Comparison of the USLE, RUSLE1.06c, and RUSLE2 for Application to Highly Disturbed Lands

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1 Comparson of the USLE, RUSLE1.06c, and RUSLE2 for Applcaton to Hghly Dsturbed Lands George R. Foster, Terrence E. Toy, Kenneth G. Renard Abstract RUSLE1.06c and RUSLE2, recently released eroson predcton models, are descrbed. These land-use ndependent models are well suted for applcaton to hghly dsturbed land. Cover-management subfactors make possble the land-use ndependence. Smlartes and dfferences wth the USLE are dscussed. Keywords: sol eroson, eroson predcton, eroson control, conservaton plannng, ranfall, overland flow Introducton The USLE, RUSLE1, and RUSLE2 are wdely used to estmate rll and nterrll eroson that occurs on overland flow areas. These equatons apply where mneral sol s exposed to the erosve forces of randrops and water drops fallng from vegetaton and surface runoff occurrng as Hortonan overland flow. These equatons share features proven n conservaton plannng over four decades. Hghly dsturbed lands nclude constructon stes, hghways, reclamed surface mnes, landflls, mltary tranng stes, and smlar lands where mechancal operatons dsturb the sol and vegetaton to leave the land vulnerable to rll and nterrll eroson. The dsturbance perod s often bref followed by an extended recovery where permanent vegetaton Foster s a retred Agrcultural Engneer, USDA- ARS, Bryan, TX E-mal: gfoster@olbv.com. Toy s a Professor, Department of Geography, Unversty of Denver, Denver, CO Renard s a retred Hydraulc Engneer, USDA-ARS, Southwest Watershed Research Center, Tucson, AZ develops. Cropland s a specal case where a sequence of mechancal operatons s perodcally repeated. Rll and nterrll eroson also occurs on wldlands, pasturelands, rangelands, and other undsturbed lands. These lands do not experence the mechancal dsturbance common to cropland or hghly dsturbed lands. However, nfrequent renovaton to encourage forage producton often nvolves mechancal dsturbance. Extensve removal of vegetaton by lvestock and wld anmal grazng and fre that removes vegetaton and ltter subject these lands to rll and nterrll eroson. The USLE (Unversal Sol Loss Equaton), released n the early 1960s, was developed for cropland (Wschmeer and Smth 1965). Later t was extended to other land uses (Wschmeer and Smth 1978, Dssmeyer and Foster 1980). RUSLE1 (Revsed Unversal Sol Loss Equaton) was released n the early 1990s and evolved to the current RUSLE1.06c released n md 2003 (Renard et al. 1997, USDA- ARS-NSL 2003). RUSLE1 s land-use ndependent and apples to any land use havng exposed mneral sol and Hortonan overland flow. RUSLE2 was also released n md 2003, and t too s land-use ndependent (USDA-ARS-NSL 2003). The USLE s an ndex based, emprcally derved model. RUSLE1 and RUSLE2 are hybrd models that combne ndex and process-based equatons. RUSLE2 expands on the hybrd model structure and uses a dfferent mathematcal ntegraton than does the USLE and RUSLE1. Purpose of USLE, RUSLE1, and RUSLE2 The purpose of the USLE, RUSLE1, and RUSLE2 s to gude conservaton plannng. The equatons are used to estmate eroson based on ste-specfc

2 condtons for eroson control alternatves. The eroson estmates are judged aganst a crteron and those practces that meet the crteron provde satsfactory eroson control for the ste. All three equatons estmate average annual eroson. The usual sol conservaton objectve s to protect the sol from excessve eroson, even when the man objectve s to control sedment leavng the ste. Excessve eroson degrades the landscape, reduces sol productvty, ncreases the dffculty of establshng and mantanng vegetaton, nconvenences mowng, and produces sedment that cause downstream damage. The valdty of a model s judged by how well t serves ts ntended purpose (Toy et al. 2002). Accuracy s mportant, but most mportant s the conservaton plannng decson. Two models that yeld the same conservaton decson perform equally well. Other consderatons are resources requred to use a model, avalablty of nput values, ease of use, and