2. Runoff Estimation, and Surface Erosion and Control Ali Fares, PhD NREM 600, Evaluation of Natural Resources Management

3. What ’ s soil erosion? Erosion is the process of detachment and transport of soil particles by erosive agents (Ellison, 1944) Erosion is a natural geologic process o WATER EROSION o WIND EROSION o TILLAGE TRANSLOCATION

4. SOIL EROSION IS GLOBAL PROBLEM q 1/3 WORLD’S ARABLE LAND LOST SINCE 1950 q MOST IN ASIA, AFRICA, S. AMERICA q 13-18 t/a/yr q 30% OF US FARMLAND ABANDONED q EROSION q SALINIZATION q WATER-LOGGING q 90% OF US CROPLAND LOSING SOIL FASTER THAN IT IS REPLACED q >1 t/a/yr

5. SIGNIFICANT SOIL LOSS IN THE USA WATER 3.5 X 10 9 T/yr WIND 1.5 X 10 9 T/yr

7. WIND EROSION WIND CREEP SUSPENSION SALTATION q SALTATION DETACHES PARTICLES q SMALLER PARTICLES SUSPENDED q LARGER PARTICLES CREEP q SANDY AND SILTY SOILS MOST SUSCEPTIBLE q SOIL ACCUMULATION IN DITCHES AND FENCE ROWS

8. WIND EROSION CAN BE SIGNIFICANT Near Mitchell, SD

9. Dust bowl 1931-1939 there was a drought called the “dust bowl”. It caused huge dust storms to erupt that destructed billions of acres of farm land.

10. storms In the first year of the drought there were 14 storms reported and the second year there were 38 storms. It was getting worse.

11. Ruined land Tons of damage was done to every ones land and it costs billions of dollars to repair the damages.

12. Black Sunday April 14 th,1934 black Sunday was the worst blizzard of the dustbowl which caused the most extensive damage.

14. REDUCING WIND EROSION q MAINTAIN SURFACE COVER q CROP RESIDUE q COVER CROPS q INCREASE STUBBLE HEIGHT q INSTALL WINDBREAKS q EFFECTIVE 15x HEIGHT q IRRIGATE q STRIP CROPS PERPENDICULAR TO PREVAILING WIND

15. The Shelterbelt Program

16. WATER EROSION PROCESS BEGINS WITH RAINDROPS STRIKING BARE SOIL DISLODGING PARTICLES INTENSE RAINS SEAL SURFACE WHEN RAINFALL EXCEEDS INFILTRATION WATER IS STORED IN SMALL DEPRESSIONS ONCE DEPRESSIONS ARE FILLED, RUNOFF BEGINS

17. WATER EROSION PROCESS Initially water flows in a discontinuous sheet Eventually it concentrates into small channels or rills. The runoff now has energy to break off particles and cut deeper The amount of erosion caused by sheet and rill erosion increases with slope and distance Rills may eventually form gullies

18. THE SOIL WATER EROSION PROCESS

19. EFFECTS ON ENVIRONMENTAL QUALITY AND PRODUCTIVITY LOSS OF OM, CLAY, AND NUTRIENTS REDUCES PRODUCTIVITY DAMAGE TO PLANTS FORMATION OF RILLS AND GULLIES AFFECTS MANAGEMENT SEDIMENTATION IN WATERWAYS, DIVERSIONS, TERRACES, DITCHES DELIVERY OF NUTRIENTS TO SURFACE WATER

20. Quantifying Soil Erosion

25. Standard USLE plot: – 22.1m (72.6 ft) long – 9% slope – 4m (13.12 ft) wide.

26. USLE Universal Soil Loss Equation  Wischmeier, W.H. and D.D. Smith. 1978. Predicting rainfall erosion losses. USDA Agriculture Handbook 537, U.S. Department of Agriculture.

27. Empirical model: – Analysis of observations – Seeks to characterize response from these data. Based on: – Rainfall pattern, soil type, topography, crop system and management practices. Predicts: – Long term average annual rate of erosion Subroutine in models such as: – SWRRB (Williams, 1975), EPIC (Williams et al., 1980), ANSWERS (Beasly et al., 1980), AGNPS (Young et al., 1989)

28. The equation: A = R x K x LS x C x P – A = average annual soil loss (tons/acre year) – R = rainfall and runoff erosivity index – K = soil erodibility factor – L = slope length factor – S = slope steepness factor – C= crop/management factor – P = conservation or support practice factor

29. R (rainfall and runoff erosivity index) Erosion index (EI) for a given storm: – Product of the kinetic energy of the falling raindrops and its maximum 30 minute intensity. R factor =  EI over a year / 100 A = R x K x LS x C x P

30. Average annual values of the rainfall erosion index (R).

31. K (soil erodibility) Susceptibility of a given soil to erosion by rainfall and runoff. Depend on: – Texture, structure, organic matter content, and permeability. A =R x K x LS x C x P

