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Title: The GPFARM DS for agroecosystem sustainability: the past, future, and lessons learned

Author
item Ascough Ii, James
item McMaster, Gregory
item Dunn, Gale
item ANDALES, A - Colorado State University

Submitted to: Environmental Modeling International Conference Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 5/12/2010
Publication Date: 12/15/2010
Citation: Ascough II, J.C., Mcmaster, G.S., Dunn, G.H., Andales, A.A. 2010. The GPFARM DS for agroecosystem sustainability: the past, future, and lessons learned. In: Swayne, D.A., Yang, W., Voinov, A.A., Rizzoli, A., and Filatova, T., editors. Environmental Modeling International Conference Proceedings. International Modeling and Environmental Software Society, Modelling for Environment's Sake, July 5-8, 2010, Ottawa, Canada. p.2540-2547.

Interpretive Summary: The USDA-ARS Agricultural Systems Research Unit (ASRU) developed the Great Plains Framework for Agricultural Resource Management (GPFARM) DSS. GPFARM provides production, economic, and environmental impact analysis from which alternative agricultural management systems can be tested and compared. GPFARM primary development occurred from the early 1990’s to 2003, ending with the current version 2.6. Despite a reasonable level of producer involvement in the requirements analysis, development, and evaluation phases of GPFARM, it can be argued that the rate of adoption has been slow compared with the rate predicted for it over a decade ago at development initiation. In this paper, we discuss the lessons learned (e.g., successes and failures) in over a decade of agricultural DSS development. Major conclusions resulting from discussion and critical analysis of the GPFARM project include: 1) It is important that the DSS development process includes careful evaluation of the scope of the DSS in relation to the human and fiscal resources available; 2) Careful attention to the intended target user group(s) is needed by: a) matching the proposed technology appropriately with the user, and b) gathering input from a broad spectrum of potential users; and 3) Simpler tools or database information generated from simulation analyses of alternative management options may have been more appropriate for delivery to producers and consultants at this stage in time.

Technical Abstract: The USDA-ARS Agricultural Systems Research Unit (ASRU) developed the Great Plains Framework for Agricultural Resource Management (GPFARM) DSS. GPFARM provides production, economic, and environmental impact analysis from which alternative agricultural management systems can be tested and compared. GPFARM primary development occurred from the early 1990’s to 2003, ending with the current version 2.6. Despite a reasonable level of producer involvement in the requirements analysis, development, and evaluation phases of GPFARM, it can be argued that the rate of adoption has been slow compared with the rate predicted for it over a decade ago at development initiation. In this paper, we discuss the lessons learned (e.g., successes and failures) in over a decade of agricultural DSS development. Major conclusions resulting from discussion and critical analysis of the GPFARM project include: 1. It is important that the DSS development process includes careful evaluation of the scope of the DSS in relation to the human and fiscal resources available (e.g., assessment of personnel available for developing, evaluating, implementing, and maintaining a DSS that matches the scope, scale, and complexity of the project). Formal project management and software engineering protocols and tools can aid in this regard. 2. Careful attention to the intended target user group(s) is needed by: 1) matching the proposed technology appropriately with the user, and 2) gathering input from a broad spectrum of potential users when performing a requirements analysis. 3. Simpler tools or database information generated from simulation analyses of alternative management options may have been more appropriate for delivery to producers and consultants at this stage in time. 4. The capability to rapidly update major components (e.g., simulation model, databases) and address current questions or problems in the system is an absolute necessity - the ASRU has recently developed an Object Modeling System (OMS) for this purpose. In addition, an appropriate compromise between scientific rigor and simplicity is essential for critical DSS components to ensure overall quality of the product (e.g., crop and forage simulation model response to environmental stresses; N and water balance response to management).