robustness. A model may gve accurate estmates, but f t s dffcult to use, users often sacrfce accuracy for ease of use. Demonstratng that a partcular eroson model s more accurate than another s very dffcult gven the varablty n and lmted extent of the eroson research data, especally for hghly dsturbed and wld lands. Nether the USLE, RUSLE1, or RUSLE2 should be used solely to evaluate overall ste envronmental or ecologcal well-beng. These equatons estmate sol eroson rates, nothng more. The user nterprets the eroson estmates accordng to the user s purpose. Applcaton of these models to wldlands has been crtczed. Sometmes the crtcsm s msdrected to the models rather than to how eroson estmates are used. Eroson rate, even f known wth 100% accuracy, s not the sole ndcator of ecologcal well beng. Basc Equatons Sedment producton Detachment and transport are combned n these models as a sedment producton term. The equaton for sedment producton on a unform slope s: a = r k l s c p (1) where: a = eroson rate (spatal average for the slope length λ) for the th storm, r = storm ranfall erosvty, k = sol erodblty factor, l = slope length factor, s = slope steepness factor, c = covermanagement factor, and p = support practces factor. Storm erosvty r (EI) s the product of the storm s energy and ts maxmum 30-mnute ntensty. Storm energy s closely related to storm amount. The EI varable captures the two most mportant ranstorm characterstcs that determne erosvty, storm amount and a measure of peak ntensty. Sol erodblty k s eroson from the unt plot per unt erosvty. A unt plot s 22.1 m long on a 9 percent steepness, perodcally tlled up and down slope to break the sol crust and to control the weeds, and mantaned n contnuous fallow for several years. Tme s needed for the effects of prevous land use to dsspate and to measure eroson from both moderate and large storms. The unt plot s used to emprcally determne sol erodblty as a functon of nherent sol propertes where the effects of land use have been removed. The product lscp adjusts eroson for the unt-plot condton, whch s the product rk, to eroson for the actual feld condton. Deposton The USLE does not compute deposton. RUSLE1 and RUSLE2 compute deposton on concave slopes, at dense vegetatve strps, n terrace channels, and n sedment basns usng process-based equatons for transport capacty and deposton. The equaton for transport capacty s: ( ) T = k q sn θ (2) c t p where: T c = transport capacty, k t = a transport coeffcent that decreases as hydraulc resstance ncreases from ground cover, vegetatve retardance, and surface roughness, q p = characterstc runoff rate, and θ = slope angle. The product q p sn(θ) s drectly proportonal to runoff s total shear stress rased to the 1.5 power. Shear stress s dvded nto two parts, the part dsspated on ground cover, vegetaton, and surface roughness and the part that erodes and transports sedment. The term k t reduces total shear stress to the shear stress actve n sedment transport. The equaton used to compute deposton s: ( V q )( T g) D = (3) f p c where: D = deposton rate, V f = fall velocty of the sedment, and g = sedment load. A sngle deposton coeffcent s used n RUSLE1 to represent the sedment. Ths coeffcent vares wth sol texture so 155

3 that RUSLE1 computes deposton as a functon of sol texture. The coeffcent s not vared along the slope as deposton enrches the sedment load n fnes. RUSLE2 dvdes the sedment nto fve partcle classes based on sol texture. RUSLE2 treats each partcle class ndvdually wth nteracton among the classes. RUSLE2 computes deposton as a functon of sol texture and how deposton changes sedment characterstcs along the slope, whch s turn affects computed deposton. RUSLE2 computes an enrchment rato for the sedment leavng the end of the slope. Enrchment rato s the rato of specfc surface area of the sedment to specfc surface area of the sol subject to eroson. Integraton of equaton 1 USLE The dscovery that eroson s lnearly proportonal to storm erosvty facltated the development of the well known USLE: A = RKLSCP (4) where: A = average annual eroson, R = erosvty factor, K = sol erodblty factor, LS = topographc factor, C = cover-management factor, and P = support practces factor. Average annual values are used for each factor to compute eroson. Only the C-factor value results from a temporal ntegraton as: ( f c j ) C (5) = where: f j = the temporal dstrbuton of erosvty durng the year and j = an ndex for a crop stage tme step. Expermental eroson data were used to determne cover-management factor (c j ) values by crop stage perod (sol loss ratos, Table 5, AH537, Wschmeer et al. 1978). Crop stage perods mark crop development and events lke prmary tllage, seedbed preparaton, and harvest that change covermanagement condtons. Values for C are ncreased when the most erosve perod concdes wth the perod when cover-management condtons are most vulnerable to eroson. Once computed, C factor values for an erosvty dstrbuton zone are placed n tables for use n equaton 4. Erosvty values for the USLE and RUSLE1 were determned from 22-years of weather data from about 1935 to 1957 for the eastern U.S. Erosvty values were computed for storms equal to and greater than 12.5 mm and were summed for each year. The average annual value for erosvty s the R-value used n equaton 4. Mapped R-values provde an erosvty ndex by locaton. Erosvty vares durng the year. The temporal erosvty dstrbuton, f, was emprcally determned for half-month perods and mapped by zones n the U.S. Expermental data were also used to determne LSfactor values for slope length and steepness and P- factor values for support practces. Sol erodblty K- factor values were obtaned by plottng eroson from a partcular sol n the unt-plot condton versus storm erosvty. The slope of ths lne through the orgn s the sol erodblty K-factor value for that sol. The USDA-Natural Resources Conservaton Servce (NRCS) assgned and cataloged K-factor values for many sols across the U.S. Wth the excepton of the nteracton between erosvty and cover-management, all USLE factors are ndependent of each other. RUSLE1 RUSLE1 uses equatons to compute half-month values for the cover-management factor. All RUSLE1 versons untl the recently released RUSLE1.06c computed half-month values for sol erodblty for the eastern U.S. These RUSLE1 versons compute erosvty-weghted values for K and C usng equaton 5. RUSLE1.06c assumes a constant K-factor value. RUSLE1 consders a lmted nteracton among the factors n equaton 1. The relatonshps for LS and ground cover effect vary wth the rato of rll to nterrll eroson, whch n turn vares wth sol texture, slope steepness, and covermanagement varables. RUSLE2 RUSLE2 computes average annual eroson usng: ( rk kklkck p ) A (6) = S k where: k = ndex for day of the year. The mathematcal ntegraton n RUSLE2 dffers fundamentally from that n the USLE and RUSLE1. Average annual factor values are multpled n the USLE and RUSLE1. Instead, RUSLE2 multples the factor values for each day to estmate daly eroson values, whch are summed for average annual eroson. Ths dfference results n as much as a 20% dfference n average annual eroson values between RUSLE2 and the USLE and RUSLE1. RUSLE2 uses 156

4 basc varables rather than the RKLSCP factors to compute eroson. Although RUSLE2 does not use these factors to compute eroson, t computes values for them and demonstrates ther nteracton. Whch formulaton s best? RUSLE2 s mathematcally superor to the USLE and RUSLE1. Also, RUSLE2 s much more powerful than ether the USLE or RUSLE1 and uses better relatonshps to compute factor values. Use RUSLE1.06 for applcatons where the USLE equaton structure, equaton 4, s desred. Do not use the USLE because the RUSLE1.06c equatons are superor to the USLE equatons. Do not use RUSLE1.06b or older versons of RUSLE1 because RUSLE1.06c was modfed to gve values comparable to RUSLE2 values (USDA-ARS-NSL 2003). Recent Developments Erosvty, precptaton, and temperature Input clmate values for monthly erosvty, precptaton, and temperature were developed from modern clmate data from Ffteen-mnute precptaton data were analyzed to determne erosvty densty values. Erosvty densty s