Desertification and land degradation: origins, processes and solutions

Table of Contents

1. Authors and acknowledgements
2. Introduction
   1. Aims
   2. Definitions and key concepts
   3. Synthesis of previous and ongoing projects
   4. Key issues and outline
3. Evolution of desertification in the Mediterranean
   1. Climatic fluctuation
   2. Human influence
4. Primary drivers of desertification
   1. Biophysical and socio-economic causes
   2. Pathways of desertification
   3. Driving forces in the Mediterranean
   4. Synthesis of causes for DESIRE hotspots
   5. Conclusions
5. Processes and consequences of desertification in the Mediterranean
   1. Socio-economic and political factors
   2. Biophysical processes
   3. Conclusions
6. Indicators: monitoring desertification
   1. History of monitoring
   2. Indicators
   3. Monitoring and mapping techniques
   4. Concluding remarks
7. Modelling desertification
   1. Definition of modelling
   2. Model types
   3. Biophysical modelling
   4. Socio-economic and participatory modelling
   5. Gaps and progression in modelling
8. Solutions
   1. Biophysical solutions
   2. Political and socio-economic solutions
9. References

Definition of modelling

A model is a representation containing the essential structure of some object or event in the real world. Mulligan (2004) gives a review of research, funded by the EU, into modelling desertification. He states that to produce a model is to produce a simplification of reality. The purpose of a model is to formalise understanding gained through data collection or theoretical advance and to explore the properties of that understanding (Mulligan, 2004). However, this describes models that aim at understanding a (complex) system. Other models exist that are more practical and aim to be eventually applied by policy- or decision-makers. Three types of models are distinguished: conceptual, physical and mathematical models. The latter are often divided in empirical and physically-based. In scientific research, models are used as a tool for simplifying, formalising and testing theories as well as for implementing predictions of scenarios for future changes. They can be a means of understanding the system, testing of hypotheses and prediction and scenario development (Mulligan, 2004).

Process of Modelling

Mathematical modelling is the use of mathematical language to describe the behaviour of a system. The following stages are involved in the modelling process (Mulligan, 2004):

1. Model development
2. Parameterisation
3. Calibration
4. Verification and validation
5. Sensitivity analysis
6. Simulation and scenarios
7. Application

The process of verification and validation, while being one of the most important, is often neglected. Sensitivity analysis can assist in the understanding of the sensitivity of the real system and indicate which parameters are important and which are not. Eventually, a well understood, calibrated and validated model can be applied as a tool for (a) understanding the controls on some past change through comparison of modelled versus measured data, (b) simulation of future scenarios of change or (c) application to 'what if' type scenarios (Mulligan, 2004).