Transcript Quantifying the impact of soil erosion

QUANTIFYING THE
IMPACT OF SOIL
EROSION
Nesrin Negm
Helene Pühringer
OVERVIEW
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Introduction
Objectives
 General description of the problem
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Models and Methods
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USLE
RUSLE
SEMMED
INRA
PESERA
Difficulties
 Conclusion
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INTRODUCTION
Growing importance of soil erosion
 Actions taken to prevent future hazardous events
 Overall objective of quantification of soil erosion:
Prevention of soil erosion and its impacts
 Necessity of quantifying impacts:
policy makers
laws on a scientific and measurable basis
Comparison
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INTRODUCTION
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Soil erosion:
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Is a natural process that determines soil formation
Accelerated by human activities
Caused by inappropriate agricultural practices,
deforestation, overgrazing and construction activities
Natural: by wind and water
Runoff plays the biggest role
Irreversible degradation of soil
leads to loss of nutrients and organic matter
negative impact on water holding capacity and soil
structure
Development of models to quantify impacts
ACTUAL SOIL EROSION RISK IN EUROPE, (SOURCE: GRIMM ET AL., 2001)
MODELS AND METHODS
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For development of models differentiation between expert
based and model based methods
Expert based: Qualitative appraoch
 Eg: RIVM soil erosion model, CORINE programme,
GLASOD (Global Assessment of Soil Degradation), Hot
Spots map commissioned by the EEA
Model based: Quantitative approach
 USLE (Unversal soil loss equation)
 RUSLE (Revised USLE)
 SEMMED (Soil erosion model for mediterranean
regions)
 INRA (Institute national de la recherche agronomique)
 PESERA (Pan European soil erosion risk assessment)
USLE
UNIVERSAL SOIL LOSS EQUATION
Empirical model based on regression analysis
 Most used due to low data demand and simple
and robust application
 Standardised approach
 Used at many different scales
 Originally developed for long term erosion on
agricultural field
 Production of first European map of quantitative
rill and sheet erosion
 not suitable for the prediction of the occurrence of
mass movements like landslides
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USLE
UNIVERSAL SOIL LOSS EQUATION
A = R ⋅ K ⋅ L ⋅ S ⋅C [t ha-1 a-1]
Where:
A : Mean (annual) soil loss
R : Rainfall erosivity factor
K : Soil erodibility factor
L : Slope factor
S : Slope length factor
C : Cover management factor
USLE
UNIVERSAL SOIL LOSS EQUATION
Rainfall erosivity factor R:
 Intensity of rainfall
 Relation between rainfall energy E and a
maximum of 30 Minutes rainfall intensity I30
 data are mostly not available at standard
meteorological stations
 another estimation for R had to be found
 best way: use correlation between readily
available meteorological parameters and the R
factor
USLE
UNIVERSAL SOIL LOSS EQUATION
Rainfall erosivity factor R:
 For Germany/ representative for northernEuropean conditions (Rogler & Schwertmann)
R= 10 *(-1.48 + 1.48 *Ns)
 Where :
R : Mean annual erosivity (MJ.mm.ha-1 h-1 y-1)
Ns : Mean rainfall amount in summer (MayOctober) (mm)
 For Italy/representative for southern Europe
conditions (Zanchi)
R = α *P
P: Annual rainfall (mm)
α:1.1-1.5
USLE
UNIVERSAL SOIL LOSS EQUATION
Rainfall erosivity factor R:
 Approaches give only an overview of patterns of
erosion risk
 very simplified
 not suitable for a detailed quantitative analysis
USLE
UNIVERSAL SOIL LOSS EQUATION
Soil erodibility factor K:
 Rate of soil loss per unit of R
 widely used in several soil erosion models
 determined by the use of runoff plots
 unreliable results are produced when applied to
soils with textural extremes (European
conditions)
USLE
UNIVERSAL SOIL LOSS EQUATION
Soil erodibility factor K:
With:
K : Soil erodibility factor (t ha h ha‐1 MJ‐1 mm‐1)
Dg : Geometric mean weight diameter of the
primary soil particles (mm)
USLE
UNIVERSAL SOIL LOSS EQUATION
Slope and Slope Length Factor S&L:
 accounts for the effect of topography on soil
erosion
 based on the angle of the slope
Where:
As : Specific contributing area (m2/m)
β : Slope angle (degrees)
USLE
UNIVERSAL SOIL LOSS EQUATION
Cover Management Factor C
 percentage of vegetation cover and growth stage
 effect of mulch cover, crop residues and tillage
operations influence C
 defined as the ratio of soil loss from land cropped
under certain conditions to the loss from
continuous fallow
 NOAA AVHRR (‘Advanced Very High Resolution
Radiometer) used to determine approximate Cfactor values
USLE
UNIVERSAL SOIL LOSS EQUATION
due to the small scale used, almost impossible to
assess the effect of management practices (one of
most important factors for erosion)
 Improvements:
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Using a more detailed digital elevation model
 Better illustration of rainfall erosivity
 Satellite data with better spectral and geometric
properties for estimating the vegetation cover
 More detailed soil data (soil depth, stone volume,
surface texture)
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RUSLE
REVISED USLE
Improved version of USLE
 revised determining factors are as following:
