aagw2010 june 10 kibet stephen soil erosion prediction using rusle

Thursday, June 17, 2010 Kibet Stephen: Moi University//

E.R.M.I.S AFRICA NAKURU

AFRICA AGRICULTURE GIS WEEK2010

NAVIGATING THE CHANGE:

Taking a closer look at the role of spatial information and analysis in supporting

improved agricultural research and development



TOPIC:SOIL EROSION PREDICTION USING RUSLE(REVISED UNIVERSAL

SOIL LOSS EQUATION) INTEGRATEDWITH GIS

PRESENTER: KIBET STEPHENINSTITUTION: MOI UNIVERSITY

Attaché: environmental research mapping & information systems

(ERMIS) AfricaCLUSTER 3: UNDERSTANDING THE BASICS



OBJECTIVES OF THIS PRESENTATION

1. To explaining how variables in RUSLE can be obtained and analyzed using ArcGIS software

2. To show how the model can be applied in predicting soil erosion in Agricultural farms



Soil Erosion: A Great Concern

• Soil erosion is a major environmental threat to the sustainability and productive capacity of agriculture

• Soil erosion is a concern for farmers, development agencies, and governments throughout the world.

• Since the early 20th century, soil erosion, by wind and water, has been recognized as a major factor for decrease in both soil fertility and land value.



Erosion result to great Losses



Erosion can be destructive!!

• .



Effects of erosion on farms



Rates of soil erosionRates of erosion depends on several

factors:

• These include percent ground cover,

soil texture, soil structure, soil

porosity/permeability, and

topography/slope.

• Humans can influence the dynamics of

each of these and thus, improper

human land management can

accelerate rates of erosion



Soil erosion models

• Modeling soil erosion provides a

sophisticated tool for selection of

appropriate soil conservation practices.

• There are many soil erosion models,

including the European Soil Erosion Model

(EUROSEM), the Water Erosion Prediction

Project (WEPP), the Limberg Soil Erosion

Model (LISEM), and the Chemical Runoff and

Erosion from Agricultural Management

System (CREAMS) to name but a few.



The Revised Universal Soil Loss Equation (RUSLE)

• RUSLE is a revision of the Universal Soil Loss Equation (USLE), which was originally developed to predict erosion on croplands in the United States.

• With the revision, the equation can be employed in a variety of environments including rangeland, mine sites, agricultural lands, etc.

• The RUSLE is an empirical equation that predicts annual erosion (tons/acre/yr) resulting from sheet and rill erosion in croplands.



Advantages of RUSLEThe most extensively used model is the Revised

Universal Soil Loss Equation (RUSLE).

RUSLE model has advantages because

• Its data requirements are not too complex or unattainable,

• It is relatively easy to understand, and it is compatible with GIS

• RUSLE model can isolate locations of erosion on a cell by cell basis, determine the role of individual variables on the rate of erosion, and identify the spatial patterns of soil loss within a watershed



RUSLE EQUATIONA = R * K * L * S* C* P

• The RUSLE is factor-based, which means that a series of factors, each quantifying one or more processes and their interactions, are combined to yield an overall estimate of soil loss.

• A = Average annual soil loss (tons/acre) resulting from sheet and rill erosion.

• This is the predicted value resulting from the execution of the equation above.



R-RainfallRunoff erosivity factor

• This factor measures the effect of

rainfall on erosion.

• The R factor is a summation of the

various properties of rainfall including

intensity, duration, size etc.

• Rainfall erosivity can be mapped for

the entire country by using data from

local weather stations



Computing R-factor

• Load the R-factor.shp. Containing rainfall

measurements

• Add a new field labeled R_factor.

• Calculate the R-Value for the drainage

basin using Modified Fournier Index (MFI)

• MFI=Pi^2/p

• Where Pi is monthly rainfall yearly

averages (mm), P represent yearly

averages (mm)



Computing R-factor

• Enter this value in the new column of the R-factor table.

• Now convert the R-factor Shapefile to a Grid by highlighting on the R-factor shapefile in the table of contents and going to Spatial Analyst > Convert > feature to grid.

• Select R_factor for the field.

• Name your grid R_factor.



K-Soil Erodibility factor

• The soil erodibility factor measures the

resistance of the soil to detachment and

transportation by raindrop impact and surface

runoff.

• Soil erodibility is a function of the inherent soil

properties, including organic matter content,

particle size, permeability, etc.

• Because these properties vary within a given

soil, erodibility (K values) also varies.



