1. DefinitionDefinition ofof land desertificationland desertification
risk by using simple indicatorsrisk by using simple indicators
Christos Karavitis Costas Kosmas
Orestis Kairis Vassileia Fassouli
Mina Karamesouti Kate Kounalaki
Agricultural University of Athens

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ContributorsContributors
1.Celeste de Oliveira Alves Coelho, João Soares, Sandra Valente: University of Aveiro, Portugal.
2.Dino Torri, Fabrizio Ungaro, Francesca Santaloia, Maurizio Polemio, Piernicola Lollino: Research
Institute for Hydrogeological Protection – CNR, Italy.
3.Faruk Ocakoglu, Candan Gokceoglu, Harun Sonmez, Levent Tezcan, Halil Gungor, Sanem
Ac.kalin: Eskisehir Osmangazi University-EOU, Turkey.
4.Abdellah Laouina, Miloud Chaker: University of Mohamed V, Chair UNESCO-GN, Morocco.
5.Mohamed Ouessar, Houcine Khatteli, Mongi Sghaier, Houcine Taamallah, Azaiez Ouled
Belgacem: Institut des Regions Arides-IRA, Tunisia.
6.Li Rui, Yang Qinke, Jiao Juying, Wang Fei, Wen Zhonging, Jiao Feng: Institute of Soil and Water
Conservation-ISWC, China.
7.Ioannis Diamantis, Fotios Pliakas, Apostolos Ziogas: Democritus University of Thrace-DUTH,
Greece.
8.Albert Sole Benet, Francisco Domingo, Ana Rey, Emiliano Pegoraro, Jesus Fernandez: Estacion
Experimental de Zonas Aridas, EEZACSIC, Spain.

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9. Antonio Ferreira, Pedro Morais, Marta Lopes: Escola Superior Agraria de Gois-ESAC,
Portugal
10. Raban Chanda, Michael B.K. Darkoh, Lapo Magole, Julius R. Atlhopheng, Jeremy Perkins,
Kutlwano Mulale, Reuben Sebego: University of Botswana-UB, Botswana.
11. Anatoly M. Zeiliguer, Marya L. Sizemskaya, Nikolay B. Khitrov, Vladimir A. Romanenkov,
Olga S. Ermolaeva: Moscow State University of Environmental Engineering-MSUEE,
Russia.
12. Carlos Ovalle, Alejandro del Pozo, Erick Zagal, Cladio Perez, Juan A. Barrera, Jorge
Riquelme, Fernando Fernandez: Instituto de Investigaciones Agropecuarias-INIA, Chile.
13. Jorge Mendes Brito, Nora Helena Ramos Silva, Paulo Jorge Alfama: National Institut for
Agriculture Research and Development-INIDA, Cape Verde.
14. Christian Prat, Maria Alcalá, Lenin Medina, Adriana Ramos, José Juan Ramos, Manuel
Mendoza, Daniel Gonzalez: Institut de Recherche pour le Développement-IRD, Mexico.
Contributors (continued)Contributors (continued)

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Methodology usedMethodology used
17 study sites were selected located in:
1. Rendina Basin Basilicata - Italy
• Nestos Basin Maggana - Greece
• Crete - Greece
• Mação - Portugal
• Gois - Portugal
• Guadalentin Basin Murcia - Spain
• Konya Karapinar plain - Turkey
• Eskisehir Plain - Turkey
• Novij Saratov - Russia
• Djanybek - Russia
• Zeuss Koutine - Tunisia
• Boteti Area - Botswana
• Santiago Island - Cape Verde
• Mamora Sehoul - Morocco
• Loess Plateau - China
• Secano Interior - Chile
• Cointzio catchment - Mexico.

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MethodologyMethodology usedused
The following processes or causes were identified as
affecting land desertification in the study sites:
Soil erosion
Soil salinization
Water stress
Overgrazing
Forest fires

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Methodology usedMethodology used
A list of 72 candidate indicators has been identified using the
following sources:
United Nations Committees for Combating Desertification
(UNCCD) – National Action Plans
European Environmental Agency (EEA) - DPSIR (Driving forces,
Pressure, State, Impact, Responses indicators)
MEDALUS projects - Mediterranean Desertification and Land Use
MEDRAP – Mediterranean Desertification Regional Action Plan
DESERTLINKS – DIS4ME
Local stakeholders

