Presentation is loading. Please wait.

Presentation is loading. Please wait.

Soil Erosion Peter Kinnell Research area: Rainfall erosion processes and prediction

Similar presentations


Presentation on theme: "Soil Erosion Peter Kinnell Research area: Rainfall erosion processes and prediction"— Presentation transcript:

1 Soil Erosion Peter Kinnell Research area: Rainfall erosion processes and prediction http://ozemail.com.au/~pkinnell

2 Soil Erosion Soil erosion requires particles to be plucked from a surface where they are held by gravity and other forces (interparticle friction, cohesion) and moved laterally away from the place where they were.

3 Tectonics: Lifts the Earth Surface Soil Erosion: ► Flattens the Earth Surface ► Moves soil material over the Earth Surface Soil Erosion

4 Drivers 2 primary drivers: Wind – semi-arid and arid areas Water – non arid areas Gravity is involved in wind and water erosion

5 Importance of Soil Erosion by Water Geological time Modification of landform Soil formation Current time Onsite Land degradation – loss of productivity Offsite  Deposition of sediment on land - beneficial eg: soil fertility of flood plains - problematic eg: in buildings, on roads  Soil material in rivers affects water quality Translocation of material over the landscape Soil Catena

6 Geographic Distribution Climate and soil characteristics control whether erosion occurs by wind or water Water erosion vulnerability

7 Wind Erosion

8 Water Erosion in Arid/Semi-arid areas Nevada, USA

9 Wind Erosion Energy required to drive erosion comes from wind Wind speed is the wind factor normally considered Dry non-cohesive soil material at the surface is highly susceptible to being blown by wind

10 Wind Erosion Wind driven saltation and creep Sahara desert

11 Wind Driven Saltation & Creep Saltation – hop Creep - roll Wind

12 Very fine particles remain suspended in air Dust Wind

13 Dust Broken Hill, NSW 22 Sept 2009

14 Dust Sydney, NSW 23 Sept 2009

15 Wind Erosion Soil lost per unit area Wind speed Critical speed required for wind to overcome forces holding particles to soil surface (gravity, interparticle friction, cohesion) o

16 Water Erosion 2 Drivers: Surface Water Flow Raindrop Impact

17 Water Erosion Channels caused by flow driven erosion Processes similar to wind erosion Rill Erosion Gully Erosion

18 Flow Driven Saltation & Rolling Flow

19 Very fine particles remain suspended in water Suspended Load Flow

20 Flow Driven Erosion Soil lost per unit area Flow energy Critical energy required for water to overcome forces holding particles to soil surface (gravity, interparticle friction, cohesion) Raindrops impacting the soil can also overcome the forces holding particles to the soil surface o

21 On sloping surfaces more splashed down slope than up so more erosion as slope gradient increases Raindrop Detachment & Splash Transport (RD-ST) Splash Erosion Transport process limits erosion particularly on low gradient slopes - Relatively inefficient erosion system especially on slopes with low to moderate gradients Raindrop impact driven erosion Detachment = the process of plucking particles held within the soil surface by cohesion and interparticle friction

22 Detachment and uplift caused by raindrops impacting flow Flow Raindrop impact driven erosion Rain-impacted flow Transport Mechanism 1. Raindrop Induced Saltation (RIS) Detachment by raindrop impact may be followed by 1.Raindrop induced saltation (RIS) 2.Raindrop induced rolling (RIR) 3.Transport in suspension (FS) 4.Flow driven saltation (FDR) 5.Flow driven rolling (FDR) Rain-impacted flows have more efficient transport processes

23 Particles move downstream during fall Flow Wait for a subsequent impact before moving again Transport Mechanism 1. Raindrop Induced Saltation (RIS) Raindrop impact driven erosion Rain-impacted flow

24 Transport Mechanism 2. Raindrop Induced Rolling (RIR) Particles move downstream by rolling Flow Wait for a subsequent impact before moving again Raindrop impact driven erosion Rain-impacted flow

25 Small particles remain suspended and Flow Large particles wait move without raindrop stimulation Acts at the same time as RD – RIS/RIR Raindrop impact driven erosion Rain-impacted flow Transport Mechanism 3. Flow Suspension (FS)

26 After detachment by drop impact Coarse particles Flow move without raindrop stimulation Raindrop impact driven erosion Rain-impacted flow Transport Mechanism 4. Flow Driven Saltation (FDS) Transport Mechanism 5. Flow Driven Rolling (FDR )

27 Raindrop impact driven erosion Rain-impacted flow Pedestals result from stone protecting the soil beneath them from detachment by raindrop impact while raindrop detachment and sediment transport by rain- impacted flows occurs in the surrounding area

28 Raindrop impact driven erosion Rain-impacted flow A lot of the soil loss is INSIDIOUS 1 mm loss from the surface on 1 km 2 = 1 m x 1 m x 1km channel

