K

K

L

L

N

N

1 5 50

0.5 5.0 50.0 500.0

b) post-logging

A

A

B

B

C

C

D

D

E

E

F

F

G

G

J

J

K

K

L

L

N

N

Suspended load at HIM (kg ha-1)

Figure 10—Regression lines for storm suspended sediment loads at treated watersheds in the North Fork,

predicted from HIM control (mean suspended load of unlogged tributaries HEN, IVE, and MUN). (a) pre-logging,

and (b) post-logging. Solid lines represent main-stem stations and dashed lines represent tributary stations.

immediately below clearcut units with one exception. At KJE, loads

have decreased. A possible explanation for this anomaly lies in the

tributary channel morphology. The stream channel in the KJE

watershed is an extension of the main stem of the North Fork. It is

(and, before recent logging, was) more deeply incised than the other

tributaries, and it has the lowest gradient of tributaries other than

the reach between the DOL and EAG gaging stations. The channel

may have taken its gully-like form after the historic logging that

took place between 1860 and 1904, when streams and streambeds

were used as conduits for moving logs (Napolitano 1996). In any

case, KJE had the highest pre-logging (1986-1989) unit area

sediment loads of any of the tributaries (fig. 10a). Sediment in its

channel is plentiful and the banks are actively eroding. It is likely,

then, that the pre-logging sediment regime in KJE may have been

energy-limited, which is more characteristic of disturbed

watersheds. That is, sediment discharge was determined more by

the ability of the stream to transport sediment than by the

availability of sediment to be transported.

After logging, woody debris was added to the channel, and the
Coastal Watersheds: The Caspar Creek Story Evaluating Impacts of Logging Activities in Caspar Creek Watersheds Lewis

USDA Forest Service Gen. Tech. Rep. PSW-GTR-168-Web. 1998. 67

whether these results might be generalizable to larger watersheds,

annual sediment loads for water years 1992-1996 were plotted

against annual water yield (fig. 12) for NFC, SFC, and six gaging

stations on streams in the vicinity of Redwood National Park (RNP).

These watersheds were selected because of the high quality of their

data and because, like Caspar Creek, they are underlain by the

highly erodible Franciscan formation and historically supported

mostly redwood forest with varying amounts of Douglas-fir. Caspar

Creek receives less rainfall than the RNP watersheds, hence the

lower annual flows.

In contrast to Caspar Creek, the RNP main-stem stations

(Redwood Creek at Orick, 720 km2, and at O’Kane, 175 km2)

continue to yield higher sediment loads than the RNP tributaries

even after intensive management. Except for Little Lost Man Creek,

these watersheds have been heavily logged at various times over the

past 50 years, including the 1980’s and 1990’s. (Ground disturbance

from logging in these watersheds was much more severe than that

in Caspar Creek.)

The watershed with the lowest sediment loads is the unlogged

Little Lost Man Creek (9.0 km2

), which is also the smallest of the

RNP watersheds. Lacks Creek (44 km2), Coyote Creek (20 km2), and

Panther Creek (16 km2) are high-gradient (4-7 percent) channels in

three different geologic subunits of the Franciscan formation

(Harden and others 1982). Part of the explanation for the higher

sediment loads at the main-stem stations may lie in the greater

abundance of fine sediments available for transport in these low

gradient (<1 percent) channels. Note that the Caspar Creek main

stems are intermediate in both stream gradient (~1 percent) and

sediment transport between the RNP tributaries and main stems.

Regardless of the cause, if these lower reaches have the poorest

Annual streamflow (m3 ha-1)

Excess suspended sediment (kg ha-1)

2000 3000 4000 6000 9000 12000

0 10 100 1000 5000

72

73 74

75

76 78

90

91

93

94

95

96

SFC excess

NFC excess

Figure 11—Relations between annual excess suspended sediment and

annual streamflow for six years after logging in the South Fork and North

Fork. South Fork excess loads are the departures from the pretreatment

regression of figure 2. North Fork excess loads are the sums of storm

departures from the pretreatment regression of figure 6.

