How to Use ArcGIS Pro to Estimate Soil Erosion from a Catchment Basin

Jeff Oppong

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Soil erosion is the wearing away of the topsoil of a part of the surface of the earth. Soil erosion is mainly influenced by floods, rainwater, winds, ice, humans, animals, and plants, among many others.

As urbanization increased and agricultural practices intensified, soil erosion has become prevalent over the years. As a result, several environmental effects became a consequence. However, public officials, individuals, and organization agencies have contributed their quota to anti-soil erosion mechanics by implementing policies that will sustain Agriculture and the environment. 

Using GIS to Calculate Soil Erosion

This tutorial contributes to the many anti-soil erosion mechanisms by using spatial data science and Remote Sensing techniques to estimate soil erosion from a catchment in ArcGIS Pro by the Universal Soil Loss Equation (USLE).

Factors that are utilized in this tutorial were derived from the Universal Soil Loss Equation; rainfall, soil type, slope, flow accumulation from Digital Elevation Model (DEM), Land Cover, and Land management.

The figure below shows a summary of the methodological flow of the several geospatial tools employed in the study.

A black and white diagram showing the process to estimate soil erosion using a GIS software package.
Figure 1: A summary of methodological flow employed in estimating soil erosion from a catchment in ArcGIS Pro. Figure: Jeff Oppong.

Estimation of Rainfall Runoff Factor (R) in ArcGIS Pro

The Universal Soil Loss Equation (USLE) for estimation of soil erosion from a catchment is given by:

A = R*K*(LS)*C*P

Where 

A = Average annual soil loss (ton/ha/yr)

R = Rainfall Runoff Factor for soil erosion (MJ mm ha-1 hr-1 yr-1)

K = Soil erodibility factor (ton ha hr MJ-1 ha-1 mm-1)

LS = Topographic Steepness factor (based on length and slope)

C = Land Cover Management factor

P = Erosion control practice factor 

Mean annual rainfall data can be accessed from cru data’s website (CRU TS v4.05 Data Variables: PRE (uea.ac.uk)). For more information on accessing and processing mean annual rainfall data, use the link Rainfall data: NetCDF file to interpolation for whole world with map layout – YouTube).

Where the rainfall data is in point feature, the following method should be used for interpolation (kriging):

  1. Open and create a new project in ArcGIS Pro.
  2. From the search bar of the geoprocessing toolbox, type and search “kriging.”
  3. Set “input point features” to the rainfall data.
  4. Set “Z value” field to rainfall column of the data.
  5. Set “output cell size” to 30 and set “output surface raster” to P.
  6. Click Run. 
Screenshots showing how to search for kiriging and the kriging GUI in ArcGIS Pro.
Figure 2: Interpolation (Kriging) in ArcGIS Pro. Image: Jeff Oppong.

Given the mean annual rainfall from 5 stations, R can be calculated using the formula (Wischmeier and Smith, 1978);

R = 0.5*P*1.73

To calculate “R,” use the steps outlined below;

  1. Type and search raster calculator from the search bar of the geoprocessing toolbox.
  2. From the search bar of the raster calculator, type the formulation as shown below:
Screenshot of the raster calculator in ArcGIS Pro.
Figure 3: Calculation of “R” in ArcGIS Pro. Image: Jeff Oppong.

Estimation of Soil Erodibility Factor (K) in ArcGIS Pro

Global soil data can be accessed freely from FAO soil’s website (FAO Map Catalog).

The soil data from FAO can be imported and processed in ArcGIS Pro using the steps below:

Screenshot highlighting the "add data" button in the menu bar in ArcGIS Pro.
  1. From the insert tab, click the “Add data” icon. 
  2. Search and import soil data onto the map canvas using the “open” button.

    To clip the soil data to a specific catchment area of interest:
  3. Type and search “extract by mask,” using the search bar of the geoprocessing toolbox.
  4. Set “input raster” to the soil data.
  5. Set “feature mask” to the shapefile of the specified Area of Interest. 
  6. Set “output raster” to the desired output location and save output name as “K.”
  7. Click Run.
Screenshot showing the "Extract by Mask" GUI in ArcGIS Pro.
Figure 4: “Extract by Mask” in ArcGIS Pro. Image: Jeff Oppong.

Estimation of Topographic Steep Factor (LS) in ArcGIS Pro

Digital Elevation Model (DEM) can be accessed freely from the USGS Earth Explorer’s website after registration (EarthExplorer (usgs.gov)). After, DEM should be imported onto the ArcGIS Pro map canvas using the “Add data” tool.  

