1. 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 cultivation up and down the slope The model works mathematically in 2 steps A 1 = R K UNIT PLOT is the primary physical model A = A 1 L S C P Factors are not independent in RUSLE and RUSLE2 L = (slope length / 22.1 ) m where m varies with rill to interill ratio which varies with soil properties and slope gradient C varies with climate through interaction between temporal variations in erosivity and crop growth RUSLE2 Daily Erodibility Storm EI 30, Q R and Erodibility Predicted storm soil loss by RUSLE2 and USLE-M 1/3 EGU2014

2. Runoff as a factor in USLE/RUSLE Technology P.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 variable Consequently, 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 RUSLE2 K j / K n = 0.591 + 0.732 (P j /P s ) – 0.324 (T j /T s ) T j > 30 o F K n = nomograph K, j = month, T s = average summer temp, P s = average summer monthly rain Base climate = Columbia, Missouri RUSLE2 Daily Erodibility Storm EI 30, Q R and Erodibility Predicted storm soil loss by RUSLE2 and USLE-M 2/3

3. Runoff as a factor in USLE/RUSLE Technology P.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 K d ), wet (giving K w ), very wet (giving K vw ) K = (13 K d + 4 K w +3 K vw ) /20 (Dabney et al, 2004) Tillage treatment K d K w K vw Conventional Till0.330.580.76 No Till0.370.840.89 K values in customary US units Weighting for climate in central USA. RUSLE2 Daily Erodibility Storm EI 30, Q R and Erodibility Predicted storm soil loss by RUSLE2 and USLE-M 3/4

4. Runoff as a factor in USLE/RUSLE Technology P.I.A. Kinnell, Institute for Applied Ecology, University of Canberra RUSLE2 can predict soil losses for a set of representative storms USLE-M includes runoff as a factor in the event erosivity index A 1 = Q R EI 30 K UM Q R = runoff ratio K UM = soil erodibility associated with Q R EI 30 index A 1 = Q R EI 30 K UM = EI 30 [Q R K UM ] [Q R K UM ] = a runoff dependent erodibility factor associated with EI 30 and can be compared with RUSLE2 Ks when applied to individual events RUSLE2 Daily Erodibility Storm EI 30, Q R and Erodibility Predicted storm soil loss by RUSLE2 and USLE-M 3/3 To 1

5. Runoff as a factor in USLE/RUSLE Technology P.I.A. Kinnell, Institute for Applied Ecology, University of Canberra Daily temperature Daily soil erodibility  Presque Isle, ME Bethnay, MO Macon, GA Tampa, FL North South Frozen ground in Winter

6. Runoff as a factor in USLE/RUSLE Technology P.I.A. Kinnell, Institute for Applied Ecology, University of Canberra EI 30 and Q R for storm sequenceErodibilities associated with EI 30 

7. Runoff as a factor in USLE/RUSLE Technology P.I.A. Kinnell, Institute for Applied Ecology, University of Canberra Erodibilities associated with EI 30 Predicted event soil loss The product of Q R and K UM produces similar results to RUSLE2 Ks when applied RUSLE2 storms 

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