32. Soil-erodibility nomograph.

33. LS (slope length-gradient) Ratio of soil loss under given conditions to that at a site with the "standard" slope and slope length. A =R x K x LS x C x P

34. Topographic LS factor

35. C (crop/management) Ratio of soil loss from land use under specified conditions to that from continuously fallow and tilled land. A =R x K x LS x C x P CropFactor Grain Corn0.40 Silage Corn, Beans & Canola0.50 Cereals (Spring & Winter)0.35 Seasonal Horticultural Crops0.50 Fruit Trees0.10 Hay and Pasture0.02 TillageFactor Fall Plow1.00 Spring Plow0.90 Mulch Tillage0.60 Ridge Tillage0.35 Zone Tillage0.25 No-Till0.25

36. P (conservation practices) Ratio of soil loss by a support practice to that of straight-row farming up and down the slope. A =R x K x LS x C x P Support PracticeP Factor Up & Down Slope1.00 Cross Slope0.75 Contour farming0.50 Strip cropping, cross slope0.37 Strip cropping, contour0.25

37. USDA Agriculture Handbook 703 (Renard et. al. 1997) USLE factor values: updated, expanded, improved. – Expanded isoerodents – Ponded water on the soil – Freeze-thaw cycle and soil moisture – Complex slopes – Conservation tillage and crop rotation Software RUSLE: Revised Universal Soil Loss Equation

38. WHAT IS RUSLE 2 “GREAT GRANDSON” OF USLE MODEL TO PREDICT SOIL LOSS – WHERE OVERLAND FLOW OCCURS – COMPUTES ANNUAL SHEET/RILL EROSION – COMPUTES PARTICLE DISTRIBUTION AND RUNOFF CROPLAND, FOREST, LANDFILLS, CONSTRUCTION SITES, SURFACE MINES WINDOWS “PULL DOWN” MENUS

39. WHO AND WHAT OF RUSLE 2 USDA-ARS, USDA-NRCS, VARIOUS UNIVERSITIES ON-GOING PROCESS OVER 70 YEARS THOUSANDS OF RESEARCH DATA SET UP WITH VARYING LEVELS OF COMPLEXITY COMPUTER REQUIREMENTS – WINDOWS 98 – INTERNET EXPLORER BROWSER – 64 MB RAM DOWNLOAD – HTTP://BIOENGR.AG.UTK.EDU/RUSLE2/ HTTP://BIOENGR.AG.UTK.EDU/RUSLE2

40. APPLICABILITY OF RUSLE 2 ESTIMATES INTER-RILL AND RILL EROSION ESTIMATES SEDIMENT YIELD FROM OVERLAND FLOW AND TERRACE CHANNELS DOES NOT ESTIMATE EPHEMERAL OR PERMANENT GULLIES, MASS WASTING, OR STREAM CHANNEL EROSION BEST SUITED TO CROPLAND, BUT IS USEFUL FOR CONSTRUCTION SITES, LANDFILLS, RECLAMATION PROJECTS, AND DISTURBED FOREST LAND

41. APPLICABILITY OF RUSLE 2 (cont.) BEST WHERE RAINFALL IS REGULAR AND EXCEEDS 20”/YR. MEDIUM-FINE TEXTURED SOILS SLOPES 3-20% AND LESS THAN 600 FT. BEST AT CALCULATING “AVERAGE ANNUAL SOIL LOSS”, NOT RECOMMENDED FOR SINGLE STORM EVENTS

42. RUSLE 2 FACTORS A = R x K x LS x C x P CLIMATE (R) AND SOIL (K) FACTORS ARE SET FOR A GIVEN FIELD SLOPE GRADE (S) AND LENGTH (L) CAN BE ADJUSTED WITH DIFFICULTY MOST FLEXIBILITY WITH COVER MGT. (C) AND SUPPORTING PRACTICES (P)

43. EROSION CONTROL PRACTICES Structures: diversions, terraces, waterways Reduce slope length Slow runoff velocity Divert excess water safely Avoid runoff over barnyard, feedlots, etc.

44. CONTOUR TERRACES Grant Co.

45. EROSION CONTROL PRACTICES Management practices – Cover crops – Crop residue management 30% residue reduces erosion 50-60% – Contour tillage Slope < 8% and 300’ long – Contour strip cropping and buffers Alternating sod strip for steep land

47. Controlling Water contaminants at the Source, Kaiaka-Waialua Watershed

48. Kaiaka and Waialua bays, are water quality limited segments due to high levels of total P, NO - 3, chlorophyll a, and turbidity exceeding the maximum allowable levels (HI-DOH). Sediment loads from agricultural lands and effluent discharged from household cesspools are two of the major sources of pollution. Sediment losses are generated from cropped and fallow zones as a result of an intensive agricultural system that includes a crop/fallow cropping combination.

49. Objectives The goal of this project is to implement and demonstrate erosion control practices to help manage erosion throughout Kaiaka- Waialua watershed, thereby reducing sediment and potential pollutant loads (P, N) into the surface water resources, and consequently improving water quality of the coastal area.

