Thursday, June 17, 2010 Kibet Stephen: Moi University// E.R.M.I.S AFRICA NAKURU AFRICA AGRICULTURE GIS WEEK 2010 NAVIGATING THE CHANGE: Taking a closer look at the role of spatial information and analysis in supporting improved agricultural research and development
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Aagw2010 June 10 Kibet Stephen Soil Erosion Prediction Using Rusle
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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
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
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
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
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
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
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.
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
Erosion result to great Losses
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
Erosion can be destructive!!
• .
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
Effects of erosion on farms
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
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
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
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.
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
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.
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
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
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
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.
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
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
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
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)
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
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.
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
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.
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
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
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
Symbology of K-factor
• .
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
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.
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
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
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
Digitital Elevation Model-DEM
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
Delineated drainage basin
• .
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
Catchment streams delineated
• .
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
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
Thursday, June 17, 2010 Kibet Stephen: Moi University//
E.R.M.I.S AFRICA NAKURU
Flow Accumulation feature
• .
Thursday, June 17, 2010 Kibet Stephen: Moi University//