29 Critical conditions for detachment and transport modes Change in soil surface (crusting) Flow depth effect on drop energy available for detachment Erosion results from the expenditure of energy associated with both flow and raindrop impact

30 Critical conditions for detachment and transport modes Flow Energy Flow detachment only occurs when the shear stress needed to cause detachment is exceeded Raindrop detachment only occurs when the raindrop energy exceeds that needed to cause detachment Coarse sand RD-RIR Coarse sand RD-FDR Splash Erosion Rain Driven Transport in Flow Flow Driven Transport Raindrop driven erosion Change in soil surface (crusting) Flow depth effect on drop energy available for detachment Flow driven erosion NB: Both raindrop detachment and flow detachment can operate at the same time Not a 2D (X,Y) graph Erosion results from the expenditure of energy associated with both flow and raindrop impact

31 Rain Forms of Water Erosion on a Hillslope Splash Erosion Flow energy increasing Rill & Interrill Erosion Rill Interrill Sheet Erosion Surface Runoff River (Gully Erosion) Rills occupy a small proportion of the surface area Splash Erosion, Sheet Erosion, and Interrill Erosion operate over most of the nutrient rich soil surface

32 Prediction of Rainfall Erosion Map of climatic effect on soil loss as determined by the Universal Soil Loss Equation The USLE is the most widely used erosion model in the world

33 Universal Soil Loss Equation Soil Loss = f (climate, soil, topography, landuse) A = R K LS C P A = Long term average annual soil loss (~ 20 years) caused by sheet and rill erosion R = rainfall-runoff (erosivity) factor [CLIMATE] K = soil (erodibility) factor ● LS = topographic factors (L re slope length S re slope gradient) C = crop/crop management factor [VEGETATION] P = soil conservation practice factor

34 Universal Soil Loss Equation Soil Loss = f (climate, soil, topography, landuse) A = R K LS C P Developed from more than 10,000 plot-years of experiments in the USA

35 Universal Soil Loss Equation Soil Loss = f (climate, soil, topography, landuse) A = R K LS C P C, P & L are the main factors modified by land management A has units of weight per unit area (t/ha) = the amount of soil lost from a specific area divided by the area The soil loss within that area may not be uniform - the bigger the area the less likely it is to be uniform

36 Universal Soil Loss Equation Soil Loss = f (climate, soil, topography, landuse) A = R K LS C P Originally developed in the 1960s The Revised USLE (RUSLE):1997 An update of the USLE to take account of new information gained since the 1960s and 70s The mathematical form of the model remained as above but changes were made to the way in which some of the factor values are calculated

37 Universal Soil Loss Equation Soil Loss = f (climate, soil, topography, landuse) A = R K LS C P USLE/RUSLE used widely in the world including Australia Catchment Erosion Urban Erosion State of Environment Reports Implemented in NSW via SOILOSS computer program (Dept Land & Water Conservation, NSW)

38 Universal Soil Loss Equation Oz Validation - 6 SCS NSW Research Stations bare soil

39 A 1 = R K = 10 t/ha A 1 A C = A 1 ( L S C P ) 10 A C = 10 (1.22 x 0.57 x 0.16 x 1.0) = 1.1 t/ha Unit Plot 22m long 9% slope bare soil 33m long 6% slope Cropped Plot Works mathematically in 2 steps: 1. Predict the loss from a control plot called the “unit” plot 2. Use factors to adjust this to predict loss from area of interest

40 R factor The R factor is dependent on the total kinetic energy of the raindrops produced by rain during rainstorms over many (20 or so) years and the maximum rainfall intensities that occur during those storms

41 R Map for New South Wales Erosivity increases from the inland to the coast Erosivity increases northward along the coast

42 K: soil erodibility factor K from field experiments:  Time - 5 years or more  Expense - setup of plots (equipment and labour) - maintenance (equipment and labour) - resources tied up in data collection  Predict K from soil properties - less time and expense

43 K from soil characteristics K = 2.77 M 1.14 (10 -7 ) (12-OM) + 4.28 (10 -3 )(SS-2) + 3.29(10 -3 ) (PP-3) K in SI units M (% silt + % very fine sand) (100 - % clay) - soil texture OM% organic matter - organic matter SSsoil structure code (USDA Soil Survey Manual) - soil structure PP USDA profile permeability class - water entry Developed by Wischmeier el al (1971) for soils in the USA where silt + very fine sand is 70% and less but commonly used in many other places Other equations for other soils (Volcanic) and using other properties have been developed in some countries

44 C: crop & management factor N  A e.C e=1 C = —————— N  A e.1 e=1 A e.C = event loss with crop and L = S = P = 1.0 A e.1 = event loss for bare fallow and L = S = P = 1.0 A = R K L S C P cropbare 22 m 9 % Conceptually C = 1.0 for the “unit” plot a bare fallow area 22 m long with a 9 % slope gradient

