The effects of wildfi re on the sediment yield of a coastal California watershed

J.A. Warrick1,†, J.A. Hatten2, G.B. Pasternack3, A.B. Gray3, M.A. Goni4, and R.A. Wheatcroft4 1U.S. Geological Survey, Pacifi c Coastal and Marine Science Center, Santa Cruz, California 95060, USA 2College of Forest Resources, Mississippi State University, Mississippi State, Mississippi 39762, USA 3Department of Land, Air and Water Resources, University of California, Davis, California 95616, USA 4College of Oceanic and Atmospheric Sciences, Oregon State University, Corvallis, Oregon 97331, USA

ABSTRACT approach of estimating sediment yield from sediment discharge and sedimentation in sediment rating curves and discharge data— downstream channels, reservoirs, and coastal The occurrence of two wildfi res separated without including periodic perturbations landforms, which can alter landform morphol- by 31 yr in the chaparral-dominated Arroyo from wildfi res—may grossly underestimate ogy and aquatic habitats (e.g., Florsheim et al., Seco watershed (293 km2) of California pro- actual sediment yields. 1991; Reneau et al., 2007; Malmon et al., 2007; vides a unique opportunity to evaluate the Warrick et al., 2008). Postfi re erosion also re- effects of wildfi re on suspended-sediment INTRODUCTION sults in increased export of carbon and nutrients yield. Here, we compile discharge and sus- from burned watersheds, which can infl uence pended-sediment sampling data from before Wildfi re alters the physical conditions of veg- rates of primary production and carbon preser- and after the fi res and show that the effects of etation and soil, and these changes can modify vation in depositional settings (Johnson et al., the postfi re responses differed markedly. The the hydrologic and geomorphic processes within 2004; Murphy et al., 2006; Hunsinger et al., 1977 Marble Cone wildfi re was followed by the burned landscape (Shakesby and Doerr, 2008). Because of the rates and patterns of ero- an exceptionally wet winter, which resulted 2006). There are two primary hydrogeomorphic sion following a fi re, both hillslope morphology in concentrations and fl uxes of both fi ne effects of wildfi re: (1) an increase in runoff, pri- and sedimentary deposits within the geologic and coarse suspended sediment that were marily through increased overland fl ow from the record will be infl uenced by periodic wild- ~35 times greater than average (sediment combined effects of reduced water infi ltration fi re (Meyer et al., 1995; Mensing et al., 1999; yield during the 1978 water year was 11,000 through soil hydrophobic layers, reduced sur- Pierce et al., 2004; Roering and Gerber, 2005; t/km2/yr). We suggest that the combined face roughness, and a reduction in evapotranspi- Shakesby and Doerr, 2006). 1977–1978 fi re and fl ood had a recurrence in- ration (DeBano and Krammes, 1966; Swanson, The rate of erosion following a wildfi re can terval of greater than 1000 yr. In contrast, the 1981; Brown, 1972; Rice, 1974; DeBano, 2000; vary widely, and differences have been at- 2008 Basin Complex wildfi re was followed Doerr et al., 2000; Martin and Moody, 2001; tributed to prefi re vegetation, landscape slope, by a drier than normal year, and although Neary et al., 2005), and (2) an increase in ero- wildfi re burn intensity, postfi re soil conditions, suspended-sediment fl uxes and concentra- sion through several mechanisms including dry and precipitation rates (Shakesby and Doerr, tions were signifi cantly elevated compared to ravel, rain splash erosion and transport, rilling 2006; Malmon et al., 2007). The prefi re vegeta- those expected for unburned conditions, the resulting from surface-water fl ow, and mass tion types and conditions will have important sediment yield during the 2009 water year movements (Osborn et al., 1964; Wells, 1981; infl uences on the burn intensity and postfi re was less than 1% of the post–Marble Cone Scott and Williams, 1978; Scott and Van Wyk, soil hydrophobicity. For example, combustion wildfi re yield. After the fi rst postfi re winters, 1990; Inbar et al., 1998; Moody et al., 2005; of fi re-prone chaparral produces marked water sediment concentrations and yield decreased Shakesby and Doerr, 2006). Although these two repellency in soils because of the low vegetation with time toward prefi re relationships and effects can be pronounced—runoff and erosion height and high burn temperatures (Rice, 1982; continued to have signifi cant rainfall depen- can increase by up to several orders of magni- Wells, 1981). dence. We hypothesize that the differences in tude following wildfi re—they commonly last Vegetation also inhibits downslope sediment sediment yield were related to precipitation- only 3–8 yr and decay quickly over this time transport during the years before a wildfi re, enhanced hillslope erosion processes, such as (Rowe et al., 1954; LACFCD, 1959; Swanson, resulting in hillslope storage of sediment (Fig. rilling and mass movements. The millennial- 1981; Brown et al., 1982; Cerdà, 1998; Cerdà 1A; Rice, 1982; Florsheim et al., 1991). After a scale effects of wildfi re on sediment yield and Lasanta, 2005; Reneau et al., 2007; War- wildfi re, this hillslope sediment will be released were explored further using Monte Carlo rick and Rubin, 2007). Even so, wildfi re will downslope as dry ravel on slopes greater than simulations, and these analyses suggest that increase long-term erosion rates from the land- a critical angle of repose (Fig. 1B). Dry ravel infrequent wildfi res followed by fl oods in- scape if the effects are marked and fi re recur- is recognized as an important postfi re sediment crease long-term suspended-sediment fl uxes rence is suffi ciently frequent (Swanson, 1981; transport process in both wet and dry climates markedly. Thus, we suggest that the current Lavé and Burbank, 2004). (e.g., Florsheim et al., 1991; Roering and Ger- Increased runoff and erosion from burned ber, 2005), and Wells (1981) reported that an- †E-mail: [email protected] landscapes often cause increased suspended- nual net dry ravel transport rates increased

GSA Bulletin; July/August 2012; v. 124; no. 7/8; p. 1130–1146; doi: 10.1130/B30451.1; 16 fi gures; 3 tables; Data Repository item 2012140.

1130 For permission to copy, contact [email protected] © 2012 Geological Society of America

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an ideal opportunity to evaluate the effects of A Prefire B Postfire C1 Light rainfall wildfi re on hydrologic fl uxes from a water- shed. This is largely due to a river gauging and sampling program by the U.S. Geological Erosion of Dry ravel dry ravel and Survey (USGS) that provided discharge and Chaparral Barren loose soil suspended-sediment data, which we supple- C2 Heavy rainfall mented with additional suspended-sediment Veg Soil bic sampling from 2008 to 2010. Using these data, we investigated whether the wildfi res produced Dry ravel Hydropholayer signifi cant changes in water and suspended- 1 m 1 m Rills, gullies, debris flows sediment discharge rates. Our primary goals were to: (1) characterize the postfi re changes Figure 1. Illustration of the effects of wildfi re on sediment yield from a steep, chaparral in water and sediment yields, (2) use the two landscape. (A) Before a wildfi re, the dense chaparral vegetation (veg) and organic debris wildfi res and postfi re hydrologic conditions retain sediment that had been mobilized downslope by diffusive processes. (B) During and to compare and contrast postfi re effects, and immediately after a wildfi re, the combustion of vegetation and organic debris above the (3) use these data to provide insights into long- ground reduces surface roughness and releases retained soil as dry ravel, which accumu- term (millennial) dynamics of watershed-scale lates as talus in colluvial hollows, hillslope toes, and stream channels. The high tempera- denudation. ture of chaparral fi re also creates a hydrophobic layer beneath the soil surface. (C1) and (C2) Sediment erosion and transport processes during postfi re rainfall are highly dependent STUDY SITE upon rainfall intensity. Whereas light rainfall will result in the erosion of loose soil and dry ravel talus, heavy rainfall will generate overland fl ow at rates that can cut rills and gullies The Arroyo Seco watershed is a steep, into the soil and potentially generate debris fl ows. 790 km2 basin within the second largest water- shed of California’s coastal ranges, the Salinas River (11,000 km2). Here, we focus on the ~30-fold during the fi rst year following wild- 1998; Moody and Martin, 2001), the results of upper Arroyo Seco watershed that drains into fi res in southern California chaparral. which cannot be scaled directly to watersheds USGS gauging station 11151870 (site 1A Once the postfi re sediment supply has in- (Shakesby and Doerr, 2006; Walling, 2006). in Fig. 2; Table 1) and has a drainage area of creased by dry ravel, the fate of this sediment Perhaps the largest drainage basin with exten- 293 km2. The Arroyo Seco drains the steep and further erosion of hillslope soils will de- sive pre- and postfi re sampling of suspended- Santa Lucia Range (maximum elevation 1784 m), pend largely on the timing and intensity of rain- sediment discharge is the ephemeral mountain which trends southeast from Monterey Bay to fall (LACFCD, 1959; Keller et al., 1997; Lavé stream draining a 7 km2 burn sampled by Mal- San Luis Obispo and forms the rugged Big Sur and Burbank, 2004; Shakesby and Doerr, 2006; mon et al. (2007), in which suspended-sediment coastal setting. The Santa Lucia Range is part Malmon et al., 2007). With increasing rainfall concentrations increased by two orders of mag- of the greater Coastal Ranges of California and intensity and amounts, the rate of sediment nitude after the fi re. is characterized by a Mesozoic granitic base- eroded and transported downslope from over- Watershed-scale (>100 km2) investigations of ment and widely distributed metamorphic and land fl ow increases. Overland fl ow can erode postfi re sediment production have largely relied sedimentary (both marine and terrestrial) rocks exposed soil, mobilize dry ravel talus, and— upon sediment accumulation behind debris ba- (Hall, 1991; Table 1). during heavy rainfall—cut rills and gullies into sins and dams (e.g., Scott and Williams, 1978; These steep and tall mountains orographi- the landscape and activate debris fl ows (Fig. 1C; Lavé and Burbank, 2004). While these studies cally enhance precipitation, which is dominated Rice, 1982; Wells, 1981; Florsheim et al., 1991; have shown that wildfi re can increase watershed by rainfall during winter (November to March) Cerdá, 1998; Inbar et al., 1998; Cannon, 2001; sediment yield, the interpretation of these re- storms, resulting in average precipitation rates Moody and Martin, 2001; Gabet, 2003). Thus, it sults must be balanced with the knowledge that of ~90 cm/yr along the Big Sur coast, ~165 is common to fi nd postwildfi re erosion models dams and debris basins do not capture the full cm/yr along the peaks of the Santa Lucia Range, incorporating strong rainfall dependencies (e.g., sediment load of the rivers, especially during and ~30 cm/yr in the central Salinas River val- Rowe et al., 1954; LACFCD, 1959; Rice, 1982; high loads that follow wildfi re (e.g., Keller et al., ley (Rantz, 1969). Because of the Arroyo Seco’s Keller et al., 1997; Reneau et al., 2007; Malmon 1997). Furthermore, these sedimentation studies steep slopes and high elevations—fi ve peaks et al., 2007; SEAT, 2008). typically do not yield data on changes to water on its drainage divide exceed 1400 m elevation There exists a great need to extend the under- discharge from the watershed or sediment grain (Fig. 2B)—the Arroyo Seco has the highest aver- standing of these wildfi re erosion effects to sizes (e.g., Lavé and Burbank, 2004). Thus, age runoff rates of all of the Salinas River tribu- suspended-sediment discharge at watershed to evaluate the effects of wildfi re on sediment taries (Farnsworth and Milliman, 2003). There scales (>100 km2). Shakesby and Doerr (2006) yield at watershed scales (>100 km2), one must is considerable variability in annual precipita- noted that watershed-scale studies are unfortu- attempt to extrapolate erosion rates or other tion, however, caused by the location of Pacifi c nately rare because of the diffi culty and costs of fi ndings from smaller plot-scale investigations, storm tracks and levels of atmospheric moisture, monitoring before and after a wildfi re and the which is not straightforward (e.g., Walling, which in turn are infl uenced by El Niño–South- potential for loss or destruction of monitoring 2006), or use dam and debris basin sedimen- ern Oscillation (ENSO) and Pacifi c Decadal sites during wildfi re. Much more effort has been tation records results, which may not fully ac- Oscil lation (PDO) cycles (Gabet and Dunne, placed in plot-scale experiments (1–10 m2) or count for total sediment yield. 2002; Andrews et al., 2004; Pinter and Vestal, fi rst-order drainage basin monitoring (~1 km2; Two large wildfi res within the Arroyo Seco 2005). The variability in precipitation results in e.g., Scott, 1993; Cerdá, 1998; Scott et al., watershed of central California (Fig. 2) provide annual water and sediment discharge rates that

