Enhancing RUSLE to include runoff-driven phenomena

RUSLE2 (Revised Universal Soil Loss Equation) is the most recent in the family of Universal Soil Loss Equation (USLE)/RUSLE/RUSLE2 models proven to provide robust estimates of average annual sheet and rill erosion from a wide range of land use, soil, and climatic conditions. RUSLE2's capabiliti...

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Published inHydrological processes Vol. 25; no. 9; pp. 1373 - 1390
Main Authors Dabney, Seth M, Yoder, Daniel C, Vieira, Dalmo A.N, Bingner, Ronald L
Format Journal Article
LanguageEnglish
Published Chichester, UK John Wiley & Sons, Ltd 30.04.2011
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Abstract RUSLE2 (Revised Universal Soil Loss Equation) is the most recent in the family of Universal Soil Loss Equation (USLE)/RUSLE/RUSLE2 models proven to provide robust estimates of average annual sheet and rill erosion from a wide range of land use, soil, and climatic conditions. RUSLE2's capabilities have been expanded over earlier versions using methods of estimating time-varying runoff and process-based sediment transport routines so that it can estimate sediment transport/deposition/delivery on complex hillslopes. In this report we propose and evaluate a method of predicting a series of representative runoff events whose sizes, durations, and timings are estimated from information already in the RUSLE2 database. The methods were derived from analysis of 30-year simulations using a widely accepted climate generator and runoff model and were validated against additional independent simulations not used in developing the index events, as well as against long-term measured monthly rainfall/runoff sets. Comparison of measured and RUSLE2-predicted monthly runoff suggested that the procedures outlined may underestimate plot-scale runoff during periods of the year with greater than average rainfall intensity, and a modification to improve predictions was developed. In order to illustrate the potential of coupling RUSLE2 with a process-based channel erosion model, the resulting set of representative storms was used as an input to the channel routines used in Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS) to calculate ephemeral gully erosion. The method was applied to a hypothetical 5-ha field cropped to cotton in Marshall County, MS, bisected by a potential ephemeral gully having channel slopes ranging from 0·5 to 5% and with hillslopes on both sides of the channel with 5% steepness and 22·1 m length. Results showed the representative storm sequence produced reasonable results in CREAMS indicating that ephemeral gully erosion may be of the same order of magnitude as sheet and rill erosion. Copyright © 2010 John Wiley & Sons, Ltd.
AbstractList RUSLE2 (Revised Universal Soil Loss Equation) is the most recent in the family of Universal Soil Loss Equation (USLE)/RUSLE/RUSLE2 models proven to provide robust estimates of average annual sheet and rill erosion from a wide range of land use, soil, and climatic conditions. RUSLE2's capabilities have been expanded over earlier versions using methods of estimating time-varying runoff and process-based sediment transport routines so that it can estimate sediment transport/deposition/delivery on complex hillslopes. In this report we propose and evaluate a method of predicting a series of representative runoff events whose sizes, durations, and timings are estimated from information already in the RUSLE2 database. The methods were derived from analysis of 30-year simulations using a widely accepted climate generator and runoff model and were validated against additional independent simulations not used in developing the index events, as well as against long-term measured monthly rainfall/runoff sets. Comparison of measured and RUSLE2-predicted monthly runoff suggested that the procedures outlined may underestimate plot-scale runoff during periods of the year with greater than average rainfall intensity, and a modification to improve predictions was developed. In order to illustrate the potential of coupling RUSLE2 with a process-based channel erosion model, the resulting set of representative storms was used as an input to the channel routines used in Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS) to calculate ephemeral gully erosion. The method was applied to a hypothetical 5-ha field cropped to cotton in Marshall County, MS, bisected by a potential ephemeral gully having channel slopes ranging from 0·5 to 5% and with hillslopes on both sides of the channel with 5% steepness and 22·1 m length. Results showed the representative storm sequence produced reasonable results in CREAMS indicating that ephemeral gully erosion may be of the same order of magnitude as sheet and rill erosion. Copyright © 2010 John Wiley & Sons, Ltd.
