1. National Agricultural Decision Support System (NADSS) PI: Steve Goddard An Application of Geo-Spatial Decision Support to Agriculture Risk Management

2. What is NADSS? The National Agricultural Decision Support System (NADSS) is a distributed web-based application to help decision makers assess various risk factors The National Agricultural Decision Support System (NADSS) is a distributed web-based application to help decision makers assess various risk factors our research has focused primarily on drought our research has focused primarily on drought we are investigating ways to use the system to create tools to aide in the identification of risk areas we are investigating ways to use the system to create tools to aide in the identification of risk areas Using various data and computational indices we are able to create tabular data for analysis as well as maps for further spatial analysis Using various data and computational indices we are able to create tabular data for analysis as well as maps for further spatial analysis

3. The Partnership lNational Science Foundation’s Digital Government Program lNational Drought Mitigation Center, University of Nebraska--Lincoln lHigh Plains Regional Climate Center, UNL lUSDA Risk Management Agency, Natural Resources Conservation Service, National Agricultural Statistics Service, and the Farm Service Agency lUSGS EROS Data Center lNebraska Research Initiative on Geospatial Decision Support Systems lGIS Workshop

4. Funding Source: NSF: $1 Million, 7/01—1/05 Title: DIGITAL GOVERNMENT: A Geospatial Decision Support System for Drought Risk Management Principal Investigators: Steve Goddard, Jitender Deogun, Michael J. Hayes, Kenneth G. Hubbard, Stephen Reichenbach, Peter Revesz, W.J. Waltman, Donald A. Wilhite, and Mark D. Svoboda, University of Nebraska-Lincoln (UNL), Lincoln, Nebraska 68588-0115. (goddard@cse.unl.edu) Co-Investigators: Sheri K. Harms, University of Nebraska-Kearney; J.S. Peake, University of Nebraska-Omaha; Ray Sinclair and Sharon Waltman, USDA Natural Resources Conservation Service, National Soil Survey Center, Lincoln, NE; and Marcus Tooze, GIS Workshop, Lincoln, NE.

5. Funding Source: USDA RMA/FCIC: $1.3 Million, 10/02—3/05 Title: RISK ASSESSMENT AND EXPOSURE ANALYSIS ON THE AGRICULTURAL LANDSCAPE: A Holistic Approach to Spatio-Temporal Models and Tools for Agricultural Risk Assessment and Exposure Analysis Principal Investigators: Steve Goddard, Jitender Deogun, Michael J. Hayes, Kenneth G. Hubbard, H. Douglas Jose, Stephen Reichenbach, W.J. Waltman, Donald A. Wilhite, and Mark D. Svoboda, University of Nebraska-Lincoln (UNL), Lincoln, Nebraska 68588-0115. (goddard@cse.unl.edu) Co-Investigators: Norman Bliss, EROS Data Center; Sioux Falls, SD: Sheri K. Harms, University of Nebraska-Kearney; and J.S. Peake, University of Nebraska-Omaha; Ray Sinclair and Sharon Waltman, USDA Natural Resources Conservation Service, National Soil Survey Center, Lincoln, NE; and Marcus Tooze, GIS Workshop, Lincoln, NE.

6. NADSS Web Site http://nadss.unl.edu/ http://nadss.unl.edu/

7. Current Tools Our current tools apply risk analysis methodologies to the study of drought Our current tools apply risk analysis methodologies to the study of drought Integration of basic models with data generates “information” for analysis by decision makers Integration of basic models with data generates “information” for analysis by decision makers Information can be gathered at any resolution for which we have data Information can be gathered at any resolution for which we have data http://nadss.unl.edu http://nadss.unl.edu

8. Current NADSS Tools

9. Planting date guide tool with date sliders, numerical information, and navigation buttons. Sample risk analysis maps of growing non- irrigated corn in NE and Custer county.

10. Proposed NADSS Tools An Irrigation Scheduling tool that will help producers better manage their limited water resources, decrease the use of energy for pumping, and decrease the risk of drought stress.

11. Another Proposed NADSS Tool A Crop-Specific Yield Prediction tool that will provide the producer with an estimate of yield based on the weather up to the current date and projections of what it might be from the current date to the end of the growing season.

12. Another Proposed NADSS Tool A Field Analyst tool that can, for example, analyze the soil quality for a particular field based on the NRCS Soil Rating for Plant Growth (SRPG) index. It can also be used by a producer to evaluate “value added” when new fields are put into service or removed from service.

13. Another Proposed NADSS Tool: Field Analyst continued Following the example using an SRPG analysis, when both an original field and field addition have been digitized, the Field Analyst provides the user with the SRPG of the combined fields, and whether the field addition had a positive or negative affect on the overall soil quality.

14. Building a Spatial View Data from information and knowledge layers are translated spatially and interpolated to provide a “risk view” for a defined area Data from information and knowledge layers are translated spatially and interpolated to provide a “risk view” for a defined area Drought Indices Soil Data Climate Data Reported Yields Raster interpolation of data points within various windows Inverse Distance Weighting Spline Kriging Re-summarization of raster data Generation of displayable images Risk Indicators SurfacingDisplay Other Data Type

15. Combining Risk Factors By combining several domain specific factors from our “information layer” we are able to create maps displaying the risk for states, regions or countries By combining several domain specific factors from our “information layer” we are able to create maps displaying the risk for states, regions or countries The user adjusts weight factors for each variable The result is a “spatial” view of risk Variables are spatially rendered

16. Conclusion We have developed the framework for a Distributed Geospatial Decision Support System architecture that can be applied to other problems and domains We have developed the framework for a Distributed Geospatial Decision Support System architecture that can be applied to other problems and domains For example, we can integrate water models, economic models and even threat models into the system. For example, we can integrate water models, economic models and even threat models into the system.

17. Application Layer (user interface) e.g. Web interface, EJB, servlets Knowledge Layer e.g. Data Mining, Exposure Analysis, Risk Assessment Information Layer e.g. Drought Indices, Regional Crop Losses Data Layer e.g. Climate Variables, Agriculture Statistics Spatial Layer e.g. spatial analysis and rendering tools Any component can communication with components in other layers above or below it Any component can communication with components in other layers above or below it Each layer is tied to the spatial layer, allowing the data from any layer to be rendered spatially Each layer is tied to the spatial layer, allowing the data from any layer to be rendered spatially