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50 yr (Griffi n, 1978). Accounts of this fi re and 8 A Study area B 1977 Marble Cone fire 2 km its effects on the vegetation, soil conditions, 37°N and channel morphology are provided by Griffi n (1978) and Hecht (1981). The 1977 fi re burned 7 1A 2 intensely and uniformly throughout the chapar- N ral, and these hillslopes were observed to have “suffered heavy soil erosion during the January- 3 1B 50 km 4 to-March storms of 1978” as described quali- tatively by Griffi n (1978, p. 10). Griffi n (1978) BGS 1A observed that the upper layers of soil had been 36°N removed, and extensive networks of rills and 5 small gullies had been cut into steep slopes dur- C 2008 Basin Complex fire 6 2 km ing these 1978 storms. Hecht (1981) described the extensive fi lling and subsequent scour of USGS Stations: sand and gravel from the channels in the Car- 1A - AS nr Greenfield 1A 1B - AS below Reliz Cr. mel River watershed following the 1977 Marble 2 - Salinas R. at Spreckels Cone wildfi re and suggested that this fi ll-scour 3 - Carmel R. at Robles del Rio 4 - Big Sur R. nr Big Sur cycle transpired over an interval of 1–3 yr. 5 - San Antonio R. nr Lockwood Hecht (1981) also reported that sedimentation 35°N 6 - Nacimiento R. nr Bryson Salinas River of the Los Padres Reservoir of the Carmel River 7 - San Benito R. nr Willow Cr. watershed 8 - San Lorenzo R. at Big Trees during the fi rst winter after the 1977 fi re was 25 121°W 120°W 119°W times greater than the average annual sedimen- tation rate during the previous 30 yr. Figure 2. The central California study area and research stations. (A) Watershed map of the The July 2008 Basin Complex wildfi re burned Salinas River (shaded) and the Arroyo Seco (AS). U.S. Geological Survey (USGS) gauging the majority (~93%) of the gauged Arroyo Seco stations shown with numbered symbols (1–8), precipitation station at Big Sur (BGS) shown watershed (Figs. 2C and 3). Field- and satellite- with triangle. (B–C) Fire maps from 1977 and 2008 focused on the Arroyo Seco watershed based analyses of this fi re and its intensity were (shown with heavy line). Wildfi re extent is shown with shading. Peaks over 1400 m are provided by consortia of state and federal agen- shown with triangles. cies (BAER, 2008; SEAT, 2008), which noted thorough combustion of the chaparral, wide- spread occurrence of soil hydrophobicity, ex- vary by over an order of magnitude (Farnsworth while the 2008 wildfi re was similarly started tensive dry ravel throughout steep slopes, and and Milliman, 2003). by lightning, a second region of the 2008 burn moderate to high burn intensity classifi cations The Arroyo Seco watershed is dominantly was started by a human disturbance suspected for the majority of the Arroyo Seco watershed. chaparral (Table 1), which is characterized by to be arson. Both wildfi res were noted to have Postfi re erosion-control measures (e.g., hydro- dense communities of fi re-prone shrubby vege- burned at high intensities throughout the chapar- mulching and seeding) were not performed be- tation. It also lies wholly in the undeveloped ral (Griffi n, 1978; SEAT, 2008; Fig. 3). cause of concerns about native plant species and lands of the Ventana Wilderness of the Los The August 1977 Marble Cone wildfire potential weed introduction into the wilderness Padres National Forest and is thus not subject burned the entire gauged portion of the Ar- area (BAER, 2008; SEAT, 2008). Combined, to grazing or other landscape disturbances (cf. royo Seco watershed and parts of adjacent these factors indicated that the likelihood for Pinter and Vestal, 2005). Wildfi re is a regular watersheds, including those of the Big Sur and fl ooding and debris fl ows in the burned region phenomenon in the chaparral-dominated water- Carmel Rivers (Fig. 2B). Prior to this fi re, the was “high to very high” (BAER, 2008, p. 1), al- sheds of central and southern California, largely Arroyo Seco watershed had not burned for 30– though it was predicted that the “magnitude of owing to the hot, dry summers and the abundant fuel from vegetation and plant litter (Wells, TABLE 1. WATERSHED CHARACTERISTICS OF THE ARROYO SECO 1981; Rice, 1982; Greenlee and Langenheim, U.S. Geological Survey gauging station 11151870 1990; Keeley and Zedler, 2009). Because of the Station name Arroyo Seco near Greenfi eld high temperatures and low burn heights of wild- Drainage area 293 km2 Maximum elevation 1789 m fi re in chaparral, soil hydrophobicity is com- Average landscape slope at 30 m resolution 0.53 m/m monly observed after chaparral wildfi res (Fig. Surficial geology* 52.0% schist 1B; Wells, 1981; Rice, 1982). 22.1% sandstone 21.3% granodiorite 3.3% mudstone Recent Wildfi res in the Arroyo 1.3% plutonic rock † Seco Watershed Land cover 66.8% shrub 28.5% hardwoods 3.9% conifer Two recent wildfi res—the 1977 Marble Cone 0.6% herbaceous 0.1% barren/other fi re and the 2008 Basin Complex fi re—burned Percent burned in 1977 100% the majority of the Arroyo Seco watershed Percent burned in 2008 93% (Figs. 2B and 2C; Table 1). The ignition source *From data provided from Jennings et al. (1977). † of the 1977 wildfi re was a lightning strike, and From data provided from FRAP (2002).

