Using fuzzy set theory to address the uncertainty of susceptibility to drought

This paper presents the technical aspects of a new methodology for assessing the susceptibility of society to drought. The methodology consists of a combination of inference modelling and fuzzy logic applications. Four steps are followed: (1) model input variables are selected—these variables reflect the main factors influencing susceptibility in a social group, population or region, (2) fuzzification—the uncertainties of the input variables are made explicit by representing them as ‘fuzzy membership functions’, (3) inference modelling—the input variables are used to construct a model made up of linguistic rules, and (4) defuzzification—results from the model in linguistic form are translated into numerical form, also through the use of fuzzy membership functions. The disadvantages and advantages of this methodology became apparent when it was applied to the assessment of susceptibility from three disciplinary perspectives: Disadvantages include the difficulty in validating results and the subjectivity involved with specifying fuzzy membership functions and the rules of the inference model. Advantages of the methodology are its transparency, because all model assumptions have to be made explicit in the form of inference rules; its flexibility, in that informal and expert knowledge can be incorporated through ‘fuzzy membership functions’ and through the rules in the inference model; and its versatility, since numerical data can be converted to linguistic statements and vice versa through the procedures of ‘fuzzification’ and ‘defuzzification’.     

A new approach to quantifying and comparing vulnerability to drought

In this study we develop an “inference modeling” approach to compare and analyze how different disciplines (economics, political science, and behavioral science/environmental psychology) estimate vulnerability to drought. It is thought that a better understanding of these differences can lead to a synthesis of insights from the different disciplines and eventually to more comprehensive assessments of vulnerability. The new methodology consists of (1) developing inference models whose variables and assertions incorporate qualitative knowledge about vulnerability, (2) converting qualitative model variables into quantitative indicators by using fuzzy set theory, (3) collecting data on the values of the indicators from case study regions, (4) inputting the regional data to the models and computing quantitative values for susceptibility. The methodology was applied to three case study regions (in India, Portugal and Russia) having a range of socio-economic and water stress conditions. In some cases the estimates of susceptibility were surprisingly similar, in others not, depending on the factors included in the disciplinary models and their relative weights. A new approach was also taken to testing vulnerability parameters by comparing estimated water stress against a data set of drought occurrences based on media analysis. The new methodologies developed in this paper provide a consistent basis for comparing differences between disciplinary perspectives, and for identifying the importance of the differences.

Application of fuzzy models to assess susceptibility to droughts from a socio-economic perspective

By combining the concepts of environmental stress, state susceptibility and environmental crisis, “Security Diagram” (SD) provides a quantitative approach to assessing environmental change and human security. The SD is a tool that clearly presents in a diagram the security situation of a population or region affected by a particular environmental crisis. Its underlying concept emphasises that the higher the level of environmental stress and socio-economic susceptibility, the higher the probability of the occurrence of crisis. Focusing on drought, this study analyses the susceptibility of case study regions in India, Portugal, and Russia from a socio-economic perspective. A conceptual framework of socio-economic susceptibility is developed based on the economic development theories of modernisation and dependency. Fuzzy set theory is used to generate susceptibility indices from a range of national and sub-national indicators, including financial resources, agricultural dependency and infrastructure development (for economic susceptibility), and health condition, educational attainment and gender inequality (for social susceptibility). Results indicate that socio-economic susceptibility over the period 1980–1995 was highest in India, followed by Russia and (since 1989) lowest in Portugal. Globalisation is likely to contribute to changes in the level of socio-economic susceptibility over time. Moreover, specific social and economic structures unique in each country (e.g., the role of women in society in India, the socialist legacy in Russia) may explain differences in susceptibility between the case study regions.

To produce or not to produce: an analysis of bioenergy and crop production decisions based on farmer typologies in Brandenburg,Germany

Regional Environmental Change - The future course of the political regulation of bioenergy will have a significant sustainability impact on many levels. Understanding the specific effects of...     

Mobilisation capacity for agri-environmental management

The integration of environmental concerns into agricultural policies - through agri-environment measures (AEM) - has seen a fast development across Europe. This paper conceives AEM as an evolving instrument, a product that takes shape, gets diffused and taken up in, by and through networks of relations. Success then depends on the mobilisation or active participation of all those who may support and develop it. Using the examples of the Flanders' and Walloon regions of Belgium, the paper sets out to examine the mechanisms by which mobilisation for agri-environmental management develops, and by doing so, to gain a better understanding of mobilisation capacity as a concept to be used for evaluating policy implementation in this area. The study follows AEM along the various trajectories of implementation (design, distribution, application). The findings reveal how mobilisation capacity is gradually built-up by the interplay between AEM and the networks it connects to. The case illustrates well how such interactions occur all the way from administration offices to farmers' fields, and that their nature can be very different (e.g., formal and informal, durable and short-lived, expected and unexpected). It is concluded that in evaluating actor-networks, one should look at them in an open and fluid manner, that is, not to privilege any particular configuration or form of attachment over the other, not take intentions and objectives as a starting point but instead address the opportunities for synergies, and be aware that any network built around the instrument may change its content and the way it functions.