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PREDICTION OF SOIL LOSSES

PREDICTION OF SOIL LOSSES.

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PREDICTION OF SOIL LOSSES

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  1. PREDICTION OF SOIL LOSSES

  2. EMPIRICAL WATER EROSION FORMULASA= k s 0,75 L1,5I1,5 (Kornev,1937) A= k s 1,49 L1,6 (Zingg,1940)A= k s 0,8 p I1,2(Neal,1938) A= k s 0,75 L1,5 (I-i)1,5(Kostiakow, 1938)A= c s 1,5 L0,35 (Musgrave, 1947)where: A –soil loss, k – coefficient, s- slope, L- slope length, p- rainfall, I –rain intensity, i – infiltration rate, c- crop factor.

  3. USLEUniversal Soil Loss Equation • The Universal Soil Loss Equation (USLE) is the most widely used predictive estimator for annual soil erosion rates. • The equation can be used to estimate the average annual soil loss in tons per hectare or to determine the value of other parameters to meet a desired value of tolerance soil loss amount. • The equation can be used for estimating average annual soil loss from sheet and rill erosion only.

  4. The USLE is not based on physical principles. The USLE is an empirical equation derived from more than 10,000 plot-years of data collected on natural runoff plots and an estimated equivalent of 2,000 plot-years of data from rainfall simulators.

  5. WISCHMEIER’S PLOT

  6. The Universal Soil Loss Equation (USLE) A = R K L S C P where: A- mean annual soil loss [t ha-1year-1], R - rainfall erosivity index [ MJ ha –1mm h-1], K - soil erodibility factor [t MJ-1year-1 ha –1 h mm -1], L - slope length factor (dimensionless), S - slope steepness factor (dimensionless), C - crop management factor (dimensionless), P - erosion control practice factor (dimensionless).

  7. USLE R-Factor • A = R K LS C P • R is the rainfall factor • R = SEI • E is the Energy in the Rainfall • I is the maximum half-hour rainfall intensity for the storm. • R varies with the climate at a particular location.

  8. Average Annual Rainfall Factor (R)

  9. SOIL ERODILILITYErodilility defines the resistance of the soil to detachment and transport. It depends to some extent on topographic position, slope steepness and the extent of disturbance during tillage or due to devegetation.Shear strength of a soil is a measure of its cohesiveness and resistance to shearing forces exerted by gravity or moving water. It is derived from frictional resistance between particles. Increases in moisture reduce shear strength by reducing friction and causing aggregate breakdown.The proportion of easily dispersed clays is a factor in high erodibility.

  10. SOIL CRUSTING • Soils with high aggregate stability are resistant to surface crusting. • Crusting may increase surface erosion by reducing infiltration rates and increasing runoff discharge on the hillslope. • Crustability decreases with increasing clay content. Loams are most susceptible. • High proportions of exchangeable sodium causes loss of soil strength on wetting.

  11. Soil erodibility factor K depends on: • soil texture, • soil structure, • permeability, • content of organic matter.

  12. USLE LS-Factor • A = R K LS C P • LS is the field topography factor • L is the slope length factor • S is the slope degree factor • L = 1 for a field length of 72.6 feet • S = 1 for a field slope of 9% • LS is a ratio of erosion for the given condition to erosion for the standard

  13. Slope length factor (L) is the relation between the soil loss on the actual slope length and the standard slope with constant other parameter values. • Slope gradient factor (S) is the relation between the soil loss on the actual slope gradient and that on the standard slope (9%) with constant values the other factors.

  14. USLE C-Factor • A = R K LS C P • C is the Cropping and management factor • C is a ratio of the erosion rate for the given condition to the erosion rate for the standard condition • The standard condition is a bare soil • All other conditions will have C<1 • C also depends on rainfall timing

  15. Crop and tillage factor (C) is define as the relation between the soil loss of land which a certain crop or rotation crop is grown and land that has laid fallow for at least two years, under the same circumstances.C-factor is determined mainly by cover rate, crop residues (mulch) and tillage.

  16. USLE C-Factor • Continuous Fallow 1.00 • Fresh Clean-Tilled Seedbed 0.80 • Corn at Full Canopy 0.25 • Established Thick Meadow 0.004 • Established Meadow Poor Cover 0.1 • Typical Rowcrop Annual Value 0.40

  17. Crop Residue C-factor

  18. USLE C-factors for CornSpring Plow (residue left) • Fallow (rough plow) 0.36 • SB to 10% cover 0.60 • To 50% cover 0.52 • To 75% cover 0.41 • To harvest (90% cover) 0.24 • Harvest to Plowing (RdL) 0.30 • Average 0.41

  19. CONSERVATION PRACTICE FACTOR: P • A = R K LS C P • P is the factor for supporting conservation practices. • The standard condition for P is direct up-and-down the slope cultivation. • P will be less than one for all other conditions. • P depends on field slope

  20. The erosion control factor (P) is based on tables of ratios for soil loss where the erosion control practice is applied to soil loss where it is not. To the most important erosion control measures belongs:- contour tillage,- contour strip cropping,- terracing, - vegetated waterways. The database on which the USLE is based was elaborated mainly for the USA conditions.

  21. CONSERVATION PRACTICE FACTOR: P • On nearly level land contouring has little effect, so the ratio is 1.0 • On very steep land contouring has little effect, so the ratio is 1.0 • The greatest effect of contouring on erosion is on slopes between 3 and 8 percent.

  22. Application of USLE- the estimation of the average annual soil losscaused by surface runoff for comparison with tolerance amount, - estimation of the reduction in soil loss as a result of the measures taken at the field level, - to enable planners to project limited erosion data to many locations and conditions not directly represented by research, - guide-lines for the planning of erosion control measures by use of digital models like AGNPS. .

  23. WEEP MODEL • WEPP (2004/700) hillslope/watershed model developed by • USDA – ARS, NESERL & Purdue University • is a process-based, distributed parameter, • continuous simulation, erosion prediction model • erosion prediction technology based on fundamentals of stochastic weather generation, infiltration theory, • hydrology, soil physics, plant • science, hydraulics and erosion mechanics

  24. Use of model AGNPS - casestudy Burzanka river

  25. R - rainfall erosivity index [ MJ ha –1mm h-1]Station Elbląg, period 1977-1997

  26. K - soil erodibility factor [t MJ-1year-1 ha–1 h mm-1]

  27. Conceptions of solution

  28. Evaluation of erosion’s threats and proposal of land use in Burzanka watershed

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