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A B the 2008–2009 winter, one sample was obtained during the low-fl ow conditions of November 2008, and the remaining 19 samples were ob- tained between 15 and 18 February 2009 during the highest rainfall and discharge event of the water year. Eleven samples were taken during the 2009–2010 winter, and all were taken dur- ing storms with elevated river discharge. Sam- pling dates, times, and results are provided in the GSA Data Repository.1 Samples were obtained using a Wildco Hori- zontal Alpha Sampler that was lowered into the center of the main channel and tripped to cap- ture water from just below the surface. Rouse calculations for these sampling sites suggest that the fi ne fraction of the suspended sediment (i.e., Figure 3. Photographs of the burned chaparral and bare soils in the upper slopes of the <0.063 mm) and some sand should be wash load Arroyo Seco watershed following the 2008 Basin Complex wildfi re. Also shown is rapid (see part 2 of supplementary information [see regrowth of chaparral from the roots (A), burned overstory of pine forest (A, background), footnote 1]). Hence, our near-surface samples and a region of riparian and oak woodland that was unburned (B, background). Photos of fi ne (<0.063 mm) suspended-sediment con- were obtained on 17 November 2008 by J. Hatten. Burned chaparral in the foreground of centrations should be directly comparable to each photograph is 0.5 to 1 m tall. the depth-integrated fi ne suspended-sediment samples of the USGS, because uniform verti- cal concentration profi les would be expected for post-fi re damage will ultimately be determined sisting of 65 samples collected during water these grain sizes. by the intensity and duration of storms that im- years 1965–1983. Water samples were passed through a pact the burn area, particularly during the winter From these discharge and concentration 0.063 mm sieve to recover coarse suspended of 2008–09” (SEAT, 2008, p. 21). data, the USGS estimated daily and annual sus- sediment, and fi ne suspended sediment was pended-sediment fl uxes using the techniques of concentrated from the sieved water by cen- METHODS Porterfi eld (1972), and these estimates are avail- trifugation in 500 mL bottles at 3250 g for 10 able for water years 1963–1984 for site 1A. The min. After centrifugation, a 20 mL subsample Data Collection uncertainties of these load estimates were not of the overlying (i.e., supernatant) liquid was provided by the USGS, although we provide an removed from each bottle and fi ltered through USGS River Data—Arroyo Seco assessment of these uncertainties in the “Data a combusted glass fi ber fi lter (Whatman GF/A Our analyses focused on river discharge, Analyses” section below. All data were obtained with a 0.7 μm pore diameter) to determine the suspended-sediment concentration, and sus- through the USGS Surface Water Database portion of suspended sediment that did not pended-sediment discharge data from the (http://waterdata.usgs.gov/nwis/sw). settle during centrifugation. Sediments recov- USGS gauging station 11151870 (Arroyo Seco ered from sieving, centrifugation, and super- near Greenfi eld; 293 km2 drainage area). This River Sample Collection—Arroyo Seco natant subsampling were all oven-dried until station was designated site 1A for the purposes To characterize the effects of the 2008 wild- constants weights were achieved (12–24 h for of this paper (Fig. 2; Table 2). Mean daily and fi re, we collected suspended-sediment samples fi lters, 24–48 h for bulk samples). Suspended- annual peak discharge data were available for at two USGS gauging stations on the Arroyo sediment concentrations for each particle class this site for water years 1962–1986. In addi- Seco (sites 1A and 1B; Fig. 2A; Table 2). The (sieved, centrifuged, and supernatant) were cal- tion, we utilized all USGS suspended-sediment purpose of this sampling was to collect samples culated by dividing the dried mass of particles concentration and grain-size distribution results for total suspended solids and organic chemis- by the total volume of the water sampled, or from fl ow-integrated samples at this site, con- try analyses (e.g., Hatten et al., 2010). During subsampled in the case of the supernatant. The concentration of fi ne particles (<0.063 mm) was determined by adding the concentrations TABLE 2. U.S. GEOLOGICAL SURVEY (USGS) GAUGING STATIONS UTILIZED FOR THIS PAPER of centrifuged and supernatant particles, while USGS gauging Drainage area Record interval the coarse fraction (>0.063 mm) was the con- 2 Site no. station Station name (km ) (water years) centration of sieved material. 1A 11151870 Arroyo Seco near Greenfi eld 293 1962–2010* 1B 11152050 Arroyo Seco below Reliz Cr. 787 1996–2010 2 11152500 Salinas R. at Spreckels 10,770 1930–2010 1 3 11143200 Carmel R. at Robles del Rio 500 1957–2010 GSA Data Repository item 2012140, tabulated 4 11143000 Big Sur R. near Big Sur 120 1951–2010 river suspended-sediment sampling results from 5 11149900 San Antonio R. near Lockwood 562 1966–2010 water years 2009–2010, a comparison of the USGS 6 11148900 Nacimiento R. near Bryson 240 1972–2010 fl ow-integrated suspended-sediment samples and our 7 11156500 San Benito R. near Willow Cr. 645 1940–2010 near surface suspended-sediment samples, and a com- 8 11160500 San Lorenzo R. near Big Trees 275 1937–2010 parison of the suspended-sediment concentrations *This site was operated as a continuous-record streamfl ow site during water years 1962 to 1986, after which measured at the three sites sampled on the Arroyo operations were reduced to a partial-record program, for which instantaneous stage and limited flood-flow Seco, is available at http://www.geosociety.org/pubs measurements were recorded. /ft2012.htm or by request to [email protected].

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For each suspended-sediment sample, we within the Arroyo Seco watershed (station ARY; for the Arroyo Seco are estimated at ±46% and found an instantaneous river discharge from 300 m elevation), these data are only available ±50% for the loads estimated from the pre-1978 USGS gauging records. The USGS calculates for June 1999–2010, which does not include and 1978 water year data. Confi dence intervals discharge at 15 min intervals for the down- the important pre-1977 and post-1977 intervals. for the sediment discharge during subsequent stream gauge (site 1B). The primary gauge, The next nearest station with data available for water years (1979–1984) are much higher due site 1A, was maintained as a partially record- the duration of our study is the monthly record- to the smaller number of samples. Assuming a ing station between 1987 and 2010, for which ing National Weather Service rainfall gauge at similar standard error as calculated for the 1978 instantaneous stage was recorded continually. Big Sur (station BGS; 73 m elevation; Fig. 2A), water year, computed 95% confi dence intervals The USGS does maintain a stage-discharge rat- which has been operated since October 1913, al- range between ±68% and ±89% for water years ing curve for this site (http://waterdata.usgs.gov though these data were not collected for the ma- 1979–1981 and are greatest for 1984 at ±250%. /nwisweb/data/ratings/exsa/USGS.11151870 jority of the 1981 and 1982 water years (Fig. 4). Confi dence intervals in the Salinas River sedi- .exsa.rdb), and we used this rating curve and the The annual rainfall values at stations BGS and ment loads are computed to be ±90% using the instantaneous stage measurements to estimate ARY are correlated at r 2 > 0.8 using linear re- same methods. discharge at the time that our samples were col- gression, although total rainfall at BGS averages Suspended-sediment discharge from the lected. Our suspended-sediment sampling was 1.5 times that measured at ARY. Thus, for the Arroyo Seco at site 1A was estimated for water conducted only during and immediately follow- purposes of this paper, we utilize BGS data to years 2009 and 2010 using a combination of in- ing rainfall, and we were able to sample both provide information about rainfall rates in the stantaneous discharge and suspended-sediment rising and falling limbs of these events, although Arroyo Seco watershed. sampling data. A suspended-sediment rating no consistent hysteresis patterns were observed curve was developed from the power-law fi t be- over fl ood hydrographs. Data Analyses tween discharge and fi ne suspended-sediment We were able to sample both Arroyo Seco concentrations. As shown in the “Results” sec- sites during the 2009 water year but only site Sediment Discharge and tion, the least-squares fi ts of the 2009 and 2010 1B during the 2010 water year. A comparison Uncertainty Calculations data were not signifi cantly different, so all sam- of suspended-sediment concentrations for the The USGS calculated suspended-sediment pling data were combined to produce one rating two Arroyo Seco sampling sites during the fi rst discharge for the Arroyo Seco for water years curve utilized for both years. Fine suspended- year is presented in part 3 of the supplementary 1963–1984 and for the Salinas River for 1970– sediment discharge was estimated as the product information (see footnote 1). This comparison 1979, although uncertainties for these discharge of the instantaneous discharge values and concen- reveals that the discharge-concentration rela- estimates were not provided. Uncertainty in trations of fi ne suspended-sediment derived from tions did not vary signifi cantly between these these suspended-sediment discharge estimates the rating curve. Because the log-transformed sites. Thus, for comparative purposes with the can be evaluated by the scatter in the discharge residuals about the power-law rating curve were 1965–1983 USGS samples from site 1A, we and suspended-sediment concentration data not normally distributed (Kolmogorov-Smirnov present site 1A data from water year 2009 and from which these estimates were based. Fol- test, p = 0.13), a correction factor to account site 1B data from water year 2010. lowing Hicks et al. (2000), the 95% confi dence for the logarithmic transform of the data was intervals of sediment discharge can be estimated not utilized (cf. Ferguson, 1987; Cohn et al., USGS Data—Other Rivers as 2s/√(N), where s is the standard error in the 1989). The 95% confi dence intervals for 2009 For comparative purposes, we also evaluated rating curve (even though the USGS methods do and 2010 were estimated using the techniques water and sediment discharge records from other not utilize simple rating curve techniques), and described previously and were found to be ±37%. USGS gauges in the region. To evaluate whether N is the number of samples. Assuming a power- For the 2009 and 2010 sediment discharge wildfi re infl uenced suspended-sediment fl uxes law rating curve, the 95% confi dence intervals estimates, discharge was estimated for intervals from the larger Salinas River watershed, we ob- tained suspended-sediment concentration and 1977 Marble Cone 2008 Basin daily and annual sediment fl ux estimates from 200 A the USGS station 11152500 (10,770 km2; site 2; Fig. 2). For this station, the USGS collected 105 100 (cm) suspended-sediment samples during water years 1969–1986 and made fl ux estimates for water Precipitation 0 years 1970–1979. We also evaluated the effect B 10 1 of the two wildfi res on peak and total water dis- 100 Qss

/s) 0.1

3 10 Q

charge in the Arroyo Seco using comparisons 0.01 (Mt/yr) (m

1 Sediment with six additional USGS stations listed as sites 0.001 discharge Discharge 3–8 in Table 2 and Figure 2. 1960 1970 1980 1990 2000 2010 Water year Precipitation Data Lastly, precipitation data were obtained from Figure 4. Annual water year (October–September) hydrological the California Department of Water Resources characteristics of the Arroyo Seco study area. (A) Precipitation at California Data Exchange Center (CDEC), Big Sur, California (BGS). Mean annual precipitation during 1915– which makes hydrologic data available from 2010 was 103 cm. There was no data collection during water years numerous state and federal agencies (http:// 1982–1983. (B) Average annual discharge (Q, gray) and annual sus- cdec.water.ca.gov/). Although there is a weather pended-sediment discharge (Qss, black) for the Arroyo Seco (USGS station maintained by the U.S. Forest Service 11151870). Watershed-scale wildfi res are highlighted and named.