RUSLE2 (Revised Universal Soil Loss Equation) is the most recent in the family of Universal Soil Loss Equation (USLE)/RUSLE/RUSLE2 models proven to provide robust estimates of average annual sheet and rill erosion from a wide range of land use, soil, and climatic conditions. RUSLE2's capabilities have been expanded over earlier versions using methods of estimating time-varying runoff and process-based sediment transport routines so that it can estimate sediment transport/deposition/delivery on complex hillslopes. In this report we propose and evaluate a method of predicting a series of representative runoff events whose sizes, durations, and timings are estimated from information already in the RUSLE2 database. The methods were derived from analysis of 30-year simulations using a widely accepted climate generator and runoff model and were validated against additional independent simulations not used in developing the index events, as well as against long-term measured monthly rainfall/runoff sets. Comparison of measured and RUSLE2-predicted monthly runoff suggested that the procedures outlined may underestimate plot-scale runoff during periods of the year with greater than average rainfall intensity, and a modification to improve predictions was developed. In order to illustrate the potential of coupling RUSLE2 with a process-based channel erosion model, the resulting set of representative storms was used as an input to the channel routines used in Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS) to calculate ephemeral gully erosion. The method was applied to a hypothetical 5-ha field cropped to cotton in Marshall County, MS, bisected by a potential ephemeral gully having channel slopes ranging from 0?5 to 5% and with hillslopes on both sides of the channel with 5% steepness and 22?1 m length. Results showed the representative storm sequence produced reasonable results in CREAMS indicating that ephemeral gully erosion may be of the same order of magnitude as sheet and rill erosion.
RUSLE2 (Revised Universal Soil Loss Equation) is the most recent in the family of Universal Soil Loss Equation (USLE)/RUSLE/RUSLE2 models proven to provide robust estimates of average annual sheet and rill erosion from a wide range of land use, soil, and climatic conditions. RUSLE2's capabilities have been expanded over earlier versions using methods of estimating time-varying runoff and process-based sediment transport routines so that it can estimate sediment transport/deposition/delivery on complex hillslopes. In this report we propose and evaluate a method of predicting a series of representative runoff events whose sizes, durations, and timings are estimated from information already in the RUSLE2 database. The methods were derived from analysis of 30-year simulations using a widely accepted climate generator and runoff model and were validated against additional independent simulations not used in developing the index events, as well as against long-term measured monthly rainfall/runoff sets. Comparison of measured and RUSLE2-predicted monthly runoff suggested that the procedures outlined may underestimate plot-scale runoff during periods of the year with greater than average rainfall intensity, and a modification to improve predictions was developed. In order to illustrate the potential of coupling RUSLE2 with a process-based channel erosion model, the resulting set of representative storms was used as an input to the channel routines used in Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS) to calculate ephemeral gully erosion. The method was applied to a hypothetical 5-ha field cropped to cotton in Marshall County, MS, bisected by a potential ephemeral gully having channel slopes ranging from 0·5 to 5% and with hillslopes on both sides of the channel with 5% steepness and 22·1 m length. Results showed the representative storm sequence produced reasonable results in CREAMS indicating that ephemeral gully erosion may be of the same order of magnitude as sheet and rill erosion.
Author Dabney, Seth M.
Vieira, Dalmo A. N.
Yoder, Daniel C.
Bingner, Ronald L.
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Cites_doi 10.1175/1520-0450(1996)035<1878:SWSOAA>2.0.CO;2
10.13031/2013.23153
10.1016/S0341-8162(02)00143-1
10.1175/1520-0477(2002)083<0954:TGEWGT>2.3.CO;2
10.2136/sssaj2007.0434
10.13031/2013.23957
10.1111/j.1752-1688.2005.tb03742.x
10.1029/96WR02104
10.1029/91WR02381
10.1061/(ASCE)0733-9429(1991)117:6(725)
10.1002/hyp.1177
10.13031/2013.23150
10.2489/jswc.63.6.496
10.1002/hyp.6668
10.13031/2013.9952
10.1061/(ASCE)1084-0699(1997)2:3(145)
10.1061/(ASCE)1084-0699(2006)11:6(631)
10.2136/sssaj1998.03615995006200060026x
10.13031/2013.21343
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References Harmel RD, Johnson G, Richardson CW. 2002. The GEM experience: weather generator technology development in the USDA. Bulletin of the American Meteorological Society 83: 954-957.