45 C varies geographically C =  C i (R i /R) where i is a period (eg month) during a year C depends on how the crop grows over time C depends on how rainfall erosivity varies over time

46 C varies geographically C =  C i (R i /R) where i is a period during a year Bare soil has high C i. C factor highly influenced by R i /R during cultivation for crop establishment C influenced by how well the crop grows – area not well suited, poor growth produces high C C i values depend on above ground vegetative cover, on ground cover (trash), soil roughness (cultivation), etc – documented in technical manuals

47 C varies geographically C =  C i (R i /R) where i is a period during a year Avoid bare soil (high C i ) when R i /R is high R

48 P: support practice factor Accounts for impact of conservation practice eg. cultivation across slope vs up/down slope P = 1.0 for cultivation up/down P = 0.75 for example with cultivation across Support practices * Across slope - P varies with ridge height, furrow grade * Strip Cropping, Buffer strips, Filter strips, Subsurface drains A = R K L S C P

49 S: slope factor USLE: S = 65.4 sin 2  + 4.56 sin  + 0.0654  angle to horizontal RUSLE: S = 10 sin  + 0.03 slopes <9% S= 16.8 sin  - 0.50 slopes  9% USLE S overpredicts erosion at high slope gradients A = R K L S C P S = 1.0 when the slope gradient is 9 %

50 L: slope length factor L = ( / 22.13) m USLE: m=0.6 slope >10%  m=0.2 slope <1% RUSLE: m =  / (1+  )  = ratio rill to interrill erosion is the projected horizontal distance travelled by runoff before deposition or a channel occurs A = R K L S C P L = 1.0 when the slope is 22.13 m long

51 Hands on RUSLE The SOILOSS program will be used later today and can be download at anytime from http://ozemail.com.au/~pkinnell/SOILOSS.htm http://ozemail.com.au/~pkinnell/SOILOSS.htm It prompts the user to go through the steps required to get a result. It requires outside knowledge of some factor values such as R. Values for C for some crop and crop management options are calculated by the program but the options may not represent current practices. Users can setup background files to overcome such issues

52 RUSLE 2 The RUSLE does not model the effect of deposition caused by a change in slope gradient Commonly, a factor known as the sediment delivery ratio; sediment delivered from the hillslope SDR =  erosion predicted as if no deposition occurred is used in catchment scale models. RUSLE 2 is a hillslope model that now replaces the RUSLE in the USA. It uses physical principles to predict deposition caused by a change in slope gradient deposit

53 RUSLE 2 22 t/ha/yr

54 Effect of Erosion on Water Quality In USA About 60% of the pollution in rivers comes from agriculture In UK About 50% of the pollution in rivers comes from agriculture In Australia Most rivers in the Murray Darling Basin are polluted to a large degree from material that comes from the land - an issue of concern throughout the world

55 Effect of Erosion on Water Quality Molonglo river flows into Lake Burley Griffin

56 Effect of Erosion on Water Quality Green: low amounts indicating early stage of a possible bloom Amber: algae multiplying to give green tinge – water ok for recreational use only Red: Toxic bloom conditions Algae blooms are a result of nutrients that come from the land

57 AGNPS 2000 SWAT ANSWERS 2000 WEPP small watershed model   Sednet Australia USA Europe Models: Catchment scale models: Tools to model the impact of landuse on water quality Many catchment models use the RUSLE

58 Catchment scale models: Tools to model the impact of landuse on water quality AGNPS 2000, Sednet and some others include channel erosion (gullies)

59 Commonly use grid cell representation of the landscape Map overlaid with grid with e.g. spacing of 50 m Each cell is considered to be uniform with respect to soil, vegetation, slope gradient etc Enables soil loss caused by sheet and rill erosion to be modelled for each cell using RUSLE methodology Applying the RUSLE in 2D space A 1.cell = R K cell ( Bare 22 m long 9 % slope ) A cell = A 1.cell L cell S cell C cell P cell

60 Generated from elevation and land cover data – Geographic Information Systems channel Representation of land use and flow directions Applying the RUSLE in 2D space

61 Dividing a hillslope into lesser hillslopes provides a mechanism for predicting soil loss when factors other than R vary down along a hillslope. 1 2 3 4 5 A hillslope can be divided into number of lesser hillslopes L = ( / 22) m

62 Water flow through bottom cell the same in all cases Applying the RUSLE in 2D space ?? Soil loss varies with flow through the cell not upslope length itself

63 slope length for grid cells ( A i,j-in + D 2 ) m+1 - A i,j-in m+1 L i,j = ———————————— D m+2 (22.13) m A i,j-in D Enables the USLE/RUSLE to be applied in modeling erosion in catchments