1134 Geological Society of America Bulletin, July/August 2012

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without stage measurements assuming expo- the sediment load. These concepts are applic- below. As detailed in the “Synthesis” section be- nential decreases in discharge with time be- able here because of the potential increases in low, the model was tested for a range of wildfi re tween the two measured end points, and these river discharge relative to precipitation follow- recurrence intervals to evaluate the implications data gaps occurred wholly during summer base ing a wildfi re, which may cause dilution pat- of stochastic wildfi res and fl oods on total sedi- fl ow and represented only 11% and 2% of the terns in the discharge–sediment concentration ment yield. total annual water discharge for the two years, relationships. respectively. To produce an independent metric of sedi- RESULTS ment yield from a suspended-sediment rating Comparisons of Prefi re and Postfi re Data curve, the river discharge–derived variables Comparison of Postwildfi re Rainfall The effects of the two wildfi res were ana- must be corrected for these effects of increased lyzed using the measurements and calculations discharge. For the simple case in which sus- The two large wildfi res in the Arroyo Seco of discharge, suspended-sediment concentra- pended-sediment rating curves shift vertically were followed by considerably different hydro- tions, and sediment yield. Analysis techniques in time without a change in the curve slope (b), logic conditions. The fi rst wet season after the included comparisons of the deviations between Warrick and Rubin (2007) showed that the rela- 1977 Marble Cone wildfi re was wetter than nor-

sampled suspended-sediment concentrations tive vertical shift in a rating curve (ra = a1/a2, mal, with almost 170 cm of rainfall (Fig. 4A).

and the river discharge–sediment concentra- where a1 and a2 are the a coeffi cients for prefi re This rainfall amount has a 25 yr annual recur- tion relationships (i.e., the “sediment rating and postfi re intervals, respectively) is equiva- rence interval over the 1915–2010 record at Big curves”). First, a power-law regression (Cs = lent to a power function of the relative increases Sur (BGS). In contrast, the 2008 Basin Complex b aQ , where Cs is suspended-sediment con- in both water (rw) and sediment discharge (rs), wildfi re was followed by a much drier winter,

centration, Q is discharge, and a and b are co- where rw = Q1/Q2, rs = Qs1/Qs2, and Qs is the sus- during which 90 cm of rainfall fell in Big Sur effi cients) was developed for the prewildfi re pended-sediment discharge. To convert a rating- (Fig. 4A). This is equivalent to 87% of the his-

interval of time. To evaluate whether the postfi re curve change (ra) into a sediment yield change torical mean and to a 1.7 yr annual recurrence

data were signifi cantly different from the prefi re (rs), the following relationship is suggested: during the 1915–2010 record. Subsequent years data, log-transformed residuals were computed after both wildfi res were much closer to the (b+1) between the measured concentrations and the rs = rarw . (1) long-term average rainfall (Fig. 4A). expected concentrations from the prefi re rating curve equation. The prefi re and postfi re residu- Because we could not detect a significant Arroyo Seco Suspended-Sediment als were compared using analyses of variance change in b over the postfi re record, Equation 1 Concentrations

(ANOVA) because these data were normally was used to correct the ra values derived from distributed as shown by Kolmogorov-Smirnov the rating curves for changes in sediment yield. Suspended-sediment concentrations during tests (p < 0.05). Similar corrections are needed when com- the fi rst winter after the 1977 Marble Cone wild- This framework for evaluating changes in paring annual water and suspended-sediment fi re were ~30 times greater than the previous pre- and postfi re suspended-sediment concen- discharge values over time. For example, if the 11 yr (Figs. 5A and 5B). These 30-fold increases tration data was also followed for suspended- relative postfi re increases in water and sediment in suspended-sediment concentrations were ob-

sediment discharge. Power-law regressions discharge are equivalent (i.e., rw = rs), the rela- served for both the fi ne and coarse fractions of were developed between prefi re annual sus- tionship between these fl ux rates will not deviate the suspended sediment when compared to in- pended-sediment discharge and both annual from historical values, and the discharge-load stantaneous discharge (Figs. 5A and 5B). The discharge and annual precipitation. Residuals rating curve will remain unchanged. Thus, the slopes (b) of least-squares regressions through about these regressions were placed into prefi re changes (or lack of changes) in a discharge-load the fi ne (b = 1.2) and coarse (b = 2.2) sediment and postfi re groups and compared with ANOVA rating curve over time may not provide an ade- data did not change signifi cantly after the wild- when applicable. Lastly, the effects of wildfi re quate index of sediment yield. In the case that fi re. During the subsequent years, suspended- on discharge were evaluated with similar com- sediment yield is altered to a larger scale than sediment concentrations (total, coarse, and fi ne)

parisons of residuals about prefi re regressions water yield (i.e., rs > rw) such as was the case decreased with respect to discharge, and by the

between precipitation and annual peak and total here, rs can be found by: seventh year after the wildfi re, concentrations discharge. were approximately equivalent to the prefi re rsa rs = , (2) values (Figs. 6A and 6B). rw Rating Curve Corrections Suspended-sediment concentrations after

Patterns and trends in suspended-sediment where rsa is the measured vertical offset in the the 2008 Basin Complex fi re were only mod- rating curves are generally associated with the water-versus-sediment discharge plot between erately higher than those without infl uence of sediment load of rivers (e.g., Hicks et al., 2000; prefi re and postfi re data (Warrick and Rubin, wildfi re (Fig. 5C). During the fi rst year after Hu et al., 2011). However, the river discharge 2007). the wildfi re, the mean ratio of the measured rate can also play a signifi cant role in rating- fi ne suspended-sediment concentrations and curve shapes and parameters (Syvitski et al., Monte Carlo Simulations those expected from the regression through 2000). For example, an increase in river dis- Lastly, the millennial-scale infl uences of prefi re concentrations was only 2.3 (Fig. 5C). charge with no change in sediment discharge wildfi re on suspended-sediment yield were in- During the second postfi re year, this ratio was will result in lower suspended-sediment con- vestigated using Monte Carlo simulations of 3.1 (Fig. 6C). Because these offsets were not centrations because of dilution (Warrick and the Arroyo Seco watershed. These simulations signifi cantly different (p = 0.33), there was Rubin, 2007). The resulting suspended-sedi- were conducted on an annual basis with rela- not a fundamental decrease in fi ne sediment ment rating curve for this scenario will shift tionships and patterns derived from the results concentrations during the two years of postfi re downward, even though no changes occurred to of this study presented in the “Results” section sampling after the 2008 Basin Complex fi re.

Geological Society of America Bulletin, July/August 2012 1135

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1977 Marble Cone 2008 Basin Complex 100,000 A C Prefire (pre-1978) Prefire (pre-1978) 10,000 Year 1 (1978) Year 1 (2009)

1000

100 concentration (mg/l) 10 2 2

Fine suspended-sediment r = 0.76 r = 0.55 r 2 = 0.69 r 2 = 0.69 1 1 10 100 1000 1 10 100 1000 100,000 Instantaneous river discharge (m3/s) B 10,000 Figure 5. Fine and coarse suspended- sediment concentrations for the Arroyo 1000 Seco watershed comparing samples col- lected without the infl uence of wildfi re 100 (pre-1978) with samples collected during the fi rst year following the 1977 Marble 10 Cone wildfi re (A, B) and the 2008 Basin Complex wildfi re (C). Fine sediment and concentration (mg/l) 1 r 2 = 0.90 coarse sediment are separated by the 2

Coarse suspended-sediment r = 0.75 sand-silt threshold of 0.063 mm. Power- 0.1 law regressions (lines) and correlations 1 10 100 1000 are shown. Equations for these regres- Instantaneous river discharge (m3/s) sions are given in Table 3.

Combined, the two years of postfi re concentra- the expected value from the discharge-fl ux re- the USGS estimates for the fi rst year following tions averaged 2.8 times greater than the prefi re lationship that existed during the 11 preceding the 1977 wildfi re (Fig. 7B). regression. However, an unpaired Student t-test years (Fig. 7A). Sediment discharge during the A more independent assessment of the ef- shows that the prefi re (pre-1978) and postfi re 2–4 yr after the 1977 fi re was 5–6 times greater fects of wildfire on sediment yield can be residuals about the prefi re regression were sig- than the prefi re relationship (Fig. 7A), and these obtained with comparisons to precipitation nifi cantly different at p < 0.002, suggesting that values exceeded the maximum deviations from because river discharge rates were likely infl u- the concentrations after the 2008 wildfi re were the prefi re regression and the uncertainty in enced by the wildfi res. The relation between signifi cantly elevated compared to unburned these estimates. The annual sediment discharge annual precipitation and suspended-sediment conditions. estimates after year 4—including those from the discharge changed after both wildfi res, and exceptionally wet 1983 water year—fall within these changes were greatest following the Arroyo Seco Suspended-Sediment the range of values observed during the prefi re 1977 Marble Cone wildfi re (Fig. 8). Although Discharge record (Fig. 7A). annual precipitation was positively correlated The total suspended-sediment discharge after with suspended-sediment discharge during Suspended-sediment discharge for the Arroyo the 2008 wildfi re was estimated by the sum of the prefi re record, there was substantial scat- Seco watershed reached unprecedented rates the fi ne and coarse suspended-sediment dis- ter in this relationship, as shown by the 0.40

following the 1977 wildfi re (Fig. 4B). The sus- charge. Fine suspended-sediment discharge was log10 units (or 2.5-fold) standard error about pended-sediment discharge during water year estimated using the best-fi t power-law regres- the power-law regression and by a maximum

1978 was ~3.1 Mt, which greatly exceeded the sion through the combined 2009 and 2010 data deviation of 0.66 log10 units (or 4.6-fold). Sedi- 1.04 2 previous maximum of 0.13 Mt during 1969. following this fi re (Cfs = 3.88Qinst ; r = 0.74). ment discharge values for years 1–3 after the Averaged over the drainage area, the 1978 sedi- Coarse suspended-sediment discharge was es- 1977 Marble Cone wildfi re were 37, 20, and ment discharge was equivalent to a suspended- timated by assuming a 2.5-fold increase in the 15 times greater, respectively, than the prefi re sediment yield of 11,000 t/km2/yr. prefi re regression shown in Figure 5B. These regression, far exceeding the prefi re variance By comparing the estimates of suspended- calculations resulted in estimates of 0.027 Mt (Fig. 8A). During the fi rst year following the sediment discharge with annual river discharge, during the fi rst postfi re year and 0.31 Mt for the 2008 Basin Complex wildfi re, the sediment it can be shown that sediment discharge from second year (Fig. 4). Thus, our estimate of sus- discharge was 7.2 times greater than the prefi re the Arroyo Seco watershed during the fi rst year pended-sediment discharge during the fi rst year relationship, and during the subsequent year, after the 1977 wildfi re was 27-fold greater than after the 2008 wildfi re was 120-fold lower than this increased to 16 times (Fig. 8B).

1136 Geological Society of America Bulletin, July/August 2012

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1977 Marble Cone 2008 Basin Complex 100,000 A C Year 2 (1979) Year 1 (1978) Year 2 (2010) 10,000 Year 3 (1980) Year 4 (1981) Year 1 (2009) Year 7 (1984) 1000 Prefire Prefire

100

concentration (mg/L) 10 Fine suspended-sediment

1 1 10 100 1000 1 10 100 1000 100,000 Instantaneous river discharge (m3/s) B Year 1 (1978) 10,000 Prefire 1000

100 Figure 6. Fine and coarse suspended-sedi- 10 ment concentrations for the Arroyo Seco watershed for years 2–7 after the 1977

concentration (mg/L) 1 Marble Cone (A, B) and the 2008 Basin Complex fi re (C). For comparison purposes, Coarse suspended-sediment 0.1 power-law regressions (lines) are shown for 1 10 100 1000 the prefi re period and the fi rst year after the Instantaneous river discharge (m3/s) wildfi re (year 1) from Figure 5.

