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The USLE/RUSLE Model:

Runoff as a factor in USLE/RUSLE Technology P.I.A. Kinnell, Institute for Applied Ecology, University of Canberra. The USLE/RUSLE Model: A = R K L S C P R and K have units, L = S = C = P = 1 on UNIT PLOT UNIT PLOT = 22.1 m long bare fallow on 9% slope

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The USLE/RUSLE Model:

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  1. Runoff as a factor in USLE/RUSLE TechnologyP.I.A. Kinnell, Institute for Applied Ecology, University of Canberra • The USLE/RUSLE Model: A = R K L S C P R and K have units, L = S = C = P = 1 on UNIT PLOTUNIT PLOT = 22.1 m long bare fallow on 9% slope cultivation up and down the slope • The model works mathematically in 2 steps A1 = R K UNIT PLOT is the primary physical model A = A1 L S C P • Factors are not independent in RUSLE and RUSLE2L = (slope length / 22.1 )m where m varies with rill to interill ratio which varies with soil properties and slope gradientC varies with climate through interaction between temporal variations in erosivity and crop growth 1/3 RUSLE2 Daily Erodibility Storm EI30, QR and Erodibility Predicted storm soil loss by RUSLE2 and USLE-M

  2. Runoff as a factor in USLE/RUSLE TechnologyP.I.A. Kinnell, Institute for Applied Ecology, University of Canberra • Soil loss depends on runoff but the R factor is based on event erosivity factor that does not include runoff as an independent variableConsequently, K, the soil loss per unit of R, for a soil with given physical properties will be greater for wet climates than for dry climates. • In RUSLE2Kj / Kn = 0.591 + 0.732 (Pj/Ps) – 0.324 (Tj/Ts) Tj > 30oF Kn = nomograph K, j = month, Ts = average summer temp, Ps = average summer monthly rain • Base climate = Columbia, Missouri 2/3 RUSLE2 Daily Erodibility Storm EI30, QR and Erodibility Predicted storm soil loss by RUSLE2 and USLE-M

  3. Runoff as a factor in USLE/RUSLE TechnologyP.I.A. Kinnell, Institute for Applied Ecology, University of Canberra • Nomograph was developed from rainfall simulating experiments on 10.6 m long plots using a sequence of runs – dry (giving Kd), wet (giving Kw), very wet (giving Kvw) • K = (13 Kd + 4 Kw +3 Kvw) /20 (Dabney et al, 2004) Tillage treatmentKdKwKvw Conventional Till 0.33 0.58 0.76 No Till 0.37 0.84 0.89 K values in customary US unitsWeighting for climate in central USA. 3/4 RUSLE2 Daily Erodibility Storm EI30, QR and Erodibility Predicted storm soil loss by RUSLE2 and USLE-M

  4. Runoff as a factor in USLE/RUSLE TechnologyP.I.A. Kinnell, Institute for Applied Ecology, University of Canberra • RUSLE2 can predict soil losses for a set of representative storms • USLE-Mincludes runoff as a factor in the event erosivity indexA1 = QR EI30 KUM QR = runoff ratio KUM = soil erodibility associated with QR EI30 index • A1 = QR EI30 KUM = EI30 [QR KUM ] • [QR KUM ] = a runoff dependent erodibility factor associated with EI30and can be compared with RUSLE2 Ks when applied to individual events 3/3 To 1 RUSLE2 Daily Erodibility Storm EI30, QR and Erodibility Predicted storm soil loss by RUSLE2 and USLE-M

  5. Runoff as a factor in USLE/RUSLE TechnologyP.I.A. Kinnell, Institute for Applied Ecology, University of Canberra  Daily soil erodibility Daily temperature Frozenground in Winter Presque Isle, MEBethnay, MOMacon, GA Tampa, FL NorthSouth

  6. Runoff as a factor in USLE/RUSLE TechnologyP.I.A. Kinnell, Institute for Applied Ecology, University of Canberra  EI30 and QR for storm sequence Erodibilities associated with EI30

  7. Runoff as a factor in USLE/RUSLE TechnologyP.I.A. Kinnell, Institute for Applied Ecology, University of Canberra  Erodibilities associated with EI30 Predicted event soil loss The product of QR and KUM produces similar results to RUSLE2 Ks when applied RUSLE2 storms

  8. Runoff as a factor in USLE/RUSLE TechnologyP.I.A. Kinnell, Institute for Applied Ecology, University of Canberra

  9. Runoff as a factor in USLE/RUSLE TechnologyP.I.A. Kinnell, Institute for Applied Ecology, University of Canberra

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