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Compendium on methods and tools to evaluate impacts of, and vulnerability and adaptation to, climate
change
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Information and Decision Support System for Climate Change Studies in
South East South America (IDSS-SESA Climate Change)
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Description
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The IDSS SESA is based on the linking and integration of
- Maps and associated databases of soils, weather, land use, and political divisions;
- National and regional statistics (production, socioeconomic, demographic);
- Prices of inputs and products;
- Remotely sensed information (crops, pastures, natural resources, climate);
- Simulation models of crop, pasture and forest growth, development and production (DSSAT,
APSIM);
- Climate change scenarios (GCMs, RCMs, and statistical methods);
- A statistical package for analyzing climate data and generating synthetic weather (LARS and
MARKSIM);
- Methods for land use evaluation and for defining land use feasibility classes;
- A simulation model of soil carbon and nutrient dynamics (CENTURY);
- Tools for agricultural applications of global positioning systems (GPS); and
- Geographic information systems (GIS) to process and analyze maps and databases and to generate
information that can be easily understandable and applied by agricultural stakeholders.
Climate change scenarios are defined using three methods:
- Studying the changes in climate during the last 100 years and projecting those changes for the
near future;
- Using sensitivity analyses, i.e., modifying observed weather data with combinations of changes
in temperatures max and min and rainfall and generating synthetic weather data;
- Using GCMs to estimate monthly anomalies of weather (temperatures and rainfall) or atmospheric
variables (SLP, geopotential at 850 mb, etc.) and modifying the observed climatic data.
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Appropriate Use
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To study the impacts of possible climate change scenarios on different agricultural production
systems (livestock, crops, mixed) and on the natural resource base, and explore adaptive
technological options (crop/pasture management, input use, mixes of crop and pasture types).
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Scope
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Agro-ecological zone level (national, regional).
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Key Output
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Changes in agricultural productivity and economic results, variation in agricultural and
environmental risks, etc., for different climate change scenarios. Produces outputs (e.g., maps,
tables, etc.) in formats easily understood by non-specialist users such as policy makers and farmers.
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Key Input
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Soils, weather, and land use data; national and regional statistics of crop/livestock production;
prices of inputs and products.
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Ease of Use
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For trained agronomists
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Training Required
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Requires training on the basic tools included in the IDSS: simulation models, GIS, weather
generators, and statistical analyses.
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Training Available
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Training is available for some of the IDSS components (DSSAT, APSIM, CENTURY).
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Computer Requirements
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Windows-based PC
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Documentation
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http://sedac.ciesin.columbia.edu/aiacc/methods.html
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Applications
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Used in INIA-Uruguay, INTA-Argentina, IAPAR-Brazil, EMBRAPA-Trigo, Brazil, and the AIACC project LA
27 (
http://www.aiaccproject.org/Final Reports/Final Reports/FinalRept_AIACC_LA27.pdf).
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Contacts for Framework, Documentation, Technical Assistance
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Walter E. Baethgen IFDC-Uruguay, Juan M. Perez 2917 Apt. 501, Montevideo, Uruguay; Tel:
598.2.712.0838; e-mail: wbaethgen@undpfim.org.uy.
Agustín Giménez, INIA La Estanzuela, Colonia, Uruguay 70000; Tel: 598.574.8000.
Graciela Magrin, INTA Castelar, Buenos Aires; Tel: 54.11.4621.1684.
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Cost
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Not identified
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References
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Baethgen, W.E., R. Faría, A. Giménez, and P. Wilkens. 2001. Information and decision
support systems for the agricultural sector. In Proceedings — Third International Symposium
on Systems Approaches for Agricultural Development, Lima, Peru, 8-10 November 1999 [CD-ROM computer
file]. International Potato Center (CIP), Lima, Peru.
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