Arroyo Seco Water Discharge cantly higher with respect to rainfall (40% on Hydrological effects can also be assessed average, p < 0.02), and this higher rate of dis- by comparing discharge records with those of Analyses of river discharge after each wild- charge was observed through water year 1984 similar unburned watersheds within the region fi re were made with mean and peak annual (Fig. 9A). Similarly, water discharge during the (Fig. 2; Table 2). For the comparative watersheds discharge records. Comparisons between pre- two years following the 2008 wildfi re averaged that were simultaneously burned in 1977 (the cipitation and these discharge metrics reveal 40% greater than expected rates extrapolated Carmel, Big Sur, and San Antonio Rivers), that although the postfi re discharge was gener- from prefi re relationships (Fig. 9C), although the rates of annual total and peak discharge did not ally within the historical bounds of the prefi re the sample size (n = 2) does not allow for evalu- change between pre- and postwildfi re intervals data, there were measurable increases in aver- ation by ANOVA. In contrast, there were not of time, suggesting that hydrologic responses age river discharge (Figs. 9A and 9C). For ex- statistically signifi cant differences in peak dis- were generally similar across these watersheds ample, the annual average discharge during the charge between pre- and postfi re intervals of (data not shown). Comparison of the unburned fi rst three years after the 1977 fi re was signifi - time (Figs. 9B and 9D). watersheds (the Nacimiento, San Benito, and

1977 Marble Cone 2008 Basin Complex 10 Figure 7. Annual river water A B 1 and suspended-sediment dis- Prefire (pre-1978) Prefire (pre-1978) 10,000 1 Year 1 (1978) Year 1 (2009) charge for the Arroyo Seco near Year 2 (1979) 3 Year 2 (2010) 6 2 1000 Greenfield (USGS 11151870) Year 3 (1980) 2 0.1 Year 4 (1981) 5 highlighting the effects of the /yr) Year 5 (1982) 4 7 2 1977 and 2008 wildfi res (A and Year 6 (1983) 1 100 B, respectively). A power-law 0.01 Year 7 (1984) (t/km regression (line; r 2 = 0.88) is 10 shown through the prefi re data. discharge (Mt/yr) 0.001 Suspended-sediment 2 Vertical lines are 95% confi- r = 0.88 1 0.0001 dence intervals of the sediment 0.1 1 10 0.1 1 10 Suspended-sediment yield discharge estimates. Mean annual river discharge (m3/s)

Geological Society of America Bulletin, July/August 2012 1137

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1977 Marble Cone 2008 Basin Complex 10 A B 1 Prefire (pre-1978) Prefire (pre-1978) 1 Year 1 (1978) Year 1 (2009) Year 2 (1979) Year 2 (2010) Year 3 (1980) 3 2 Year 6 (1983) 6 0.1 Year 7 (1984) 2

7 1 0.01

Annual suspended- 0.001 2 sediment discharge (Mt/yr) r = 0.80 r 2 = 0.80 0.0001 50 100 200 50 100 200 Annual precipitation (cm/yr) Annual precipitation (cm/yr)

Figure 8. The relation between suspended-sediment discharge from the Arroyo Seco watershed (USGS 11151870) and precipitation at Big Sur (BGS) highlighting the 1977 and 2008 wildfi res (A and B, respectively). Power-law regression lines and correlation coeffi - cients are shown only for prefi re data. Vertical lines are 95% confi dence intervals of the sediment discharge estimates.

1977 Marble Cone 2008 Basin Complex 100 A C Prefire (pre-1978) Prefire (pre-1978) Year 1 (1978) Year 1 (2009) /s) Year 2 (2010)

3 Year 2 (1979) 10 Year 3 (1980) Year 6 (1983) Year 7 (1984)

1 discharge (m Annual average river r 2 = 0.96 r 2 = 0.96 0.1 10 100 1000 10 100 1000

1000 B D /s)

3 100 (m

r 2 = 0.76 r 2 = 0.76

Annual peak river discharge 10 10 100 1000 10 100 1000

Annual precipitation (cm/yr) Annual precipitation (cm/yr)

Figure 9. The relation between precipitation at Big Sur (BGS) and the annual average and annual peak discharges from the Arroyo Seco watershed (USGS 11151870) highlighting the 1977 (A, B) and the 2008 (C, D) wildfi res. Power-law regression lines and correlation coeffi - cients are shown only for prewildfi re (pre-1978) data.

1138 Geological Society of America Bulletin, July/August 2012

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San Lorenzo Rivers) to the burned Arroyo Seco 1977 Marble Cone watershed, however, reveals higher annual av- 100 A /s)

erage discharge in the burned watershed but 3 Prefire (pre-1978) no difference in peak discharge. For example, Year 1 (1978) Year 2 (1979) Arroyo Seco discharge is compared to the San Year 3 (1980) Lorenzo River in Figure 10. During the fi rst four Year 4 (1981) 10 years after the 1977 fi re, mean annual discharge Year 5 (1982) Year 6 (1983) in the burned watersheds was 87% higher (Fig. Year 7 (1984) 10A). These differences are signifi cant using an unpaired Student t-test (p < 0.001). Annual peak discharge did not show signifi cant deviations 1 from the historical patterns (Fig. 10B). Arroyo Seco

Integration of Sediment Yield Results r 2 = 0.93 0.1

In Figure 11, we compile all of the relative average annual discharge (m 0.1 1 10 100 changes in suspended-sediment discharge re- ported herein. These data come from three San Lorenzo River 3 sources: changes in the discharge-concentration average annual discharge (m /s) relationship (Figs. 5 and 6), changes in the dis- 1000 charge–sediment discharge relationship (Fig. 7), B and changes in the rainfall–sediment discharge /s)

relationship (Fig. 8). All of the values in Figure 3 11 are taken from the ratio between measured values and expected values from regressions through the prefi re data (Table 3). There are discrepancies, however, in these 100 metrics (Figs. 11B and 11E). Specifi cally, the discharge-based metrics for sediment discharge ( f [Q], blue symbols) are consistently lower

than the precipitation-based metric ( f [P], red Arroyo Seco symbols; Figs. 11B and 11E). This should be 2 expected, as noted in the previous section, be- r = 0.61 cause discharge will not be an independent 10 variable when it increases after a fi re. Thus, we annual peak discharge (m 1 10 100 1000 used Equations 1 and 2 to correct the relative increases in suspended-sediment concentrations San Lorenzo River 3 and sediment discharge with respect to fl ow using annual peak discharge (m /s) r derived from comparisons of mean annual w Figure 10. Comparison of the annual average and annual peak dis- discharge with precipitation (Figs. 9A and 9C). charges in the Arroyo Seco (USGS 11151870) with the San Lorenzo After these corrections, the three estimates of River (USGS 11160500) before and after the 1977 Marble Cone the relative change in sediment yield are much wildfi re. Postwildfi re water years are highlighted with fi lled sym- more consistent (Figs. 11C and 11F). Increases bols. Power-law regression lines and correlation coeffi cients are in sediment yield were observed to last for sev- shown only for prewildfi re (pre-1978) data. eral years after the fi res (Figs. 11C and 11F). The 1977 wildfi re caused an initial increase in sediment yield that was 35 times greater than expected without fi re, and sediment yield de- possibilities in the discussion. In contrast, sedi- to evaluate whether wildfi re infl uenced sedi- creased somewhat steadily with time (Fig. 11C). ment yield during the fi rst year following the ment concentrations and fl uxes from this larger Unfortunately, data could not be generated for 2008 fi re was 5 times greater than expected dur- coastal watershed. Unfortunately, we were only 1981 and 1982 because there were no precipi- ing unburned conditions, and this increased to 9 able to evaluate the effects of the 1977 Marble tation data collected on which to base a cor- times during year 2 (Fig. 11F). Cone wildfi re because of the limited data collec- rection. Although the observations of sediment tion at this site. yield during water year 1983 were consistent Observations from the Salinas Watershed During the 1977 Marble Cone wildfire, with continued decay, water year 1984, which ~400 km2 of the Salinas watershed were burned. was the seventh year following the fi re, revealed Sediment and water discharge increased sub- Therefore, we made the following fi rst-order increases in all sediment yield metrics (Fig. stantially in the Arroyo Seco watershed follow- approximations for the Salinas River: (1) the 11C). It is not evident from these data whether ing wildfi re. Because the sediment yield effect burned area had a sediment yield response these elevated sediment yields were related to was pronounced, we looked downstream to data similar to the Arroyo Seco (i.e., ~35-fold in- the 1977 wildfi re or not, so we consider both from the Salinas River gauge (site 2; Fig. 2) crease in sediment yield), and (2) the remaining

Geological Society of America Bulletin, July/August 2012 1139

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1977 Marble Cone 2008 Basin Complex unburned watershed had a relatively constant 200 A D sediment yield. Only ~9000 km2, or 81%, of the Salinas River watershed are undammed and 100 actively contributing suspended sediment to the

