A Cyberinfrastructure for Drought Risk AssessmentAn Application of Geo-Spatial Decision

Support to Agriculture Risk Management

NADSS OverviewThe National Agriculture Decision Support System (NADSS) is a distributed web based application to help decision makers assess various risk factors

our research has focused primarily on droughtwe 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

Funding$1M of Nebraska Research Initiative seed money was leveraged to secure competitive awards in excess of $4.5M in funding.Has been used to build a proof-of-concept framework:

National Agricultural Decision Support System,Self Calibrating ToolsSupported research in multiple domains.

Drought Tools: SPIStandard Precipitation IndexBuilt to quantify deficit or excess moisture conditions at a location for a specified time intervalValues computed using precipitation records for a location

represents the number of standard deviations from the normalized mean

Can quantify both deficit and excess precipitation over multiple time scales

Drought Tools: PDSIPalmer Drought Severity IndexBuilt to quantify the severity of drought conditions

is one of the most widely used drought toolsUnlike the SPI, the PDSI uses temperature as well as precipitation dataComputations are based on a supply demand model for the amount of moisture in soilNADSS uses a unique implementation of the PDSI that dynamically calculates certain coefficients used in the computation so that extreme periods a reported with a predictable frequency of occurrence for rare events.

Drought Tools: NSMNewhall Simulation ModelUsed by USDA services to estimate soil moisture regimes as defined by Soil TaxonomiesRuns on monthly normals for both precipitation and temperature

generally for 30 year normalsNADSS implemented a revision of the model to tun on monthly records for individual years

We currently include “centennial stations” or stations with 100 years or more of dataAllows us to determine where new or alternative crops can be adapted to the landscape

NADSS ArchitectureNADSS currently utilizes a layered architecture with individual components residing together in layers

this approach allows us to more easily develop, distribute, and deploy new components; allowing for greater flexibility and performance

The bulk of computing is done on by component server objects designed to deal solely with data requests

component logic can be combined (connected) to create unique requests

The application front-end is further partitioned into individual EJB modules to provide a Web-services interface

Application Layer (user interface)e.g. Web interface, EJB, servlets

Knowledge Layere.g. Data Mining, Exposure Analysis, Risk Assessment

Information Layere.g. Drought Indices, Regional Crop Losses

Data Layere.g. Climate Variables, Agriculture Statistics

Spatial Layere.g. spatial analysis and rendering tools

Any component can communicate with components in other layers above or below itEach layer is tied to the spatial layer, allowing the data from any layer to be rendered spatially

The user adjusts weight factors for each variable

The result is a “spatial” view of riskVariables are

spatially rendered

By combining several domain specific factors from different layers we are able to create maps (in this case: displaying the risk for crop failure) that show data for states, counties, farm or even field level

Application of Layering

Next StepsWe are currently working towards unification of our tools under a common interface, architecture and data setMaintain a quality controlled data set, minimizing windows of missing climate data to achieve more accurate resultsFocused on human centric design to increase the usability of our tools thereby providing broader access to producersCreate a fully distributable architecture allowing us to more easily integrate other projects for other research facilities

provides better support for the needs of producers and researchers