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6. WAVES Project

PIK Report No. 27

6. WAVES Project

6.1 Goals of the project

The basic goal of the WAVES project (Water Availability, Vulnerability of Ecosystems and Society in Northeastern Brazil), as stated in the project's Framework Concept, is to understand the regional interactions between water availability, ecosystems and human systems and to build up integrated models as an additional tool for developing strategies to make these regions less vulnerable to climatic change. More specifically, migration from rural areas is chosen as the central focus of the societal impacts studied.

Next to achieving an understanding of the interactions between the physical and the socio-cultural systems, an explicitly stated goal of the project is to support planners and politicians in anticipating and evaluating consequences of their decisions and to find solutions for a sustainable rural development under current and changing climatic conditions. The anticipated integrated model is intended to be the main tool to deliver such a policy support. Furthermore, the approach of the project is intended to be applicable more generally to tropical semi-arid regions.

6.2 What is integrated

The WAVES project is a bilateral collaboration project, in which some 5 German and 5 Brazilian research institutes are involved. Within the project, PIK bares responsibility for climate analysis and modelling, large scale hydrological modelling and integrated modelling.

In this interdisciplinary project, the responsibility for the individual disciplines lies primarily with the individual specialized institutes. As a consequence, quantitative disciplinary knowledge is represented by models common in their specific disciplines, rather than by models designed from one overall modelling philosophy. The descriptions of the relevant regional dynamical processes that are being integrated stem from the sectoral models, or simplifications of them. For regional integrated assessments, Global Change processes affect the region through the boundary conditions they impose on it. Scenarios are used to represent these boundary conditions.

Disciplines represented in the project are: climatology, hydrology (including water management and water demand issues), agricultural sciences (including agroeconomy) and socio-cultural sciences.

6.3 Philosophy of integration

A central problem in integrating interdisciplinary information lies in the consistency of the information at the interfaces between (and overlaps of) disciplines. Consistency problems may arise due to differences in terminology or interpretation, resolution of spatial and temporal scales and of quantifiability. Integration of disciplinary information can proceed through either qualitative methods/expert opinions or through quantitative connections.

The most stringent test of consistency will follow from the actual construction of an integrated model, forcing all information exchanges to be made explicit. Integration using integrating modelling is thus preferred when feasible, following CIESIN (Parson and Fisher-Vanden, 1995). Within the WAVES project, integrated modelling is chosen to be used for the endogenous regional dynamics. Expert opinions and subjective judgement are used in checking the consistency of scenarios.

The evolutionary process of the construction of the integrated model can best be described as strategic cyclic integration, as inspired by strategic cyclic scaling (Root and Schneider). The strategy iterates top-down and bottom-up approaches in a cyclical way, focusing process re-search and refining descriptive parameterizations.

The conceptualization of the integrated model started with a joint qualitative problem analysis. Possibly relevant quantities and processes were subjectively judged on their relevance in tackling the problem, and on their dynamic dependence on the problem.

The central problem was taken as a starting point. In our case (WAVES project) this is the causal relationship between climate (change) and migration in the semi-arid region of NE Brazil. To establish the link (or to bridge the gap) between the physics (climate) on the one hand and social dynamics (migration) on the other hand, it is necessary to include knowledge of a variety of disciplines, i.e. meteorology, hydrology and water resources, agricultural, economic and societal processes. The various processes and quantities hypothesized as relevant for the central problem were derived until a closed system of endogenous dynamics was achieved.

This (top-down) approach yields the concept of a model that is sufficiently complete and has endogenous dynamics. The relative degree of knowledge concerning the processes chosen to be represented in the model, played a minor role in this phase of the conceptualization.

In a second stage, disciplinary groups were asked to report on how quantifications of relevant parts of the conceptual model could be achieved, at largely homogenized spatial and temporal scales. This quantification could involve sectoral models, e.g. appropriately simplified or homogenized. This stage represents a bottom-up assessment of available knowledge.

Afterwards, the coverage of process descriptions required for the integrated model and the deliverable quantitative knowledge were compared. Double coverage of both process-descriptions and omissions was observed. In the case of overlaps between scientific disciplines, working groups will define a consensus on process descriptions. The gaps that are found partly represent processes that are poorly understood by the scientific community. Those gaps are being filled by hypothesizing on a number of (simple) plausible prototypical descriptions. Recommendations with respect to research in the field of these gaps in knowledge will certainly be one of the side-products of the integration process. The integration effort will clarify the specific importance of the various gaps found.

The latter two stages may be more important for projects involving a series of research groups from single disciplines, like WAVES, than for projects where only one (interdisciplinary) group is building an integrated model based entirely on its own experience. Such a difference in project organization necessarily influences the approach to integration taken.

The homogenization of spatial and temporal scales (and in other dimensions) will be one of the most important integrative efforts within the project. Scaling issues are commonly studied in all research fields individually. Typical spatial scales which are dealt with in this project range from plot size to regions of several 10 000 square km (the maximum size of a spatial discretization unit is about 2500 square km). Typical time scales range from hours to seasonal (a few months) periods. The main responsibility of the integrated modellers here is to define the scales at which the most relevant endogenous dynamics take place and to harmonize the scaling methods used.

Apart from purely scientific arguments, other arguments have an influence, not only on how the integration actually proceeds, but also on the level of the approach to integration. The organizational form of the project has already been mentioned as a relevant factor in shaping the approach to integration.

Another factor is the project's aim that the integrated model should become a tool for policymakers. This aim precludes that the integrated model complies with additional requirements. Usage of the model in the policy arena requires a fair recognizability and acceptability of sectoral representations within the model by sectoral specialists who will be involved in the policy analysis. The strategy of having sectoral research groups bear responsibility for sectoral representations tries to comply with this additional requirement. As a consequence, the integrated model may be more elaborate and less harmonized in its descriptions than desirable from the purely scientific integrative point of view.

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