(cm/yr) No No river (Willis and Griggs, 2003), so a total of P P Precipitation 0 4.4% of the undammed Salinas River watershed 100 Css burned in 1977. A 35-fold increase in sediment B E Qss yield from this burned area without a change in f(P) the sediment yield of the remaining watershed 10 f(P) f(Q) would result in a 2.5-fold increase in the total f(Q) sediment fl ux. 1 Consistent with this hypothetical effect on

sediment yield sediment yield, suspended-sediment concentra- actual to expected

Uncorrected ratio of 0.1 tions from USGS sampling of the Salinas River 100 were signifi cantly higher than normal during the C F fi rst two years after the 1977 fi re (Fig. 12). For example, the fi ve highest (and 10 of the top 14) 10 –kt e–kt e suspended-sediment concentrations measured LA in the river were obtained during these two post- 1 LA fi re years. Although these postfi re samples were Ratio of taken at higher discharge rates than the pre- sediment yield 0.1 fi re samples (4 of the top 5 sampled discharge actual to expected pre- ’78’79 ’80 ’81 ’82 ’83 ’84 ’09 ’10 rates occurred postfi re), we note that postfi re ’78 Water year Water year suspended-sediment concentrations from the lowest discharge rates deviate to a greater extent Figure 11. The effect of time after the Marble Cone (A–C) and Basin Complex (D–F) wild- from prefi re concentrations (Fig. 12). This non- fi res on the Arroyo Seco suspended-sediment discharge (Qss) and concentrations (Css) rela- parallel shift is different from the parallel shift tive to the prefi re (pre-1978) conditions. The relative changes shown in B and E are the ratio observed in the Arroyo Seco (cf. Fig. 5). between measured values and expected values from prefi re regressions shown in Figures Statistical analyses of the Salinas River data 5, 7, and 8. These prefi re regressions are either with respect to precipitation “f(P)” or dis- can be made with a comparison between the charge “f(Q).” The values in B and E have been corrected for the effects of discharge in prefi re and postfi re concentrations for the most C and F using Equations 1 and 2. A least-squares fi t exponential function through the cor- heavily sampled discharge range of the postfi re rected data was found to have a 1.4 yr half-life (k = 0.51) and is shown with a gray line in C record (40–300 m3/s; Fig. 12) using an unpaired and F. The LACFCD (1959) vegetation-based decay function is also shown with a light-blue Student t-test. The mean suspended-sediment line and denoted with “LA” in C and E. Annual precipitation in A is shown for Big Sur concentrations with this discharge range (2420 (BGS); “No P” denotes years with incomplete precipitation records; and incomplete rec- and 8240 mg/L, respectively) are signifi cantly ords during 1981 and 1982 account for the missing data in C. Box plots show the following different at p < 0.001 (both linear and logarith- percentiles: 5% and 95% (whiskers), 25% and 75% (box), and 50% (line). Whiskers on the mically transformed), even though the mean symbols represent 95% confi dence intervals. discharge rates of these samples (122 and 116 m3/s, respectively) are not signifi cantly different (p = 0.83). Thus, even though there is substan- TABLE 3. POWER-LAW REGRESSION EQUATIONS FOR THE tial scatter in the prefi re samples, the postfi re LEAST-SQUARES FITS SHOWN IN FIGURES OF THIS PAPER Figure numbers Equation* Description r 2 samples were more likely to have elevated 1.24 concentrations of suspended sediment, and the 5A, 5C, 6A, and 6C Cfs = 0.850Qinst Arroyo Seco annual prefi re (pre-1978) 0.69 1.16 5A, 5C, 6A, and 6C Cfs = 34.7Qinst Arroyo Seco annual postfi re (1978) 0.76 mean rate of this increase was ~3-fold. 2.25 5B and 6B Ccs = 0.00923Qinst Arroyo Seco annual prefi re (pre-1978) 0.75 2.10 Suspended-sediment discharge from the 5B and 6B Ccs = 0.600Qinst Arroyo Seco annual postfi re (1978) 0.90 1.58 5C and 6C Cfs = 0.438Qinst Arroyo Seco annual postfi re (2009) 0.55 Salinas River during the fi rst year after the 1977 2.29 7 Qs-an = 0.000581Qan Arroyo Seco annual prefi re (pre-1978) 0.88 fi re was substantially greater than any other –13 4.96 8 Qs-an = 7.52e Pan Arroyo Seco annual prefi re (pre-1978) 0.80 2.27 year in the record (Fig. 13). Over 15 Mt of sus- 9A and 9C Qan = 0.0000819Pan Arroyo Seco annual prefi re (pre-1978) 0.96 1.90 9B and 9D Qpeak = 0.0266Pan Arroyo Seco annual prefi re (pre-1978) 0.76 pended sediment were discharged during water 1.15 10A Qan1 = 0.815Qan2 Arroyo Seco annual prefi re (pre-1978) 0.93 0.575 year 1978, which is almost 10 times the next 10B Qpeak1 = 10.6Qpeak2 Arroyo Seco annual prefi re (pre-1978) 0.61 0.226 greatest rate of 1.6 Mt during 1973 (Fig. 13). 12 Cfs = 2504Qinst Salinas River prefi re (pre-1978) 0.27 0.594 12 Cfs = 107Qinst Salinas River postfi re (1978–1979) 0.51 Unfortunately, the sediment discharge record 13 Q = 0.00732Q 1.77 Salinas River annual prefi re (pre-1978) 0.97 s-an an does not include other water years with high dis- 14B R = 0.0101Pan – 0.464 Arroyo Seco postfi re (all) 0.78 1.72 14C R = 0.000405Pan Arroyo Seco postfi re (all) 0.37 charge (e.g., water years 1969, 1980, or 1983),

*Variables include: Cfs—concentration of fi ne suspended sediment (mg/L); Ccs—concentration of coarse for which a better comparison could be made. suspended sediment (mg/L); Pan—annual precipitation (cm/yr); R—ratio of expected to measured sediment 3 Thus, during the two years after the 1977 fi re, yield increase; Qan—average annual river discharge (m /s); Qan1 and Qan2—average annual river discharge of the 3 3 the Salinas River discharged suspended sedi- y-axis and x-axis variables (m /s), respectively; Qinst—instantaneous river discharge (m /s); Qpeak—annual peak 3 3 river discharge (m /s); Qpeak1 and Qpeak2—annual peak river discharge of the y-axis and x-axis variables (m /s), ment at higher concentrations and at higher rates respectively; Q —annual suspended sediment discharge (Mt/yr). s-an than was expected from historical records. The

1140 Geological Society of America Bulletin, July/August 2012

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1977 Marble Cone the production and erosion of dry ravel talus dur- 100,000 ing the 2008–2009 winter, and unpublished iso- Prefire (pre-1978) topic characterization of the 2009 Arroyo Seco Years 1–2 (1978–’79) suspended sediment suggests it was dominated 10,000 by surface soil materials (0–1 cm soil depth; J. Hatten, 2011, personal commun.). Combined, this provides evidence that the differences in 1000 sediment yield between 1978 and 2009 were re- lated to precipitation-enhanced hillslope erosion processes, such as rilling and mass movements (cf. Fig. 1C). 100

concentration (mg/L) Although the Arroyo Seco exhibited 100- fold differences in the sediment yield during Fine suspended-sediment the fi rst postfi re years, both years showed sig- 10 nifi cant increases in sediment yield relative to 0.1 1 10 100 1000 expected values for unburned conditions (Fig. 11). Considering that (1) the time interval be- River discharge (m3/s) tween preceding wildfi res was roughly equiva- Figure 12. The relation between river discharge and fi ne (less than lent (30–50 yr and 31 yr, respectively), (2) both 0.063 mm) suspended-sediment concentration for the Salinas River fi res burned with moderate to high intensities, at Spreckels (USGS 11152500) before and after the 1977 Marble and (3) there was no evidence for exhaustion Cone wildfi re. Samples are shown only from “stormfl ow” sampling, of soil within the watershed (BAER, 2008), the which is defi ned by sampling within 4 d of rainfall and a peak in fundamental differences between these post- river discharge. Other samples obtained during base-fl ow condi- fi re years were the total amount and intensity tions are not shown. Power-law regressions are shown with lines. of rainfall. Next, we evaluate whether rainfall contributed signifi cantly to sediment produc- tion rates. magnitude of these increases (roughly 3-fold) 1977 Marble Cone fi re were similar to sediment Statistical models for postwildfi re sediment was consistent with the Arroyo Seco results, yields from other watersheds burned by this yield suggest large initial increases and expo- using a simple sediment yield mass balance. fi re. For example, Hecht (1981) noted that the nential (or near-exponential) decay in sediment Padres Reservoir within the upper Carmel River yield with time (e.g., LACFCD, 1959; Wells, SYNTHESIS watershed experienced unprecedented sedimen- 1981; Swanson, 1981; Cerdà, 1998; Lavé and tation during the 1977–1978 winter. Assum- Burbank, 2004). In Figures 11C and 11F, we Sediment Yield in the Arroyo Seco ing a 1600 kg/m3 bulk density for sediment in show the exponential-like decay model de- Following Wildfi res the reservoir, Hecht’s (1981) results suggested veloped by LACFCD (1959), for which the an upper Carmel River sediment yield of 6800 vegetation-related response of postfi re erosion The Arroyo Seco watershed responded to t/km2/yr during the 1977–1978 winter, or 62% includes a fi rst-year 15.3-fold increase in yield the 1977 and 2008 wildfi res in fundamentally of the measured suspended-sediment yield of and a nonlinear decay (line denoted “LA”). This different ways. For example, fi rst-year sedi- the Arroyo Seco. model was recently evaluated and supported by ment yields following these wildfi res varied The observations of Griffi n (1978) suggest the analyses of sediment yield in the San Gabriel by over 100-fold (11,000 vs. 90 t/km2/yr), even that the landscape responded to the 1977 fi re Mountains of southern California by Lavé and though the wildfi re burn severity and extent and 1977–1978 precipitation with extensive soil Burbank (2004). We also show a least-squares were roughly equivalent. The exceptional sedi- loss, rilling, gullying, and mass movements. In fi t exponential function through the fi rst six ment yields in the Arroyo Seco following the contrast to these observations, we only observed postfi re years, which was found to have a half- life of 1.4 yr (line denoted “e–kt”; Figs. 11C and 11F). When the 1984 water year is included in Figure 13. A comparison of an- the regression, an exponential decay with a half- nual river discharge and annual 100 life of 2.0 yr is computed. suspended-sediment discharge 10 1 While neither one of these postfi re decay for the Salinas River at Spreckels functions adequately describes the time-vary- 1 (USGS 11152500) for the avail- 2 ing change in sediment yield (Figs. 11C and able data (1970–1979). Annual 0.1 11F), they are found to be useful, especially values for water year 1978 are 0.01 when combined with rainfall. For example, denoted with “1,” and 1979 val- 0.001 the residuals about both decay functions, ex- ues are denoted with “2.” The pressed as ratios of the actual to modeled sedi-

discharge (Mt/yr) 0.0001 power-law regression for the 2 ment yield, were signifi cantly correlated with