Poesen J, Nachtergaele J, Verstraeten G, Valentin C. 2003. Gully erosion and environmental change: importance and research needs. Catena 50: 91-133.
Smith RE. 1997. Discussion: runoff curve number: has it reached maturity? Journal of Hydrologic Engineering 2(3): 145-147.
USDA-SCS. 1992. Ephemeral Gully Erosion Model (EGEM). Version 2.0, User Manual. U.S. Department of Agriculture, Soil Conservation Service: Washington, DC; 106.
Foster GR. 2005. Modeling ephemeral gully erosion for conservation planning. International Journal of Sediment Research 20(3): 157-175.
Yalin MS. 1963. An expression for bed-load transportation. Proceedings of American Society of Civil Engineering 89(HY3): 221-250.
Hjelmfelt AT. 1991. Investigation of curve number procedure. Journal of Hydraulic Engineering 117(6): 725-737.
Haan CT. 1977. Statistical Methods in Hydrology, Iowa State University Press: Ames, IA; 378 pp.
Johnson GL, Hanson CL, Hardegree SP, Ballard EB. 1996. Stochastic weather simulation: overview and analysis of two commonly used models. Journal of Applied Methods 35: 1878-1896.
Gordon LM, Bennett SJ, Bingner RL, Theurer FD, Alonso CV. 2007. Simulating ephemeral gully erosion in AnnAGNPS. Transactions of the ASABE 50(3): 857-866.
Garen DC, Moore DS. 2005. Curve number hydrology in water quality modelling: uses abuses and future directions. Journal of the American Water Resources Association 41: 377-388.
Haan CT, Barfield BJ, Hayes JC. 1994. Design Hydrology and Sedimentology for Small Catchments. Academic Press: San Diego, CA.
Jain MK, Mishra SK, Suresh Babu P, Venugopal K, Singh VP. 2006. Enhanced runoff curve umber model incorporating storm duration and a nonlinear Ia-S relation. Journal of Hydrologic Engineering 11(6): 631-635.
Kinnell PIA, Risse LM. 1998. USLE-M: Empirical modeling rainfall erosion through runoff and sediment concentration. Soil Science Society of America Journal 62: 1667-1672.
Yu B. 2002. Using CLIGEN to generate RUSLE climate inputs. Transactions of the ASAE 45: 311-320.
Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL. 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE 50: 885-900.
Dabney SM, McGregor KC, Wilson GV, Cullum RF. 2009. How management of grass hedges affects their erosion reduction potential. Soil Science Society of America Journal 73(1): 241-254.
Kuhnle RA, Bingner RL, Foster GR, Grissinger EH. 1995. Effect of land use changes on sediment transport in Goodwin Creek. Water Resources Research 32(10): 3189-3196.
ASCE. 2009. Curve number hydrology, state of the practice. Hawkins RH, Ward TJ, Woodward DE, Van Mullem JA (eds). American Society of Civil Engineers: Reston, VA; 106 pp.
Hairsine PB, Rose CW. 1992. Modeling water erosion due to overland flow using physical principles: 2. Rill flow. Water Resources Research 28: 245-250.
Kuhnle RA, Bingner RL, Alonso CV, Wilson CG, Simon A. 2008. Conservation practice effects on sediment load in the Goodwin Creek Experimental Watershed. Journal of Soil and Water Conservation 63(6): 496-503.
Meyer CR, Renschler CS, Vining RC. 2008. Implementing quality control on a random number stream to improve a stochastic weather generator. Hydrological Processes 22: 1069-1079.
Renschler CS. 2003. Designing geo-spatial interfaces to scale process models: the GeoWEPP approach. Hydrological Processes 17: 1005-1017.
Ascough JC, Baffaut C, Nearing MA, Liu BY. 1997. The WEPP watershed model: I. Hydrology and erosion. Transactions of the American Society of Agricultural Engineers 40(4): 921-933.
SAS Institute. 1996. SAS/STAT Software: Changes and enhancements through release 6.11. SAS Inst., Cary, N.C.
Yoder DC, Tyner JS, Balousek JD, Panuska JC, Buchanan JR, Kirsch, and KJ, Lyon JP. 2007. Conservation planning for construction sites. Transactions of the ASABE 50(5): 1613-1618.