Annual streamflow (m3 ha-1)

Annual suspended load (kg ha-1)

10 50 500 5000

NFC

SFC

Lost Man

Coyote

Orick

O'Kane

Lacks

Panther

2500 5000 10000 20000

50 500 5000

Figure 12—Relation between annual suspended sediment loads and annual

streamflow for water years 1992-1996 at North Fork Caspar Creek (NFC),

South Fork Caspar Creek (SFC), and 6 gaging stations in the vicinity of

Redwood National Park. Caspar Creek sediment loads were divided by 0.6 to

account for suspended sediment settling in the weir ponds.

could be largely explained by the proportion of a watershed logged,

an antecedent wetness index, and time since logging. The

aggregated regression for storm suspended sediment showed that

much of the variability in suspended sediment load could, in turn,

be explained by the flow increases. The implication is that, after

logging, the channels were indeed in an energy-limited regime.

Flow increases accounted for only part of the variability in

sediment production. Road systems would typically be expected to

account for much of the sediment. However, in this case, roads were

relatively unimportant as a sediment source because of their

generally stable locations on upper hillslopes far from the stream

channels. Field observations of increased bank erosion and gully

expansion in clearcut headwater areas indicate that some of the

suspended sediment increases were associated with the length of

unbuffered stream channels in burned areas and, to a lesser degree,

in unburned areas. Further indirect evidence that factors besides

flow volume are elevating the suspended loads is that storm flows

show a recovery trend, whereas storm suspended loads do not (fig.

9). This supports the hypothesis that the sediment regime has

changed to one that will support elevated transport levels until the

overall sediment supply is depleted. This can happen only after

erosion and delivery rates to the channel decline and flows have

been adequate to export excess sediment stored in the channels.

Cumulative Effects

Before logging, the larger main stem watersheds generally yielded

the highest unit area sediment loads. But the increases after logging

were greatest in the tributaries, resulting in a much narrower range

of transport, for a given storm size, after logging (fig. 10). The

North Fork of Caspar Creek is a small watershed (4.73 km2). To see
Coastal Watersheds: The Caspar Creek Story Evaluating Impacts of Logging Activities in Caspar Creek Watersheds Lewis

68 USDA Forest Service Gen. Tech. Rep. PSW-GTR-168-Web. 1998.

water quality, then the incremental effect of an upstream

disturbance may be cause for concern whether or not a water quality

problem develops at the site of the disturbance. In other words,

activities that have acceptable local consequences on water quality

might have unacceptable consequences farther downstream when

the preexisting water quality downstream is closer to harmful levels.

Cumulative effects considered in this paper were limited to a

few hypotheses about water quality that could be statistically

evaluated. But cumulative effects can occur in many ways. For

example, resources at risk are often quite different in downstream

areas, so an activity that has acceptable local impacts might have

unacceptable offsite impacts if critical or sensitive habitat is found

downstream. For a much broader treatment of cumulative effects

see the discussion by Reid (these proceedings).

Conclusions

The main conclusions from these analyses are:

• Improved forest practices resulted in smaller increases

in suspended load after logging the North Fork than

after logging the South Fork. Increases were 2.4 to 3.7

times greater in the South Fork with roads located near

the stream, all yarding by tractor, and streams not

protected.

• Much of the increased sediment load in North Fork

tributaries was related to increased storm flow volumes.

With flow volumes recovering as the forest grows back,

these increases are expected to be short-lived.

• Further sediment reductions in the North Fork probably

could have been achieved by reducing or preventing

disturbance to small drainage channels.

• Sediment loads are probably affected as much by

channel conditions as by sediment delivery from

hillslopes. The observed changes in sediment loads are

consistent with conversion of those channels that were

supply-limited before logging to an energy-limited

regime after logging.

• The effects of multiple disturbances in a watershed were

approximately additive.

• With one exception, downstream suspended load

increases were no greater than would be expected from

the proportion of area disturbed. To the contrary, most

of the increased sediment produced in the tributaries

was apparently stored in the main stem and has not yet

been measured at the main-stem stations.

• Before logging, sediment loads on the main stem were

higher than on most tributaries. This was no longer the

case after logging. However, limited observations from

larger watersheds suggest that downstream reaches in

some watersheds are likely to approach water-quality

levels of concern before upstream reaches.

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