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Compendium on methods and tools to evaluate impacts of, and vulnerability and adaptation to, climate
change
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Decision Support System for Agrotechnology Transfer (DSSAT) developed
under the International Consortium for Agricultural Systems Applications (ICASA)
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Description
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The Decision Support System for Agrotechnology Transfer (DSSAT) is decision support system that
encompasses process-based computer models that predict growth, development and yield as a function
of local weather and soil conditions, crop management scenarios and genetic information.
The crops that are covered include grain cereals such as rice, wheat, maize, barley, sorghum, and
millet, grain legumes, such as soybean, peanut, dry bean, chickpea, tuber crops, such as potato and
cassava, cotton, sugarcane, vegetables, and various other species. DSSAT also includes a basic set
of tools to prepare the input data, as well as application programs for seasonal, crop rotation and
spatial analysis. The crop models not only predict crop yield, but also resource dynamics, such as
for water, nitrogen and carbon, and environmental impact, such as nitrogen leaching. DSSAT includes
an economic component that calculates gross margins based harvested yield and byproducts, the price
of the harvested products, and input costs.
The models use daily weather data, soil profile information, and basic crop management data as
input. Model outputs are normally compared with local experimental data in order to evaluate model
performance and determine the genetic characteristics of local varieties.
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Appropriate Use
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DSSAT can be used at a farm level to determine the impact of climate change on production and
potential adaptation practices that should be developed for farmers. It can also be used at a
regional level to determine the impact of climate change at different spatial scales, the main
consideration being availability of accurate input data.
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Scope
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DSSAT can be used for any region across the world, as long as the local input data are available.
DSSAT has been distributed to over 2,000 users in more than 90 countries and has been tested in most
regions of the world.
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Key Output
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Key outputs are the impact of climate change on crop production, resource use and environmental
pollution and management options for adaptation.
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Key Input
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The crop simulation models require daily weather data, including maximum and minimum temperature,
solar radiation, and precipitation, a description of the soil physical and chemical characteristics
of the local, and crop management, including crop, variety, planting date, plant spacing, and inputs
such as fertilizer and irrigation.
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Ease of Use
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DSSAT has been developed in Windows environment and can be easily used after installation. For all
crops considered (over 25 spp.), example data based on real experiments are provided. For local
implementation, access to weather and soil data, crop management information and some crop
measurements are needed.
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Training Required
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For proper use, some training is required, especially with respect to the preparation of the input
files, determination of the genetic coefficients and for evaluation with local data. Familiarity with
the Windows operating system, spread sheet tools, and text editors is desirable.
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Training Available
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The University of Georgia in collaboration with the International Consortium for Agricultural Systems
Applications (ICASA) offers a two week training workshop on DSSAT every other year. In addition,
training is often provided for groups of scientists in a country or region, depending on available
resources and research interests.
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Computer Requirements
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DSSAT runs on a Pentium 4 or higher computer with at least 521 MByte of memory and 0.5 GByte of hard
disk space. The preferred operating system is Windows XP.
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Documentation
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Hoogenboom, G., J.W. Jones, P.W. Wilkens, C.H. Porter, W.D. Batchelor, L.A. Hunt, K.J. Boote, U.
Singh, O. Uryasev, W.T. Bowen, A.J. Gijsman, A. du Toit, J.W. White, and G.Y. Tsuji. 2004. Decision
Support System for Agrotechnology Transfer Version 4.0 [CD-ROM]. University of Hawaii, Honolulu,
HI.
Tsuji, G. Y., G. Hoogenboom, and P. K. Thornton [Editors]. 1998. Understanding Options for
Agricultural Production. Systems Approaches for Sustainable Agricultural Development. Kluwer
Academic Publishers, Dordrecht, the Netherlands. ISBN 07923-4833-8. 400 pp.
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Applications
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The software has been used extensively in many different projects funded by US AID, US EPA, Asian
Pacific Network, and other organizations to determine the impact of climate change on agricultural
production and food security. It was also used by numerous countries in the U.S. Country Studies
Program, including Egypt, Japan, Kazakhstan, and Uruguay.
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Contacts for Framework, Documentation, Technical Assistance
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Tools and documentation: International Consortium for Agricultural Systems Applications (ICASA),
2440 Campus Rd., Box 527, Honolulu, HI 96822, USA,
e-mail: icasa@icasa.net; website: http://www.icasa.net.
Technical assistance: Dr. Gerrit Hoogenboom, Department of Biological and Agricultural Engineering,
the University of Georgia, Griffin, Georgia 30223, USA;
e-mail: gerrit@uga.edu.
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Cost
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The cost of the software is $195+ shipping expenses.
The registration costs for attending a training workshop are $1,500. Additional costs include hotel
and per diem, and travel to and from the workshop.
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References
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Alexandrov, V.A., and G. Hoogenboom. 2000. The impact of climate variability and change on major
crops in Bulgaria. Agricultural and Forest Meteorology 104(4):315-327.
Alexandrov, V.A., and G. Hoogenboom. 2000. Vulnerability and adaptation assessments of agricultural
crops under climate change in the Southeastern USA. Theoretical and Applied Climatology 67:45-63.
Baethgen, W. E. 1997. Vulnerability of the agricultural sector of Latin America to climate change.
Climate Research 9(1-7).
Hatch, U., S. Jagtap, J. Jones, and M. Lamb. 1999. Potential effects of climate change on
agricultural, water use in the southeast US. Journal of the American Water Resources Association
35: 1551-1561.
Iglesias, A., Rosenzweig, C., and Pereira, D. 2000. Agricultural impacts of climate change in
Spain: Developing tools for a spatial analysis. Global Environmental Change 10:69-80.
Jones, J.W., G. Hoogenboom, C.H. Porter, K.J. Boote, W.D. Batchelor, L.A. Hunt, P.W. Wilkens, U.
Singh, A.J. Gijsman, and J.T. Ritchie. 2003. DSSAT Cropping System Model. European Journal of
Agronomy 18:235-265.
Jones, P.G., and P.K. Thornton. 2003. The potential impacts of climate change on maize production
in Africa and Latin America in 2055. Global Environmental Change13:51-59.
Mearns, L. O., T. Mavromatis, E. Tsvetsinskaya, C. Hays, and W. Easterling. 2001. Comparative
responses of EPIC and CERES crop models to high and low spatial resolution climate change
scenarios. Journal of Geophysical Research 104(d4): 6623-6646.
Tsuji, G. Y., G. Hoogenboom, and P. K. Thornton [eds.]. 1998. Understanding Options for
Agricultural Production. Systems Approaches for Sustainable Agricultural Development. Kluwer
Academic Publishers, Dordrecht, the Netherlands. ISBN 07923-4833-8. 400 pp.
White, J.W, G. Hoogenboom, and L.A. Hunt. 2005. A structured procedure for assessing how crop
models respond to temperature. Agronomy Journal 96(2):426-439.
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