Suspended-sediment r = 0.97 prefi re record is shown (solid 0.00001 annual rainfall (Fig. 14). The majority (78%) 0.01 0.1 1 10 100 line, r 2 = 0.97). Whiskers on the of variance in the exponential decay residuals 3 symbols represent 95% confi - Mean annual discharge (m /s) (half-life = 1.4 yr) could be explained by an- dence intervals. nual precipitation (Fig. 14B). The LACFCD

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16 A through prefi re data shown in Figure 8A and listed in Table 3, F(t) is the fi re factor during 8 the tth year following a wildfi re, and E is an error term to incorporate the appropriate level of 0 Frequency uncertainty in the model. Thus, annual rainfall Post-1977 formed the basis for suspended-sediment dis- B Post-2008 Figure 14. (A) Annual precipi- charge, and wildfi re acted as a stochastic pertur- tation histogram from BGS 1 bation to sediment discharge. for 1915–2010 (shown for com- For each year, a random annual precipitation parison). (B–C) The relation was generated from the rainfall probability dis- between annual precipitation 0.5 tribution of the 1915–2010 record at Big Sur. (at BGS) and the ratio between Because there was substantial variance in the measured and predicted post- fundamental precipitation-sediment discharge sediment yield to 2 fi re suspended-sediment yields. Ratio of measured r = 0.78 exponential function relationship defi ned by m and n (Fig. 8A), an- Predictions utilize the relation- 0 nual offsets (E) were generated with a unique 4 ships from (B) least-squares C random number and a normally distributed vari- fi t of an exponential function ance density function fi t to the residuals between through the first 6 yr after 3 the log-transformed sediment yield values and the fi re, and (C) the LACFCD the best-fi t power-law regression shown in Fig- (1959) functions that account 2 ure 8A. The standard deviation of this density for the effects of vegetation function was 0.376. growth following wildfi re. Wildfi re was added using a burn model that 1 allows only for the possibility of complete burn-

sediment yield to 2 Ratio of measured

LACFCD prediction r = 0.37 ing of the watershed. Although this model could 0 be easily modifi ed to include partial burning of 40 80 120 160 200 the watershed (e.g., Gabet and Dunne, 2003), we Precipitation (cm/yr) used the more simple model because: (1) recent assessments suggest that large fi res (~100 km2) are historically dominant in California shrub- model, in contrast, generally underpredicted Monte Carlo Simulation lands (Keeley and Zedler, 2009), and (2) using the Arroyo Seco sediment yield (most residuals an incomplete (or “patchy”) burn model with an are greater than unity; Fig. 14C), and rainfall Our results suggest that the effects of wildfi re equivalent average fi re recurrence has the same could explain only 37% of the variance in these on watershed-scale sediment yields can be ex- long-term effects on total sediment yield (al- residuals. The combination of the exponential ceptional and persist for several years after the though different annual yields) as those shown model and the linear residual model shown in burn. However, the 15 yr of suspended-sediment here. The annual probability for fi re was based Figure 14B can explain 90% of the variance sampling in the Arroyo Seco does not provide on a fuel model that assumed no wildfi re during in sediment yield after both wildfi res (p < 0.05), an assessment of the century- to millennial- the fi rst 5 yr following the previous fi re, and a and this outperforms the LACFCD and its re- scale effects of wildfi re on sediment yield. Here, linearly increasing fi re probability with time sidual model, which can explain only 80% of we evaluate these effects using Monte Carlo afterward. This linear increase is similar to the the sediment yield variance. Combined, these simulations, a technique that is ideally suited to measurements of annual burn probability in results suggest that there is a strong infl uence evaluate long-term sediment yields in settings central California by Moritz (2003). of both wildfi re and rainfall on sediment yield such as California’s chaparral ecosystem (Rice, During the years after a wildfi re, the increase of this watershed. 1982). The purpose of this exercise is to evalu- in watershed sediment yield was defi ned by the Because the 1978 water year had an unusu- ate the ways in which wildfi res infl uence sedi- fi re factor (F): ally large sediment yield, it also is valuable to ment yields over intervals of time that are both F(t) = 1 (t ≥ 8) assess the approximate recurrence interval of greater than sampling records and more relevant , (4) ⎡ −kt⎤ this event. Although there continues to be de- to geologic records. = ⎣Ce ⎦ (t < 8) bate about the natural recurrence intervals and Because we do not have adequate informa- sizes of wildfi re (e.g., Griffi n, 1978; Keeley tion to develop a process-based model (e.g., where t is the year number following a wild- and Zedler, 2009), coastal shrublands of Cali- Gabet and Dunne, 2003), we simulated the fi re (fi rst year = 1), C is a factor that includes fornia likely burn every 50–100 yr without the suspended-sediment yield of the Arroyo Seco the magnitude of the postfi re sediment yield re- added pressures of human-sourced ignitions using a simple wildfi re- and precipitation-based sponse and the precipitation enhancement of this (Syphard et al., 2007), and large fi res such as the model such as suggested by Rice (1982) and response, and k is the rate of exponential decay , two recorded here are not unusual (Keeley and Swanson (1981). Annual sediment discharge which is equivalent to −0.5062 for the 1.4 yr

Zedler, 2009). The 1978 precipitation had an from the watershed (Qs–an) was predicted from: half-life. The values of C are defi ned by the best- ~25 yr recurrence interval based on the 1915– fi t exponential decay function (Fig. 11C) and the n 2010 rec ords, which suggests that the combina- Qs−an = mPan Ft( )E, (3) linear function between sediment yield residuals tion of wildfi re and fl ood for 1977–1978 had and precipitation shown in Figure 14B:

a recurrence interval over 1000 yr (computed where Pan is annual precipitation, m and n are range ~1250–2500 yr). coeffi cients from the least-squares regression C = 46.5( 0.0101Pan − 0.4957). (5)

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A model run consisted of 10,000 simulated Recurrence interval (yr) years. An example of the annual exceedance 10 100 1000 10,000 Figure 15. The effect of wild- 10 probability function of sediment yield with and fi re on the sediment yield of the without wildfi res having 100 yr average recur- Arroyo Seco watershed from 10,000 rence intervals is shown in Figure 15. These Wildfire two separate 10,000 year Monte 1 results show that for the vast majority of the Carlo simulations. Simulations annual records, the sediment yield with and 1000 use either a precipitation-infl u- No wildfire

without wildfi re differed by negligible amounts. 0.1 /yr) enced sediment yield response 2 For example, 95% of the records differed by to wildfi re (“wildfi re”) or no (Mt/yr) 100 (t/km 20% or less (Fig. 15). Sediment yield deviated wildfire effects on sediment strongly for the years with the largest sediment yield (“no wildfi re”) as noted 0.01 discharge, and wildfi re caused sediment yield to Suspended-sediment yield in the text. Average wildfi re re- 10 be up to 13 times higher than expected to oc- currence interval for the data Suspended-sediment discharge cur when wildfi re effects were excluded (Fig. 0.001 presented was 100 yr. 1 0.1 0.01 0.001 0.0001 15). The infrequent years with massive sedi- ment discharge were similar in scale (~10,000 Annual exceedance probability t/km2/yr) to the fi rst year after the 1977 Marble Cone wildfi re, and these years of combined fi re and fl ood produced the largest-magnitude sedi- Although Lavé and Burbank (2004) did not tenance, and sedimentation rates and patterns ment discharge. test this simple model with simulations, here we in the geologic record. Inventories of sediment

A simple Monte Carlo model, such as the fi nd an excellent fi t for Equation 6 with Sf solved fl ux from active margins (Milliman and Syvitski, one described here, contains several degrees of to be 61 yr by minimizing the root mean square 1992; Syvitski et al., 2005) and the North Ameri- freedom to explore. Here, we investigated the error between predicted and Monte Carlo val- can west coast in particular (Brownlie and Tay- effect of wildfi re recurrence on the sediment ues (gray line, Fig. 16). This suggests that the lor, 1981; Inman and Jenkins, 1999; Willis and yield using multiple 10,000 yr simulations with average wildfi re in the Arroyo Seco will gener- Griggs, 2003; Farnsworth and Warrick, 2008) varying probabilities for wildfi re. The probabil- ate 61 yr of sediment discharge during the fi rst have never directly assessed or purposely evalu- ity for wildfi re was adjusted so that the aver- seven postfi re winter seasons (after 7 yr, the ated the effects of wildfi res. Exceptions include age wildfi re recurrence interval varied between wildfi re effect has completely decayed). We note Lavé and Burbank (2004), who reported debris 20 and 700 yr. Consistent with the conceptual that this value is roughly three times that sug- basin and reservoir-based sediment yields for models of Swanson (1981), wildfi re recurrence gested for the San Gabriel Mountains of south- the tributaries of the San Gabriel Mountains, interval had a fi rst-order and inverse effect on ern California by Lavé and Burbank (2004); the California, and Warrick and Rubin (2007), who the long-term sediment yields (Fig. 16). For the difference may be accounted for by geological, reported that wildfi res signifi cantly infl uenced Arroyo Seco this model predicted that wildfi re vegetation, or hydrologic differences in the set- suspended-sediment and water discharge rates recurrence intervals of ~60 yr would double tings or to the imperfect sediment trapping effi - of the Santa Ana River (4406 km2) of southern sediment yield (Fig. 16). Although this model ciency of the debris basins used in the Lavé and California. Still, little has been done to incorpo- predicted that sediment yield would increase Burbank (2004) study. rate these wildfi re results into regional sediment monotonically with decreasing recurrence in- yield analyses. tervals of wildfi re, we acknowledge that there DISCUSSION Although regional sediment fl ux assessments will be a point where sediment yields could not have not specifi cally addressed wildfi res, there continue to increase because soil erosion would The sediment yield of a watershed will infl u- have been a number of large wildfi res that have exceed soil production. This limitation to sedi- ence downstream fl uvial and coastal landforms coincided with these data collection efforts. For ment yield is shown with dashed lines and shad- and habitats, fl ooding hazards, geochemical cy- example, the USGS data from the Salinas River ing in Figure 16. cling, reservoir sedimentation, debris basin main- (Figs. 12 and 13) clearly show how an upland Lavé and Burbank (2004) suggested that a simple model to assess the long-term effects of wildfi re on sediment yield would have the form: Figure 16. The effect of wildfi re recurrence interval on sedi- ζ Hypothetical limits of soil production ⎛ f ⎞ ment yield of the Arroyo Seco 300 ⎝ Qss ⎠ S R = = f , (6) watershed. Each result was Tf Tf calculated by the percent dif- ference between two 10,000 yr 200 where R is the relative increase in sediment yield Monte Carlo simulations of the ζ (dimensionless), f is the average multiple-year sediment yield of the Arroyo 100 mass sediment fl ux increase from the watershed Seco: one with and one without Increase in Q the effects of wildfi re. The gray caused by a wildfi re (t), ss is the average annual sediment yield (%)

sediment discharge of the watershed (t/yr), Sf is line is derived from Equation 6. 0 the average increase of sediment discharge fol- The dashed lines and shading 10 100 1000 lowing wildfi re expressed in the equivalent time show the hypothetical effect of Wildfire recurrence interval (yr) ζ at a steady Qss to accumulate f (yr), and Tf is the limits to the rate of soil produc- wildfi re recurrence interval (yr). tion on sediment yield.

