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Accueil du site → Doctorat → Allemagne → 2003 → Regionale integrierte Modellierung der Auswirkungen von Klimaänderungen am Beipiel des semi-ariden Nordostens von Brasilien

Potsdam Universität (2003)

Regionale integrierte Modellierung der Auswirkungen von Klimaänderungen am Beipiel des semi-ariden Nordostens von Brasilien

Jaeger, Annekathrin

Titre : Regionale integrierte Modellierung der Auswirkungen von Klimaänderungen am Beipiel des semi-ariden Nordostens von Brasilien

Auteur : Jaeger, Annekathrin

Université de soutenance : Potsdam, Univ., Diss., 2003

Semi-arid regions are characterized by a high degree of water scarcity. An increasing water demand due to population growth and economic development and a decrease in interannuell precipitation rates due to Global Climate Change may aggravate water scarcity in the future, which poses the risk of worsening the already poor living conditions in these regions. An assessment of likely impacts of Global Climate Change requires integrated studies, that analyse the complex mechanisms and feed-backs between natural and human systems in semi-arid-regions and quantify impacts, best by using integrated dynamic models. Such a study was carried out by the joint Brazilian-German research project WAVES taking the semi-arid Northeast of Brazil as an example. One main result was the Semi-arid Integrated Model SIM. For the first time, the model allows for a comprehensive modelling of the complete causal chain of Climate Change, water availability, agricultural production and quality of life/migration including feed-backs from a dynamic, quantitative and geographically explicit point of view. SIM is a deterministic integrated model, that computes discrete. It is composed of several dynamically combined sub-modules. External driving forces are included via scenario assumptions. Calculations are possible on several spatial scales for a time horizon up to 50 years. This thesis made an in-depth contribution to the model development, analysed model uncertainties with the use of sensitivity and uncertainty analysis and performed integrated scenario analysis. Model application generally results in good model performance when comparing the simulation results with observed empirical data. Crop yields and agricultural production as well as the size of population or hydrological behaviour in the region are being well represented by the model. This confirms the adequacy of the chosen modelling approach. Using the methods of sensitivity and uncertainty analysis, uncertainties in input data, model parameter and model structure were scrutinized. Especially, simulation results for irrigated crop yields, changes in irrigation areas or changes in migration processes are characterised by a high degree of uncertainty. Climate and soil reduction factors exhibit major spatial influences or irrigated crop yields. Impacts of parameter variations mostly decrease for variables that are not directly related to the origin source within the causal chain. The coupling of sub-modules is of great importance for the behaviour of certain variables. Simulations with two climate scenarios proved a high regional sensitivity and vulnerability to impacts of Global Climate Change. Significance of impacts is found after 2025 only. Both for the scenarios with an increase and a decrease of trends in precipitation, water stress continues to be a major problem, leading to lower water availability and thus worsening living conditions in the region. Within the scenario based on the assumption of a precipitation decrease, strong losses of crop yields and a substantial higher rate of migration are visible compared to the scenario based on the assumption of a precipitation increase. In order to assess the likely impacts of socio-economic development strategies, simulations with two reference scenarios were computed. Development strategies such as the extension of large reservoirs and potential irrigated areas are confronted with limits of efficiency gains due to the prevailing water scarcity in the region. Agricultural GDP increases in the scenario describing a higher extension of potential irrigated areas, but migration continues to increase. The results indicate that all regional development strategies are tightly restricted by the general natural conditions of the region and the maintaining high importance of the agricultural sector. Impacts of Global Climate Change may reinforce these restrictions which refers to the need for careful long-term planning of regional development. Generally, SIM reasonably well represents both the complex dynamics of the system investigated and the likely impacts of Global Climate Change. Therefore, the model can serve as a valuable instrument for assessing the potential of different strategies for enhancing the adaptability of the region to the impacts of Global Climate Change. However, the inclusion of a macro-economicsub-module and a better description of the feed-back mechanisms between life quality andmigration could still improve the model’s capabilities


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