To derive flow accumulation from DEM in ArcGIS Pro, use the processes outlined below;

  1. Type and search “fill” from the search bar of the geoprocessing toolbox.
  2. From the fill menu, set “input surface raster” to DEM.
  3. Set “output surface raster” to the desired output name and location.
  4. Click Run.
  5. Type and search “flow direction” from the search bar of the geoprocessing toolbox.
  6. From the flow direction menu, set “input surface raster” to results of fill_DEM.
  7. Set “output flow direction raster” to the desired output name and location.
  8. Click Run.
  9. Type and search “flow accumulation” from the search bar of the geoprocessing tookbox.
  10. From the flow accumulation menu, set “input flow direction raster” to flow direction_DEM.
  11. Set “output accumulation raster” to the desired output name and location. 
  12. Click Run.
Screenshot showing the ArcGIS GUIs for flow direction (left) and flow accumulation (right).
Figure 5: “flow direction” and “flow accumulation” in ArcGIS Pro. Images: Jeff Oppong.

According to (Moore & Burch, 1986), slope and length of the slope of a catchment can be computed using the formulation below:

Image showing the calculation for flow accumulation.

For this tutorial, Land Slope (LS) is calculated by finding the product of LS1 and LS2.

  1. To calculate LS1, type and search raster calculator from the search bar.
  2. Type the formulation as shown in figure 6 below.
Screenshot showing the raster calculator in ArcGIS Pro with the "LS1" calculation.
Figure 6: “LS1” calculation in ArcGIS Pro. Image: Jeff Oppong.

However, cell value as highlighted in figure 6 of flow_accumulation raster can be derived from raster information bar of properties menu. 

  1. To calculate LS2, type the formulation as shown in figure 7 below.
Screenshot showing the raster calculator to calculated L2 in ArcGIS Pro.
Figure 7: “LS2” calculation in ArcGIS Pro. Image: Jeff Oppong.
  1. To calculate LS, type the formulation as shown in figure 8 below.
Screenshot showing the raster calculator in ArcGIS with the equation L1+L2.
Figure 8: “LS” calculation in ArcGIS Pro. Image: Jeff Oppong.

Estimation of Crop Management Factor (C) and Average Annual Soil Loss (a) in ArcGIS Pro

Landsat 7 imagery can be accessed freely from the USGS Earth Explorer’s website. 

Bands 3 and 4 are used to calculate NDVI. For more information on how to calculate NDVI from Landsat 7 imagery, see the link attached (Calculating NDVI in ArcGIS using Landsat 7 satellite image – YouTube).

  1. From the search bar of the raster calculator, type the formulation as shown in figure 9 below (Van der Knijff et. al., 1999).
Screenshot showing the raster calculator in ArcGIS pro to calculate the estimation of crop factor.
Figure 9: Calculation of “C” in ArcGIS Pro.

Due to lack of spatial distributed data for P factor, P can be set as 0.8 for the entire catchment. 

To estimate soil erosion from the catchment area of interest, use the formulation as shown in figure 10 below.

Screenshot of the raster calculator in ArcGIS Pro with a calculation for estimating soil erosion.
Figure 10:” A” calculation in ArcGIS Pro. Image: Jeff Oppong.

The output raster of annual soil loss:

Screenshot showing the annual average soil loss layer in ArcGIS Pro.
Figure 11: Average annual soil loss of Akuapem South District in Ghana. Image: Jeff Oppong.

Read next: How to Use ArcGIS Pro to Assess Landslide Susceptibility

References

Moore, I. D., & Burch, G. J. (1986). Modelling erosion and deposition: topographic effects. Transactions of the American Society of Agricultural Engineers29(6), 1624–1630. https://doi.org/10.13031/2013.30363

Van der Knijff, J.M., Jones, R.J.A. and Montanarella, L. (1999) Soil Erosion Risk in Italy. EUR19022 EN, Office for Official Publications of the European Communities, Luxembourg, 54.

Wischmeier, W.H. and Smith, D.D. (1978) Predicting Rainfall Erosion Losses. A Guide to Conservation Planning. The USDA Agricultural Handbook No. 537, Maryland.

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About the author
Jeff Oppong
Jeff Oppong holds a BSc in Geomatic Engineering and currently a graduate student at Hohai University in China, where he's studying MSc. Harbor, Coastal, and Offshore Engineering. Jeff is a prolific researcher and a GIS/Remote sensing expert who aspires to be a change-agent and a renowned Engineer. Jeff Oppong can be contacted via email

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