K Factor DataTextural Class Average Less than 2 More than2%

Clay 0.22 0.24 0. 21

Clay Loam 0.30 0.33 0.28

Coarse Sandy Loam 0.07 -- 0.07

Fine Sand 0.08 0.09 0.06

Fine Sandy Loam 0.18 0.22 0.17

Heavy Clay 0.17 0.19 0.15

Loam 0.30 0.34 0.26

Loamy Fine Sand 0.11 0.15 0.09

Loamy Sand 0.04 0.05 0.04

Loamy Very Fine Sand0.39 0.44 0.25

Sand 0.02 0.03 0.01

Sandy Clay Loam 0.20 - 0.20

Sandy Loam 0.13 0.14 0.12

Silt Loam 0.38 0.41 0.37

Silty Clay 0.26 0.27 0.26

Silty Clay Loam 0.32 0.35 0.30

Very Fine Sand 0.43 0.46 0.37

Very Fine Sandy Loam 0.35 0.41 0.33

Source: www.omafra.gov.on.ca



Symbology of K-factor

• .



L and S Factors(slope length and slope

steepness factor)L= Slope length factor.

• This factor accounts for the effects of slope

length on the rate of erosion.

S = Slope steepness factor.

• This factor accounts for the effects of slope

angle on erosion rates.

• All things being equal, higher slope values

have greater erosion rates.



L and S Factors(slope length and slope steepness

factor)• LS can be computed using DEM (Digital

Elevation Model)

• DEM is then delineated beginning with

the drainage basin then the stream

• In order to compute LS factors you

require slope and flow accumulation

• This is then computed as follows



Digitital Elevation Model-DEM



Delineated drainage basin

• .



Catchment streams delineated

• .



Computing LS using DEM and GIS

• With DEM as our active theme we go to Spatial Analyst > Surface Analysis and use the Slope tool to calculate a slope surface for the area.

We shall name our result Area_slope .

• Next we need to derive the flow accumulation one of the inputs required to compute the RUSLE.

• The flow accumulation (Fac) was created when we delineated the Drainage Basin in Arc Hydro.

• This will give us the flow accumulation for the actual Drainage Basin.

• Name the new theme flowacc



Flow Accumulation feature

• .



Computed LS factors

• Lastly we have all the themes necessary

to generate the LS factor using the DEM.

• Using Raster calculator build the following

expression.

• 1.6 * Pow(([flowacc] * resolution) / 22.1, 0.6) *

Pow(Sin([area_slope] * 0.01745) / 0.09, 1.3

• The value for resolution used corresponds

to the cell size of the DEM.



C-Factorcover management factor

• C is the crop/vegetation and management

factor.

• It is used to determine the relative

effectiveness of soil and crop management

systems in terms of preventing soil loss.

• The C Factor can be determined by selecting

the crop type and tillage method that

corresponds to the field and then multiplying

these factors together.



Crop type factor

• Crop Type Factor

• Grain Corn 0.40

• Silage Corn, Beans & Canola 0.50

• Cereals 0.35

• Seasonal Horticultural Crops 0.50

• Fruit Trees 0.10

• Hay and Pasture 0.02



Tillage method factor

Tillage Method Factor

Fall Plow 1.0

Spring Plow 0.90

Mulch Tillage 0.60

Ridge Tillage 0.35

Zone Tillage 0.25

No-Till 0.25



C-Factorcover management factor

• The C-factor was derived from landuse/ land

cover types above.

• Load the C-factor.shp, examine the attribute

table, and change the symbology.

• Convert the C-factor shape file to a grid.

• C-factor as the attribute to use in generating

the grid.

• Name the new grid C_facgrid.



P-FACTOR (supporting practices)

Support Practice P Factor

Up & Down Slope 1.0

Cross Slope 0.75

Contour farming 0.50

Strip cropping, cross slope 0.37

Strip cropping, contour 0.25



P-FACTOR (supporting practices)

Load the P-factor.shp into GIS

Convert to grid following the procedure we

adopted in generating the C_facgrid.

Name the output P_facgrid.



Run the RUSLE equation

Now you have all the factors necessary for executing the RUSLE.

Use the map calculator to simply execute the following expression:

• ([ R-factor]*[LS]*[K-factor]*[C-facgrid]*[P-facgrid])

The result is Soil loss.

• This is the annual soil loss (tons/acre) for the given drainage basin.



Raster Calculator calculating ‘a’



Soil loss tolerance Rates

Soil Erosion Class Potential Soil Loss

(tons/acre/year)

Very Low (tolerable) <3

Low 3 – 5

Moderate 5 – 10

High 10 – 15

Severe >15



Management strategies to reduce soil loss

Factor Management strategies

R The R Factor for a field cannot be altered

K The K Factor for a field cannot be altered.

LS Terraces may be constructed to reduce the slope length resulting in lower soil losses.

C The selection of crop types and tillage methods that result in the lowest possible C factor will result in less soil erosion.

P The selection of a support practice that has the lowest possible factor associated with it will result in lower soil losses.



Conclusion

• The presentation is just an overview of how erosion can be computed

• Since it is a model with several variables, it requires sufficient time to understand how to derive the variables and apply.

• In addition it has got its limitation like other models.

• Indeed it is possible to compute and predict erosion in a give area using RUSLE together with GIS.



Remarks from the Audience

Thanks and God Bless.

aagw2010 june 10 kibet stephen soil erosion prediction using rusle

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