Transcript NADSS an Overview

A Cyberinfrastructure for Drought
Risk Assessment
An Application of Geo-Spatial Decision Support to
Agriculture Risk Management
NADSS Overview
The 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 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
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 proofof-concept framework:
National Agricultural Decision
Support System,
Self Calibrating Tools
Supported research in
multiple domains.
Drought Tools: SPI
Standard Precipitation Index
Built to quantify deficit or excess moisture conditions at
a location for a specified time interval
Values 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: PDSI
Palmer Drought Severity Index
Built to quantify the severity of drought conditions
is one of the most widely used drought tools
Unlike the SPI, the PDSI uses temperature as well as
precipitation data
Computations are based on a supply demand model for the
amount of moisture in soil
NADSS 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: NSM
Newhall Simulation Model
Used by USDA services to estimate soil moisture regimes
as defined by Soil Taxonomies
Runs on monthly normals for both precipitation and
temperature
generally for 30 year normals
NADSS 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 data
Allows us to determine where new or alternative crops can
be adapted to the landscape
NADSS Architecture
NADSS 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 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
Any component can communicate
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
Spatial Layer
e.g. spatial analysis and rendering tools
Application of Layering
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
The user adjusts weight
factors for each variable
Variables are spatially
rendered
The result is a “spatial”
view of risk
Next Steps
We are currently working towards unification of our tools under a
common interface, architecture and data set
Maintain a quality controlled data set, minimizing windows of missing
climate data to achieve more accurate results
Focused on human centric design to increase the usability of our tools
thereby providing broader access to producers
Create 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