the rato of monthly erosvty to monthly precptaton. Erosvty densty vares spatally and temporally. Erosvty densty s hgher n the southern U.S. than n the northern U.S. Summer erosvty densty s greater than wnter erosvty densty n the eastern U.S. The converse s true along the most western part of the U.S. Erosvty densty does not vary wth elevaton up to about 3,000 m, the extent of the data. Erosvty densty was mapped throughout the contnental U.S. Monthly erosvty densty s multpled by monthly precptaton to obtan monthly erosvty at a locaton. Monthly precptaton and temperature values for any U.S. locaton are avalable n the NRCS PRISM database. The PRISM precptaton and temperature values vary spatally n mountanous areas. The new erosvty values are much better than prevous values. RUSLE2 uses 10 yr-24 hr precptaton amounts to compute runoff. A new map of 10 yr EI values for the eastern U.S. was developed for use n RUSLE1.06c. Sol erodblty The NRCS assgned K-factor values cannot be used for mxed sols typcal of hghly dsturbed lands. The RUSLE2 modfed sol erodblty nomograph s used to estmate K-factor values for mxed sols and subsols where the surface layer has been strpped away wthout mxng the sols. The effect of the sol structure n the standard nomograph (Wschmeer et al. 1978) s nconsstent wth accepted scence regardng the relatonshp between eroson, texture, and structure. Topography The S factor n RUSLE1 and RUSLE2 s based on a much larger data set than the S factor n the USLE. The RUSLE relatonshp better fts data from hghly dsturbed lands than does the USLE relatonshp. The exponent n n the slope length L factor (λ/22.1) n n RUSLE1.06c vares wth land use and sol texture. Ths exponent n RUSLE2 s computed wth equatons that are functons of slope steepness, sol bomass, sol consoldaton, ground cover, and sol texture. Cover-management Cover-management represents how cultural management practces that nvolve mulch, vegetaton, and sol condton affect eroson. Subfactor method Both RUSLE1.06c and RUSLE2 use subfactors to compute temporal cover-management factor values. Eroson occurs when erosve agents exert physcal forces on the sol that exceed nternal resstng forces that hold the sol partcles n place (Toy et al. 2002). Vegetatve cover above the sol surface; ltter, stones, and other materal on the sol surface; and surface roughness reduce erosve forces. Physcal, chemcal, and bologcal propertes modfed by land use and land use condton affect sol resstance to eroson. The subfactors capture how major varables affect these external and nternal forces. A strength of RUSLE1 and RUSLE2 s that they are land-use ndependent, made possble by the subfactor method. Both models treat land use and land use condton as a contnuum. A freshly graded and seeded surface mne reclamaton ste s lke a recently tlled and seeded cropped feld. Over tme, the ste evolves to a pasture, range, or wld land lke condton. Land use n western South Dakota alternates between crop-land and rangeland as 157

5 farmng economcs shft. Prevous land use affects eroson wth the current land use. A part of a mltary tranng ground s undsturbed lke rangeland at Fort Hood, Texas or forestland at Fort Bennng, Georga. Another part of the grounds s hghly dsturbed lke a constructon ste wth a very rough sol. All sorts of condtons exst between these extremes. An eroson predcton model derved from cropland data and another derved from rangeland data are unlkely to gve common estmates at the boundary between land use condtons. Land users may not know the correct eroson estmate, but they recognze and queston nconsstent eroson estmates. Both RUSLE1.06c and RUSLE2 provde the expected consstency. The subfactor method was orgnally developed to extend the USLE to undsturbed land (Wschmeer 1975). The USLE subfactor method consdered how cover-management condtons above the sol surface, on the sol surface, and wthn the sol surface affected eroson. Values for ths procedure are gven n Table 10, AH537 (Wschmeer and Smth 1978). These values gve poor results and should not be used. Table 10, AH537 does not