1997; 40
1963; 89
2010
2006; 11
1980a
1980b
1995; 32
2009
2005; 41
1997
2008
2005; 20
1996
2006
1994
2003; 17
2007; 50
1997; 2
2004
2003
1992
1991; 117
1996; 35
1998; 62
2003; 50
1978
1977
2009; 73
2001
2002; 83
2002; 45
1992; 28
1965
1982
2008; 22
2008; 63
Haan CT (e_1_2_14_12_1) 1977
Haan CT (e_1_2_14_13_1) 1994
SAS Institute (e_1_2_14_29_1) 1996
e_1_2_14_11_1
e_1_2_14_34_1
e_1_2_14_10_1
e_1_2_14_35_1
e_1_2_14_32_1
Smith RE (e_1_2_14_30_1) 1997; 2
e_1_2_14_33_1
e_1_2_14_15_1
e_1_2_14_38_1
e_1_2_14_14_1
e_1_2_14_17_1
Hawkins RH (e_1_2_14_16_1) 1982
e_1_2_14_37_1
Foster GR (e_1_2_14_6_1) 2005; 20
Foster GR (e_1_2_14_8_1) 1980
e_1_2_14_5_1
Yu B (e_1_2_14_41_1) 2002; 45
ASCE (e_1_2_14_2_1) 2009
e_1_2_14_20_1
USDA‐SCS (e_1_2_14_36_1) 1992
e_1_2_14_4_1
e_1_2_14_3_1
e_1_2_14_40_1
Foster GR (e_1_2_14_7_1) 1980
e_1_2_14_23_1
e_1_2_14_24_1
e_1_2_14_21_1
e_1_2_14_22_1
e_1_2_14_27_1
e_1_2_14_28_1
e_1_2_14_25_1
Yalin MS (e_1_2_14_39_1) 1963; 89
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Street L (e_1_2_14_31_1) 2001
Foster GR (e_1_2_14_9_1) 2003
References_xml – reference: SAS Institute. 1996. SAS/STAT Software: Changes and enhancements through release 6.11. SAS Inst., Cary, N.C.
– reference: Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL. 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE 50: 885-900.
– reference: Yoder DC, Tyner JS, Balousek JD, Panuska JC, Buchanan JR, Kirsch, and KJ, Lyon JP. 2007. Conservation planning for construction sites. Transactions of the ASABE 50(5): 1613-1618.
– reference: Harmel RD, Johnson G, Richardson CW. 2002. The GEM experience: weather generator technology development in the USDA. Bulletin of the American Meteorological Society 83: 954-957.
– reference: Smith RE. 1997. Discussion: runoff curve number: has it reached maturity? Journal of Hydrologic Engineering 2(3): 145-147.
– reference: Haan CT. 1977. Statistical Methods in Hydrology, Iowa State University Press: Ames, IA; 378 pp.
– reference: Yu B. 2002. Using CLIGEN to generate RUSLE climate inputs. Transactions of the ASAE 45: 311-320.
– reference: Meyer CR, Renschler CS, Vining RC. 2008. Implementing quality control on a random number stream to improve a stochastic weather generator. Hydrological Processes 22: 1069-1079.
– reference: Johnson GL, Hanson CL, Hardegree SP, Ballard EB. 1996. Stochastic weather simulation: overview and analysis of two commonly used models. Journal of Applied Methods 35: 1878-1896.
– reference: USDA-SCS. 1992. Ephemeral Gully Erosion Model (EGEM). Version 2.0, User Manual. U.S. Department of Agriculture, Soil Conservation Service: Washington, DC; 106.
– reference: Haan CT, Barfield BJ, Hayes JC. 1994. Design Hydrology and Sedimentology for Small Catchments. Academic Press: San Diego, CA.
– reference: Ascough JC, Baffaut C, Nearing MA, Liu BY. 1997. The WEPP watershed model: I. Hydrology and erosion. Transactions of the American Society of Agricultural Engineers 40(4): 921-933.
– reference: Kinnell PIA, Risse LM. 1998. USLE-M: Empirical modeling rainfall erosion through runoff and sediment concentration. Soil Science Society of America Journal 62: 1667-1672.