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Each indicator has been described using existing classes based
on existing classification systems and research results.
Weighing indices have been assigned in each class.
Methodology usedMethodology used
CLIMATE
<12 12-15 15-18 18-21 >21Annual air
Temperature (o
C) 1.0 1.2 1.5 1.8 2.0
<280 280-650 650 -1000 >1000Annual rainfall
(mm) 4 2 1.5 1.0
<50 50-75 75-100 100-125 125-150 >150BG aridity
index 1.0 1.2 1.4 1.6 1.8 2.0
<500 500-800 800-1200 1200-1500 >1500Annual pot.
evapotranspiration
(mm)
1.0 1.2 1.5 1.8 2.0
<0.19 0.20-0.39 0.40-0.59 0.60-0.79 0.80-0.99 1.00-1.19 >1.20Rain seasonality
1.0 1.2 1.4 1.6 1.8 1.9 2.0
<60 60 -90 91-120 121-160 >160Rain erosivity
(mm/h) 1.0 1.2 1.5 1.8 2.0
WATER
<400 400-800 800-1500 >1500Water quality
( μS) 1.0 1.3 1.6 2.0
Adequate Moderate Low NoneWater quantity
1.0 1.3 1.6 2.0

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Questionnaires have been prepared
including all the indicators
corresponding to the identified
processes or causes.
A manual for describing indicators
has been prepared for conducting field
survey and collecting data.
A harmonized data basis has been
developed including information from
1641 field sites.
Methodology used
Field site

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Methodology usedMethodology used
A forward stepwise multiple regression analysis was applied
for each process or cause with dependent variable the
desertification risk and independent variables all the
indicators assigned for each process using the following
linear model:
Υ = β0 + β1Χ1 + β2Χ2 + ………….
+ βκΧκ.
Where: Y is the dependent variable of desertification risk,
β0 is the Υ intercept
β1, β2, etc. are slopes of the regression plane,
X1, X2, etc. are the independent variables of indicators
used.

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Type of
environmentally
sensitive area
Degree of soil erosion Desertification
risk
Assigned
weighing indices
Critical Very severe, severe Very high 5
Moderate, slight High 4
no erosion moderate 3
Fragile Very severe High 4
Severe, moderate Moderate 3
Slight, no erosion Low 2
Potential Very severe, severe Moderate 3
Moderate, Low 2
Slight, no erosion No risk 1
Non-threatened Very severe, severe,
moderate
Low 2
Slight, no erosion No risk 1
Methodology usedMethodology used
Definition of desertification risk for the degradation processes:
(a) water erosion, (b) tillage erosion, (c) forest fires, (d) overgrazing

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Distribution of data collected for the various processes and
causes with the corresponding land uses, and distribution in
the study sites
Degradation
process
Land use Study
sites
Field sites Number of
indicators
used
Soil erosion Agriculture 9 477 49
Pasture 8 244 49
Forests 6 85 49
Soil
salinization
Agriculture,
natural vegetation
5 258 27
Water stress Agriculture,
natural vegetation
5 258 50
Overgrazing Natural
vegetation,
agriculture
6 265 44
Forest fires Natural vegetation 4 85 29
Methodology used

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Results obtainedResults obtained
Assessing desertification risk due to water erosion in cropland
Analyzed candidate indicators: 49
Important indicators: 17

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Results obtainedResults obtained
Assessing desertification risk due to water erosion in
pastures
Analyzed candidate indicators: 49
Important indicators: 15

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Assessing desertification risk due to water erosion in forests
Analyzed candidate indicators: 49
Important indicators: 10
Results obtainedResults obtained

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Assessing desertification risk due to tillage erosion
Analyzed candidate indicators: 17
Important indicators: 10
Results obtainedResults obtained

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Assessing desertification risk due to soil salinization
Analyzed candidate indicators: 27
Important indicators: 9
Results obtainedResults obtained

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Assessing desertification risk due to water stress
Analyzed candidate indicators: 50
Important indicators: 12
Results obtainedResults obtained

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Assessing desertification risk due to overgrazing
Analyzed candidate indicators: 44
Important indicators: 12
Results obtainedResults obtained

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Assessing desertification risk due to forest fires
Analyzed candidate indicators: 29
Important indicators: 8
Results obtainedResults obtained

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Input data for selected landInput data for selected land
degradation processdegradation process

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Output data for selected landOutput data for selected land
degradation processdegradation process

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Main ConclusionsMain Conclusions
The analysis of the data has shown that a short list of indicators
ranging from 8 to 17 may be used to assess land desertification
risk.
The comparative analysis has shown that indicators may be
used world wide for assessing desertification risk.
The derived methodology may be used to assess the efficiency
and efficacy of different land management practices and
degradation monitoring techniques for combating
desertification at farm level and given the pertinent information
at even regional level.
The derived system of indicators may enable land users to test
different scenarios for ecosystem vulnerability in order to
assess critical stress factors and their impacts on
desertification.

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THANK YOU!THANK YOU!