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some new and revised maps
a time‐varying approach for soil erodibility factor
a new equation to reflect slope length and steepness
a new conservation‐practice values
a subfactor approach for evaluating the
cover‐management factor
SEMMED MODEL
SOIL EROSION MODEL FOR MEDITERRANEAN
REGIONS
Input variables used in this model based on
standard meteorological data, soil maps,
multitemporal, satellite imagery, digital
elevation models and a limited amount of field
data
 allows assessement of erosion risks over large
and spatially diverse areas
 Application of this model makes extensive field
surveys redundant
 By now applied for producing regional erosion
risk maps of parts of southern France
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INRA
INSTITUTE NATIONAL DE LA RECHERCHE
AGRONOMIQUE
mid-step in the direction of a “state of the art
erosion modelling at the European scale”
following USLE & before the introduction of the
PESERA project
 Using empirical rules
 combining data on land use, vulnerability
towards soil crusting, soil erodibility, relief and
meteorological data
 Units for presentation of results:
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Administrative units (EC nuts regions)
 Watershed catchment units
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INRA
INSTITUTE NATIONAL DE LA RECHERCHE
AGRONOMIQUE
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Objectives:
developing and applying a methodology that is
grounded on current knowledge and available data
for assessing soil erosion risk at European level
 Assessing mean seasonal erosion risk at the regional
scale
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Assumption
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Key factors influencing runoff and erosion risk:
Land cover
 Crust formation
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Soil Erosion due to surface runoff, moves soil
downslope
INRA
INSTITUTE NATIONAL DE LA RECHERCHE
AGRONOMIQUE
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Outcome:
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Single homogeneous map of erosion risk at European
scale
Allows comparison between regions
Depending on land use, different types of erosion are
considered
Seasonal maps can be producedshow efffect of
seasonality on erosion
Possibility to adjust results to various user needs
Model is easy to alter
Possibility of using heterogeneous data resolution
and quality
PESERA
PAN EUROPEAN SOIL EROSION RISK ASSESSMENT
First main objective:
 developing and calibrating a process-based and
spatially distributed model in order to quantify
soil erosion by water and in a further step assess
its risk in Europe
 It’s planned to include estimates of tillage and
wind erosion
PESERA
PAN EUROPEAN SOIL EROSION RISK ASSESSMENT
Second main objective:
 validation of the model’s development at low and
high resolutions and through diverse agroecological zones, comparing the model’s output
with other methods or models in the field of
erosion risk assessment
 Demonstration of the model’s performance with
different data input and at different resolutions
provides information on its robustness and
flexibility
PESERA
PAN EUROPEAN SOIL EROSION RISK ASSESSMENT
Third main objective:
 ensuring the relevance of the model for policymakers
 Establishment of a strong expert and end-user
network across Europe important for enabling
further developments
PESERA
PAN EUROPEAN SOIL EROSION RISK ASSESSMENT
At european scale, necessary to develop an
effective tool for erosion risk assessment and to
offer it as a part of decision support systems for
exploring the implications of policy options
 Assessing the impact of the physical loss of soil is
a high importance for policy making
 The model sticks tight to hydrological models,
takes spatial distribution patterns of sediment
loss into account
 By a sediment transport equation (with terms for
topography, overland flow runoff and soil
erodibility) erosion rates in individual storms can
be estimated
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DIFFICULTIES
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Quantitative models show problems at regional or
larger scale
Models developed on a smaller scale (plot or field)
 intended for generating point estimates of soil loss
 Example: USLE developed for prediction of rill- and
inter-rill erosion not appropriate for areas that are
affected by gully erosion or mass movements like
landslides and rockfalls
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On regional scale downscaling to field scale is
almost impossible results in parameter values
that are more inexact than field survey
 Result of model is rather a broad overview of the
pattern of the relative differences than accurate
erosion rates at individual points
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CONCLUSION
Still questionable how good the conversion of
vulnerability of land use systems and its
corresponding degradation by erosion into
information is, which is available for policy
maker works, so that they can develop a suitable
mitigation strategy
 There has already been big step done towards an
appropriate soil erosion prevention in Europe but
there is still a lot to improve
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Thank you for your attention!