– reference: Yalin MS. 1963. An expression for bed-load transportation. Proceedings of American Society of Civil Engineering 89(HY3): 221-250.
– reference: Hjelmfelt AT. 1991. Investigation of curve number procedure. Journal of Hydraulic Engineering 117(6): 725-737.
– reference: Foster GR. 2005. Modeling ephemeral gully erosion for conservation planning. International Journal of Sediment Research 20(3): 157-175.
– reference: Kuhnle RA, Bingner RL, Alonso CV, Wilson CG, Simon A. 2008. Conservation practice effects on sediment load in the Goodwin Creek Experimental Watershed. Journal of Soil and Water Conservation 63(6): 496-503.
– reference: ASCE. 2009. Curve number hydrology, state of the practice. Hawkins RH, Ward TJ, Woodward DE, Van Mullem JA (eds). American Society of Civil Engineers: Reston, VA; 106 pp.
– reference: Jain MK, Mishra SK, Suresh Babu P, Venugopal K, Singh VP. 2006. Enhanced runoff curve umber model incorporating storm duration and a nonlinear Ia-S relation. Journal of Hydrologic Engineering 11(6): 631-635.
– reference: Poesen J, Nachtergaele J, Verstraeten G, Valentin C. 2003. Gully erosion and environmental change: importance and research needs. Catena 50: 91-133.
– reference: Renschler CS. 2003. Designing geo-spatial interfaces to scale process models: the GeoWEPP approach. Hydrological Processes 17: 1005-1017.
– reference: Gordon LM, Bennett SJ, Bingner RL, Theurer FD, Alonso CV. 2007. Simulating ephemeral gully erosion in AnnAGNPS. Transactions of the ASABE 50(3): 857-866.
– reference: Garen DC, Moore DS. 2005. Curve number hydrology in water quality modelling: uses abuses and future directions. Journal of the American Water Resources Association 41: 377-388.
– reference: Hairsine PB, Rose CW. 1992. Modeling water erosion due to overland flow using physical principles: 2. Rill flow. Water Resources Research 28: 245-250.
– reference: Dabney SM, McGregor KC, Wilson GV, Cullum RF. 2009. How management of grass hedges affects their erosion reduction potential. Soil Science Society of America Journal 73(1): 241-254.
– reference: Kuhnle RA, Bingner RL, Foster GR, Grissinger EH. 1995. Effect of land use changes on sediment transport in Goodwin Creek. Water Resources Research 32(10): 3189-3196.
– volume: 50
  start-page: 91
  year: 2003
  end-page: 133
  article-title: Gully erosion and environmental change: importance and research needs
  publication-title: Catena
– volume: 35
  start-page: 1878
  year: 1996
  end-page: 1896
  article-title: Stochastic weather simulation: overview and analysis of two commonly used models
  publication-title: Journal of Applied Methods
– year: 2001
– start-page: 303
  year: 1982
  end-page: 324
– year: 1996
– volume: 73
  start-page: 241
  issue: 1
  year: 2009
  end-page: 254
  article-title: How management of grass hedges affects their erosion reduction potential
  publication-title: Soil Science Society of America Journal
– start-page: 713
  year: 2001
– volume: 45
  start-page: 311
  year: 2002
  end-page: 320
  article-title: Using CLIGEN to generate RUSLE climate inputs
  publication-title: Transactions of the ASAE
– volume: 89
  start-page: 221
  issue: HY3
  year: 1963
  end-page: 250
  article-title: An expression for bed‐load transportation
  publication-title: Proceedings of American Society of Civil Engineering
– volume: 50
  start-page: 857
  issue: 3
  year: 2007
  end-page: 866
  article-title: Simulating ephemeral gully erosion in AnnAGNPS
  publication-title: Transactions of the ASABE
– volume: 50
  start-page: 885
  year: 2007
  end-page: 900
  article-title: Model evaluation guidelines for systematic quantification of accuracy in watershed simulations
  publication-title: Transactions of the ASABE
– volume: 28