consder surface roughness, does not represent properly sol bomass as a functon of vegetaton type or producton level, and does not represent properly the combnaton of rock, ltter, and other ground cover. Also, Table 10 cannot be used for mechancally dsturbed land. The subfactor varables used n both RUSLE1.06c and RUSLE2 nclude percent canopy cover and fall heght; surface roughness; ground cover provded by stones, ltter, basal area, lve vegetaton touchng the ground, and other materal on the sol surface; plant communty type; average annual plant producton; and tme snce the sol has been mechancally dsturbed. Plant communty type determnes the rato of effectve root bomass to average annual above ground plant producton. The overlap of canopy over ground cover and the overlap of ltter over stones are taken nto account. The subfactor equatons n RUSLE2 are more detaled than those n RUSLE1.06c. For example, the relatonshps n RUSLE2 consder the dstrbuton of roots wth depth and where sol-dsturbng operatons dstrbute materal wthn the dsturbance depth. The tme nvarant C factor method n RUSLE1 uses effectve average annual nput values to compute a C- factor value. RUSLE2 and the tme varant C-factor method n RUSLE1 computes the accumulaton of a ltter layer on the sol surface and the accumulaton of sol bomass. Sources of sol bomass nclude lve and 158 sloughed dead roots, plant materal moved nto the sol by nsects, and materal mechancally ncorporated nto the sol. These bomass pools are a functon of precptaton and temperature at a locaton, plant producton level, ltter fall, root sloughng, decomposton characterstcs of the bomass, and bural characterstcs of mechancal operatons. Sol loss rato values n Table 5, AH 537 (Wschmeer and Smth 1978) and lterature values for conservaton tllage were used to partally calbrate the subfactor equatons. Lterature values for the effect of rangeland condtons on eroson, ncludng data collected by the USDA-Agrcultural Research Servce (ARS) n the Walnut Gulch watershed, Nevada Test Ste, and other locatons were also used. The WEPP rangeland data were used to develop values for the rato of effectve root bomass to annual plant producton. Experments were conducted at more than 10 locatons across the western U.S. Analyss of the ARS-NRCS Range Study Team data was attempted wth lmted success. The procedure was to back calculate the effectve below ground bomass values usng measured eroson and measured values for other varables n the subfactor equatons. Measured root bomass values do not work well for estmatng effectve below ground bomass. Collectng and accurately measurng root bomass s very dffcult, not all roots are equally effectveness n reducng eroson, and research has not determned the relaton of eroson to root characterstcs. Also, the presence of organc compounds from decomposton of sloughed (dead) roots and ltter brought nto the sol by nsects s not represented by measured root bomass. C factor values for constructon stes Values for the C and P factors are avalable n varous techncal publcatons for applyng the USLE to constructon stes. These values are qute nconsstent, whch means that some of them are erroneous and should not be used. RUSLE1.06c represents the current state of scentfc knowledge and research data (Toy and Foster 1998). Comparable relatonshps are used n RUSLE2. A project s underway wth the Wsconsn Department of Natural Resources to further refne RUSLE2 for applcaton to constructon stes. Support Practces

