National Agricultural Decision Support System (NADSS)

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

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 • 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 • 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 • National Science Foundation’s Digital Government Program • National Drought Mitigation Center, University of Nebraska--Lincoln • High Plains Regional Climate Center, UNL • USDA Risk Management Agency, Natural Resources Conservation Service, National Agricultural Statistics Service, and the Farm Service Agency • USGS EROS Data Center • Nebraska Research Initiative on Geospatial Decision Support Systems • GIS 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/

7. Current Tools • 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 • Information can be gathered at any resolution for which we have data • http://nadss.unl.edu

8. Current NADSS Tools

9. Current NADSS Tools 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. Surfacing Display Risk Indicators Raster interpolation of data points within various windows Inverse Distance Weighting Spline Kriging Building a Spatial View • Data from information and knowledge layers are translated spatially and interpolated to provide a “risk view” for a defined area Re-summarization of raster data Generation of displayable images Drought Indices Soil Data Climate Data Reported Yields 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 Variables are spatially rendered The user adjusts weight factors for each variable The result is a “spatial” view of risk

16. Conclusion • 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.