  start-page: 245
  year: 1992
  end-page: 250
  article-title: Modeling water erosion due to overland flow using physical principles: 2. Rill flow
  publication-title: Water Resources Research
– volume: 63
  start-page: 496
  issue: 6
  year: 2008
  end-page: 503
  article-title: Conservation practice effects on sediment load in the Goodwin Creek Experimental Watershed
  publication-title: Journal of Soil and Water Conservation
– volume: 40
  start-page: 921
  issue: 4
  year: 1997
  end-page: 933
  article-title: The WEPP watershed model: I. Hydrology and erosion
  publication-title: Transactions of the American Society of Agricultural Engineers
– volume: 20
  start-page: 157
  issue: 3
  year: 2005
  end-page: 175
  article-title: Modeling ephemeral gully erosion for conservation planning
  publication-title: International Journal of Sediment Research
– year: 1994
– volume: 117
  start-page: 725
  issue: 6
  year: 1991
  end-page: 737
  article-title: Investigation of curve number procedure
  publication-title: Journal of Hydraulic Engineering
– year: 2010
– volume: 32
  start-page: 3189
  issue: 10
  year: 1995
  end-page: 3196
  article-title: Effect of land use changes on sediment transport in Goodwin Creek
  publication-title: Water Resources Research
– start-page: 106
  year: 2009
– volume: 22
  start-page: 1069
  year: 2008
  end-page: 1079
  article-title: Implementing quality control on a random number stream to improve a stochastic weather generator
  publication-title: Hydrological Processes
– start-page: 193
  year: 1980b
  end-page: 281
– volume: 62
  start-page: 1667
  year: 1998
  end-page: 1672
  article-title: USLE‐M: Empirical modeling rainfall erosion through runoff and sediment concentration
  publication-title: Soil Science Society of America Journal
– start-page: 378
  year: 1977
– volume: 17
  start-page: 1005
  year: 2003
  end-page: 1017
  article-title: Designing geo‐spatial interfaces to scale process models: the GeoWEPP approach
  publication-title: Hydrological Processes
– year: 1965
– year: 2008
– volume: 41
  start-page: 377
  year: 2005
  end-page: 388
  article-title: Curve number hydrology in water quality modelling: uses abuses and future directions
  publication-title: Journal of the American Water Resources Association
– volume: 83
  start-page: 954
  year: 2002
  end-page: 957
  article-title: The GEM experience: weather generator technology development in the USDA
  publication-title: Bulletin of the American Meteorological Society
– year: 2006
– volume: 2
  start-page: 145
  issue: 3
  year: 1997
  end-page: 147
  article-title: Discussion: runoff curve number: has it reached maturity?
  publication-title: Journal of Hydrologic Engineering
– year: 2004
– volume: 11
  start-page: 631
  issue: 6
  year: 2006
  end-page: 635
  article-title: Enhanced runoff curve umber model incorporating storm duration and a nonlinear Ia‐S relation
  publication-title: Journal of Hydrologic Engineering
– year: 1997
– volume: 50
  start-page: 1613
  issue: 5
  year: 2007
  end-page: 1618
  article-title: Conservation planning for construction sites
  publication-title: Transactions of the ASABE
– start-page: 36
  year: 1980a
  end-page: 64
– start-page: 106
  year: 1992
– year: 1978
– start-page: 154
  year: 2003
  end-page: 160
– ident: e_1_2_14_38_1
– ident: e_1_2_14_21_1
– ident: e_1_2_14_35_1
– ident: e_1_2_14_19_1
  doi: 10.1175/1520-0450(1996)035<1878:SWSOAA>2.0.CO;2
– ident: e_1_2_14_25_1
  doi: 10.13031/2013.23153
– ident: e_1_2_14_26_1
  doi: 10.1016/S0341-8162(02)00143-1
– ident: e_1_2_14_15_1
  doi: 10.1175/1520-0477(2002)083<0954:TGEWGT>2.3.CO;2
– ident: e_1_2_14_5_1
  doi: 10.2136/sssaj2007.0434
– ident: e_1_2_14_32_1
– start-page: 193