6 Support practces nclude contourng (rdgng), barrers (vegetatve strps, slt fences), flow nterceptors (dversons), sedment basns, and subsurface dranage. These practces affect eroson by affectng runoff. The 10 yr EI n RUSLE1 and 10 yr-24 hr precptaton n RUSLE2 are used to compute runoff usng the NRCS curve number method. The curve number s related to a covermanagement condton ndex n RUSLE1 and s computed n RUSLE2 wth equatons that are functons of ground cover, sol bomass, surface roughness, and sol consoldaton. The effectveness of contourng s computed as a functon of runoff and slope steepness. Crtcal slope length, the locaton where contourng fals, s computed as a functon of the shear stress appled to the sol. Both RUSLE1.06c and RUSLE2 use runoff n process-based equatons to compute deposton caused by concave slopes, barrers, and low-grade channels usng equatons 2 and 3. Deposton depends on the characterstcs of the sedment reachng the support practce. Less deposton occurs f the sedment s fne. For example, less deposton occurs n a terrace channel or a sedment basn f a dense grass strp mmedately upslope of the channel or basn deposts sedment that enrches the sedment load n fnes. RUSLE2 computes ths effect of upslope deposton, but RUSLE1.06c does not. Computer Programs The RUSLE2 computer program ncludes an exceptonal graphcal user nterface. The user can customze the nterface to ther preferences by choosng screen arrangement, unts, sgnfcant dgts, and the complexty of the nputs and outputs. The program s computatonal engne maxmzes the power of the RUSLE2 hybrd model structure. The RUSLE1.06c program mantans the smple USLE ndex structure. However, accommodatng nteractons among the factors s nconvenent n ths structure. The same nformaton must be entered at multple places n the RUSLE1 program. RUSLE2 represents detaled nteractons wth smple data entry. RUSLE1 s lmted n the complexty of feld stuatons that t can represent. RUSLE2 can analyze very complex hllslope shapes and spatal arrangements of sol, cover-management, and support practces on the slope. Nether RUSLE1.06c nor RUSLE2 s a smulaton model. The user descrbes the feld condton usng RUSLE program features. The models use ths descrpton to compute eroson. Both models must be told almost everythng, ncludng when frost klls vegetaton. Ths approach, whle seemngly crude and awkward, mproves accuracy, power, and flexblty. Concluson RUSLE2 s modern powerful, easy-to-use eroson predcton technology. USLE and RUSLE1 users, and perhaps users of other models, should shft to RUSLE2 for estmatng rll and nterrll eroson rates needed for conservaton plannng on all land uses. Readly avalable databases facltate the adopton of RUSLE2. RUSLE1.06c s recommended for those users who wsh to contnue to use the USLE structure. The equatons n RUSLE1.06c are much better than those n the USLE and prevous RUSLE1 versons. Acknowledgments RUSLE2 was developed jontly by the USDA- Agrcultural Research Servce (ARS), the USDA- Natural Resources Conservaton Servce (NRCS), and the Unversty of Tennessee. The Illnos State Water Survey, NRCS, ARS, and Unversty of Tennessee analyzed the weather data to obtan new erosvty values. Addtonal nformaton on RUSLE1.06c and RUSLE2 can be obtaned from USDA-ARS-NSL (2003). References Dssmeyer, G.E., and G.R. Foster A gude for predctng sheet and rll eroson on forestland. U.S. Department of Agrculture, Forest Servce, Techncal Publcaton SA-TP-11. Renard, K.G., G.R. Foster, G.A. Weeses, D.K. McCool, and D.C. Yoder Predctng sol eroson by water. U.S. Department of Agrculture, Agrcultural Research Servce, Agrculture Handbook 703. Toy, T.E., and G.R. Foster Use of the Revsed Unversal Sol Loss Equaton (RUSLE1) on mned lands, constructon stes, and reclamed lands. U.S. Department of Interor, Offce of Surface Mnng, Reclamaton, and Regulaton. 159

7 Toy, T.E., G.R. Foster, and K.G. Renard Sol Eroson. John Wley & Sons, New York. U.S. Department of Agrculture, Agrcultural Research Servce, Natonal Sedment Laboratory (USDA-ARS-NSL) RUSLE1.06c and RUSLE2. Wschmeer, W.H Estmatng the sol loss equaton s cover and management factor for undsturbed lands. In Present and prospectve technology for predctng sedment yelds and sources, pp U.S. Department of Agrculture, Agrcultural Research Servce, ARS-S- 40. Wschmeer, W.H., and D.D. Smth Predctng ranfall-eroson losses from cropland east of the Rocky Mountans. U.S. Department of Agrculture, Agrcultural Research Servce, Agrculture Handbook 282. Wschmeer, W.H., and D.D. Smth Predctng ranfall eroson losses. U.S. Department of Agrculture, Agrcultural Research Servce, Agrculture Handbook

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