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wildfi re infl uenced suspended-sediment con- moderated by the amount of rainfall. Water dis- REFERENCES CITED centrations from this 11,000 km2 watershed. charge rates were also found to increase follow- Andrews, E.D., Antweiler, R.C., Neiman, P.J., and Ralph, Previous assessments of the Salinas River have ing wildfi re. Although discharge increases were F.M., 2004, Infl uence of ENSO on fl ood frequency along not included wildfi re as a perturbation to sedi- substantially less than increases in sediment the California coast: Journal of Climate, v. 17, no. 2, ment yield (Inman and Jenkins, 1999; Willis and yield, water discharge rates did have signifi cant p. 337–348, doi:10.1175/1520-0442(2004)017<0337: IOEOFF>2.0.CO;2. Griggs, 2003; Farnsworth and Milliman, 2003; effects on the discharge-related relationships of Brown, J.A.H., 1972, Hydrologic effects of a bushfi re in a Farnsworth and Warrick, 2008), even though suspended-sediment concentrations and yield catchment in south-eastern New South Wales: Journal of the USGS data utilized for these assessments (i.e., the “rating curves”). These results are gen- Hydrology (Amsterdam), v. 15, p. 77–96, doi:10.1016 /0022-1694(72)90077-7. had substantial wildfi re effects for 2 of the 10 yr erally consistent with plot-scale and landscape Brown, W.M., Taylor, B.D., Kolker, O.C., Wells, W.G., and sampled and for 16 of the 106 (15%) suspended- studies (e.g., Inbar et al., 1998; Doerr et al., Palmer, N.R., 1982, Sediment Management for South- ern California Mountains, Coastal Plains and Shore- sediment samples (Fig. 12). 2000; Lavé and Burbank, 2004; Moody et al., line: Part D. Special Inland Studies: California Institute We assume that there are additional rivers like 2005, 2008; Shakesby and Doerr, 2006; Mal- of Technology Environmental Quality Labora tory the Salinas that have had large wildfi res during mon et al., 2007), although they expand upon Technical Report 17-D, 122 p. Brownlie, W.R., and Taylor, B.D., 1981, Sediment Manage- years of suspended-sediment data collection, these results by including detailed measure- ment for Southern California Mountains, Coastal Plains and other rivers that have not. For the rivers ments of postfi re suspended-sediment fl uxes at and Shoreline: Part C. Coastal Sediment Delivery by that have had no wildfi res during suspended- larger spatial scales. Major Rivers in Southern California: California Insti- tute of Technology Environmental Quality Laboratory sediment data collection, the sediment yields Wildfi re followed by heavy precipitation was Technical Report 17-C, 314 p. are likely underestimated by traditional rating shown to produce annual watershed sediment Burned Area Emergency Response (BAER), 2008, Basin Complex Fire/Indians Fire BAER Initial Assessment. curve techniques. For steep, coastal watersheds yields that were an order of magnitude greater Burned-Area Report, Reference FSH 2509.13: Goleta, of California with similar chaparral vegetation, than expected without wildfi re. This combina- California, U.S. Department of Agriculture, U.S. Forest actual yields may be twice those estimated with- tion of fi re and fl ood was shown to occur at re- Service, 19 p. Cannon, S.H., 2001, Debris-fl ow generation from recently out wildfi re (Fig. 16). currence intervals of greater than 1000 yr, and burned watersheds: Environmental & Engineering Geo- Thus, the results presented here suggest that sediment discharge from these infrequent events science, v. 7, p. 321–341. river sediment discharge from wildfi re-prone is likely important to landform evolution, geo- Cerdà, A., 1998, Post-fi re dynamics of erosional processes under Mediterranean climatic conditions: Zeitschrift landscapes such as coastal California should be morphology, and rates and styles of sedimenta- für Geomorphologie, v. 42, no. 3, p. 373–398. carefully reexamined. Future work is needed tion within the geologic record. Cerdà, A., and Lasanta, T., 2005, Long-term erosional re- sponses after fi re in the Central Spanish Pyrenees: to evaluate the sample intervals that contained These results suggest that wildfi re can play an 1. Water and sediment yield: Catena, v. 60, no. 1, p. 59– wildfi res, how these wildfi res infl uenced sedi- important forcing role in sediment yields from 80, doi:10.1016/j.catena.2004.09.006. ment yields, and whether models such as those small watersheds (100–10,000 km2). Unfortu- Cohn, T.A., DeLong, L.L., Gilroy, E.J., Hirsch, R.M., and Wells, D.K., 1989, Estimating constituent loads: Water shown here are more broadly applicable to nately, most assessments of sediment yields of Resources Research, v. 25, p. 937–942, doi:10.1029 other watersheds. Furthermore, lumping all coastal California watersheds have not evalu- /WR025i005p00937. suspended-sediment samples together for the ated the ways in which wildfi res infl uenced the Cole, K.L., and Liu, G.-W., 1994, Holocene paleoecology of an estuary on Santa Rosa Island, CA: Quaternary purpose of “rating curve” calculations of fl uxes reported results (Brownlie and Taylor, 1981; Research, v. 41, p. 326–335, doi:10.1006/qres.1994 may miss important time-dependent patterns— Inman and Jenkins, 1999; Farnsworth and War- .1037. DeBano, L.F., 2000, The role of fi re and soil heating on water from wildfi res or other events—in the sediment rick, 2007). The results of this study suggest repellency in wildland environments: A review: Journal transport processes. that many of these sediment yield assessments of Hydrology (Amsterdam), v. 231–232, p. 195–206, Wildfi re effects on watershed sediment yields should be reexamined. Without including the doi:10.1016/S0022-1694(00)00194-3. DeBano, L.F., and Krammes, J.S., 1966, Water repellent can rival those of human impacts, such as ur- effects of wildfi re, sediment yields from steep, soils and their relation to wildfi re temperatures: Inter- banization (Trimble, 1997; Warrick and Rubin, fire-prone watersheds will be substantially national Association of Hydrological Sciences, v. 11, 2007), land-cover degradation from grazing underestimated. p. 14–19, doi:10.1080/02626666609493457. Doerr, S.H., Shakesby, R.A., and Walsh, R.P.D., 2000, (Cole and Liu, 1994; Pinter and Vestal, 2005), Soil water repellency, its characteristics, causes and and land-cover conversion (Pasternack et al., ACKNOWLEDGMENTS hydro-geomorphological consequences: Earth-Science 2001; Gabet and Dunne, 2002, 2003). Because Reviews, v. 51, p. 33–65, doi:10.1016/S0012-8252 This work was supported through a National Sci- (00)00011-8. humans continue to actively infl uence and Farnsworth, K.L., and Milliman, J.D., 2003, Effects of ence Foundation award number 0628487, “Collab- change fi re frequencies, fi re extent, burn sever- climatic and anthropogenic change on small moun- orative Research: Delivery and Burial of Particulate tainous rivers: The Salinas River example: Global ity, land cover, watershed connectivity, and lo- Organic Carbon (POC) on Ocean Margins Dominated and Planetary Change, v. 39, p. 53–64, doi:10.1016 cal and regional climate (McKenzie et al., 2004; by Small, Mountainous Rivers: The Role of Effective /S0921-8181(03)00017-1. Fried et al., 2004; Syphard et al., 2007), it is im- Discharge,” and the U.S. Geological Survey (USGS) Farnsworth, K.L., and Warrick, J.A., 2008, Sources, Dis- Coastal and Marine Geology Program. We are ex- persal and Fate of Fine-Grained Sediment for Coastal portant for future inventories of sediment yield tremely thankful for the USGS river sampling pro- California: U.S. Geological Survey Scientifi c Investi- from this and similar regions to include compre- grams that sustained river gauges and collected and gations Report SIR 2007–5254, 86 p. Ferguson, R.I., 1987, Accuracy and precision of methods hensive assessments of both natural and human- analyzed suspended-sediment samples. Without these for estimating river loads: Earth Surface Processes induced variations. programs, this paper would not have been possible. and Landforms, v. 12, p. 95–104, doi:10.1002/esp Sampling assistance was provided by Beth Watson, .3290120111. Reyna Maestas, Roxanne Hastings, and Tommaso Fire and Resource Assessment Program (FRAP), 2002, CONCLUSIONS Tesi. Boarding during sampling programs was gen- California’s Forests and Rangelands: 2002 Assess- erously provided by the Elkhorn Slough Foundation. ment, Land Cover Derived from FRAP Multi-Source Here, we provided observations of the sus- Laboratory assistance was provided by Beth Watson, Data (Version 2.2): Sacramento, California, California Sarah Greve, Peter Barnes, Duyen Ho, Yvan Alleau, Department of Forestry and Fire Protection, http://frap pended-sediment concentration and yield of a .cdf.cd.gov (accessed 25 May 2011). and Erik Mulrooney. This manuscript was improved steep coastal California watershed following Florsheim, J.L., Keller, E.A., and Best, D.W., 1991, Flu- by comments and suggestions from Joan Florsheim, vial sediment transport in response to moderate storm two wildfi res. Sediment yield increased after Daniel Malmon, Amy Draut, Kevin Schmidt, and an fl ows following chaparral wildfi re, Ventura County, both fi res, although the scale of this effect was anonymous reviewer. southern California: Geological Society of America

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