  volume-title: CREAMS: A Field‐Scale Model for Chemicals, Runoff, and Erosion from Agricultural Management Systems
  year: 1980
  ident: e_1_2_14_8_1
– ident: e_1_2_14_40_1
  doi: 10.13031/2013.23957
– start-page: 106
  volume-title: Curve number hydrology, state of the practice
  year: 2009
  ident: e_1_2_14_2_1
– ident: e_1_2_14_27_1
– ident: e_1_2_14_10_1
  doi: 10.1111/j.1752-1688.2005.tb03742.x
– ident: e_1_2_14_4_1
– volume-title: Design Hydrology and Sedimentology for Small Catchments
  year: 1994
  ident: e_1_2_14_13_1
– ident: e_1_2_14_23_1
  doi: 10.1029/96WR02104
– start-page: 106
  volume-title: Ephemeral Gully Erosion Model (EGEM)
  year: 1992
  ident: e_1_2_14_36_1
– ident: e_1_2_14_14_1
  doi: 10.1029/91WR02381
– ident: e_1_2_14_17_1
  doi: 10.1061/(ASCE)0733-9429(1991)117:6(725)
– ident: e_1_2_14_34_1
– start-page: 36
  volume-title: CREAMS: A Field‐Scale Model for Chemicals, Runoff, and Erosion from Agricultural Management Systems
  year: 1980
  ident: e_1_2_14_7_1
– ident: e_1_2_14_37_1
– ident: e_1_2_14_28_1
  doi: 10.1002/hyp.1177
– ident: e_1_2_14_11_1
  doi: 10.13031/2013.23150
– volume: 89
  start-page: 221
  issue: 3
  year: 1963
  ident: e_1_2_14_39_1
  article-title: An expression for bed‐load transportation
  publication-title: Proceedings of American Society of Civil Engineering
– volume-title: SAS/STAT Software: Changes and enhancements through release 6.11
  year: 1996
  ident: e_1_2_14_29_1
– start-page: 154
  volume-title: First Interagency Conference on Research in the Watersheds
  year: 2003
  ident: e_1_2_14_9_1
– start-page: 378
  volume-title: Statistical Methods in Hydrology
  year: 1977
  ident: e_1_2_14_12_1
– ident: e_1_2_14_22_1
  doi: 10.2489/jswc.63.6.496
– ident: e_1_2_14_24_1
  doi: 10.1002/hyp.6668
– volume: 45
  start-page: 311
  year: 2002
  ident: e_1_2_14_41_1
  article-title: Using CLIGEN to generate RUSLE climate inputs
  publication-title: Transactions of the ASAE
  doi: 10.13031/2013.9952
– volume: 20
  start-page: 157
  issue: 3
  year: 2005
  ident: e_1_2_14_6_1
  article-title: Modeling ephemeral gully erosion for conservation planning
  publication-title: International Journal of Sediment Research
– ident: e_1_2_14_33_1
– volume: 2
  start-page: 145
  issue: 3
  year: 1997
  ident: e_1_2_14_30_1
  article-title: Discussion: runoff curve number: has it reached maturity?
  publication-title: Journal of Hydrologic Engineering
  doi: 10.1061/(ASCE)1084-0699(1997)2:3(145)
– start-page: 303
  volume-title: Rainfall–runoff relationships
  year: 1982
  ident: e_1_2_14_16_1
– ident: e_1_2_14_18_1
  doi: 10.1061/(ASCE)1084-0699(2006)11:6(631)
– ident: e_1_2_14_20_1
  doi: 10.2136/sssaj1998.03615995006200060026x
– ident: e_1_2_14_3_1
  doi: 10.13031/2013.21343
– start-page: 713
  volume-title: Proceedings of the International Symposium on Soil Erosion Research for the 21st Century, 3–5 Jan 2001, Honolulu, HI
  year: 2001
  ident: e_1_2_14_31_1
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Snippet RUSLE2 (Revised Universal Soil Loss Equation) is the most recent in the family of Universal Soil Loss Equation (USLE)/RUSLE/RUSLE2 models proven to provide...
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SubjectTerms Channels
climate
concentrated flow
cotton
ephemeral gully
Erosion
Erosion mechanisms
field crops
Gullies
gully erosion
hydrologic models
land use
Mathematical models
Mississippi
prediction
rain
rain intensity
Rainfall
Revised Universal Soil Loss Equation
Runoff
RUSLE
sediment
sediment transport
sheet erosion
soil
Soil (material)
storms
Universal Soil Loss Equation
Title Enhancing RUSLE to include runoff-driven phenomena
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Volume 25
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