64 Something not in the Text Book

65 The R factor problem A = R K L S C P R is readily mapable like all the other factors BUT is the only factor that is not affected by what is on the land surface If the value of R is incorrect then the model output is wrong irrespective of anything else

66 N N = number of events in Y years  R e R e = Event erosivity factor e=1 R = ———— Y Y = number of years R e = storm energy x max 30-min rainfall intensity The R factor problem

67 R = average annual sum of event energy (E) and the maximum 30-minute intensity (I 30 ) Event soil loss : A e = K (EI 30 ) e L S C e P e Bare fallow b1b1 The R factor problem

68 R = average annual sum of event energy (E) and the maximum 30-minute intensity (I 30 ) Event soil loss : A e = K (EI 30 ) e L S C e P e   Under predicts large losses   Over predicts small losses Bare fallow b1b1 The R factor problem

69 It is well known that a relationship exists between soil loss and runoff BUT the USLE/RUSLE model does not consider runoff explicitly as a factor in producing soil loss The R factor problem

70 A e1 = Q e c e A e1 = unit plot event loss Q e = event runoff c e = sed. concentration (soil mass per unit quantity of runoff)A e1 = Q e c e A e1 = unit plot event loss Q e = event runoff c e = sed. concentration (soil mass per unit quantity of runoff) USLE: c e = f (energy per unit quantity of runoff, rainfall intensity)USLE: c e = f (energy per unit quantity of runoff, rainfall intensity) Analysis of plot data: c e = f (energy per unit quantity of rain, rainfall intensity)Analysis of plot data: c e = f (energy per unit quantity of rain, rainfall intensity) c e = E / rainfall amountc e = E / rainfall amount A 1e = k Q e E I 30 / rainfall amountA 1e = k Q e E I 30 / rainfall amount Q e / rainfall amount = Q R, the runoff ratioQ e / rainfall amount = Q R, the runoff ratio R e = [Q R EI 30 ] I 30 The R factor problem

71 R e = EI 30 R e = Q R EI 30 The R factor problem

72 The USLE-M is the name given to the version of the USLE/RUSLE model that uses the Q R EI 30 index (Kinnell and Risse, 1998) USLE: 2 mathematical steps A 1 = R K A = A 1 L S C P USLE-M: A 1 = R USLE-M K USLE-M [ K USLE-M ≠ K because R USLE-M ≠ R] A = A 1 L S C P The USLE-M 10 = 5 x 2 10 = 4 x 2.5 10 = 3 x 3.33

73 Why does the USLE/RUSLE model not include direct consideration of runoff ? The USLE-M works well when runoff is known or predicted well - as a general rule runoff is not easy to predict The USLE/RUSLE model is designed to help make decisions about land management effects over the long term (~20 years) not predict short term soil loss such as event erosion or year by year variations However, when it come to modelling the effect of landuse on water quality event soil losses are important so the USLE/RUSLE model is used to do this but in so doing the USLE/RUSLE model is being applied to do things that it wasn’t designed to do The R factor problem

74 Erosion Model Overview (all models not just the USLE/RUSLE) Not all factors dealt with adequatelyNot all factors dealt with adequately Familiarity with model & assumptions essential when using themFamiliarity with model & assumptions essential when using them While the results may not be very accurate, they can provide a means of making useful decisions about land management in order to conserve soil and improve water qualityWhile the results may not be very accurate, they can provide a means of making useful decisions about land management in order to conserve soil and improve water quality

75

76 SOILOSS SOILOSS is a computer program that runs the Revised Universal Soil Loss Equation for various locations in New South Wales The program is run from Explorer by double clicking on the SOILOSS Shortcut in the ALRS directory

77 Use space bar – user entry optional

78 Note instructions for data entry

79 Use “enter” to move to next screen

80 Enter zone – see climate zone map for NSW

81 R values for locations are provided using RAINER

82 Click OK to move to next screen RAINER is run from EXPLORER by double clicking on the RAINER shortcut in the ALRS directory

83 Click on “Load” to get location selection screen and then select location from list

84 The R factor value for the location is displayed here

85 Soil erodibility is determined using the table of soils

86 Mover the cursor by the arrow keys to select the soil required – eg Chocolate

87 Slope gradient is measured in percent and will be entered in the next screen

88 After entering slope gradient enter slope length

89 Select Cultivation around the paddock

90 Select Annual Crops (standard)

91 Select a crop and press “Enter” to enter the crop for each year required

92 Select a crop and press “Enter” to enter the crop for each year required – 10 year rotation Z to end selection prior to 10 years

93 Select tillage practice required

94 Result screen You can use ESC to go backwards to alter data entry values and then use “enter” to strp forward to get the result

95

96


Download ppt "Soil Erosion Peter Kinnell Research area: Rainfall erosion processes and prediction"

Similar presentations


Ads by Google