50. Materials and Methods Field in a commercial farm, Ewa Silty clay soil, a mean Ksat = 3.5 cm d -1 (Candler 15 m d -1 ) Three cover crops (Sunn hemp, Sudex & Oats) were replicated 3 times in a RCB design. Suction cups were installed in each plot to collect soil solution Surface runoff was collect from each plot following rainfall. Soil water contents (10,20,30 & 50cm) from each treatment

51. Materials and Methods Soil physical properties were determined: Ksat, BD & soil water release curve Soil samples were collected before, in the middle and at the end of the trial. Total dissolved and total suspend solids (TDS, TSS) were determined (EPA’s 160.1, 160.2 methods) NO3, NH4 and P were determined by UH-ADSC

52. Materials and Methods

54. Subsurface Water Quality Analysis Collected soil solution samples were analyzed at the University of Hawai’i (ADSC) for: – Ammonium – Nitrate – Total Nitrogen and – Phosphorus

55. Results Runoff water quality Subsurface water quality

57. March 3 03-16 March 22 March 25 March 31 April 7 April 18 April 22 April 27 May 18 292 mm occurred in 11 hr, 2/27 at a rate of 24 mm hr-1

58. ---------------March---------------- --------------April----------- -May Variable316222531718222718 TSS NS **** NS ***** TDS NS ** NS Nitrate * NS * ** NS ** NS ** Ammonium NS ** NS ** NS ** NS TN * NS ** NS**NS Phosphorous NS ** *, ** denotes a significant or highly significant difference was detected between treatment means, respectively. ANOVA Runoff Results

59. Sunn hemp Oats Fallow Sudex Surface Runoff Collection

60. Runoff water Quality TSS, 70% there was statistically significant treatment effect Nitrate, 50% there was statistically significant treatment effect Ammonium, 40% there was statistically significant treatment effect TN, 60% there was statistically significant treatment effect

61. Removal Efficiencies Calculation for Removal Efficiencies (RE): RE = [1- (Cover Crop (g) / Fallow (g))]x100 A positive RE means that there was a reduction in pollutant levels in comparison to the fallow A negative RE means that there was an increase in pollutant levels in comparison to the fallow treatment

62. Date3/33/163/223/253/314/74/184/224/275/18AVG Rainfall (mm)4062119178249517105 Sudex7372578451818660529474 Sunn Hemp7758709370729095879177 Oats8642809779809196908385 Removal Efficiencies for TSS

63. Date3/33/163/223/253/314/74/184/224/275/18AVG Rainfall (mm)4062119178249517105 Sudex418 276-27-38-9834-295-35.1 Sunn Hemp-92455346-68-150-83-4-96-29.1 Oats11-1939-43-55-270-189-58-150-73.5 Removal Efficiencies for Total Dissolved Solids

64. A A A A B A B B

65. Date 3/33/163/223/253/314/74/184/224/275/18AVG Rainfall (mm) 4062119178249517105 Sudex -7-4-70444672-9-585113 Sunn Hemp -53 -52-196-8-3819-17-10234-47 Oats 43-69-681857706061123122 Removal Efficiencies for Total Nitrogen

66. B A B AB A A A A

67. Date3/33/163/223/253/314/74/184/224/275/18AVG Rainfall (mm)4062119178249517105 Sudex2.4-5-25-1545-13267-46-6857-12 Sunn Hemp-43-65-83-242-133635-43-14532-53 Oats49-53-753073656153-123923 Removal Efficiencies for Ammonium

68. Soil Solution Samples ANOVA Variable3/223/253/314/7 Nitrate*** NS AmmoniumNS TN*** NS PhosphorousNS * denotes a significant difference was detected ** denotes a highly significant difference was detected

69. AB B B A

70. B B A

71. B A B B

72. Summary & Conclusions The presence of cover crops reduced the nitrate and total nitrogen levels in the soil solution compared to the fallow treatment regardless of the sampling date. 95 to 97% of the total nitrogen collected was nitrate. The sunn hemp treatment had the second highest nitrate and total nitrogen levels after the fallow treatment.

73. Statistical Analyses Results There were statistically significant effects of the cover crops on: – Nitrate and total nitrogen for all reported sampling dates: March 21, 25, 31 & April 7 However, cover crops effect was not statically significant for: – Ammonium and Total Phosphorus

74. CONTOUR STRIP CROPPING Crawford CO

76. Terracing & Contour Farming

77. References Millward, A. A., and Mersey, J. E.,(1999) Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed, Catena, 38(2), 109-129. DeRoo A.P.J. (1998) Modelling runoff and sediment transport in catchments using GIS. Hydrological Processes 12(6),905-922. http://www.bsyse.wsu. edu/cropsyst/manual/si mulation/soil/erosion.h tm http://www.bsyse.wsu. edu/cropsyst/manual/si mulation/soil/erosion.h tm WOLKOWSKI, D.Soil Science Dept. UW- Madison.