Western Region GIS Update:
National Suitability Modeling of Biofuel
Feedstocks
Chris Daly, Mike Halbleib David Hannaway
Sun Grant Western Region GIS Center
Oregon State University
Corvallis, Oregon, USA
Introduction

GIS Program Objective: Gain an understanding of the spatial
distribution of current and potential feedstock resources
regionally and nationally

A couple of envisioned outcomes:
 A series of national maps that describe the actual and
potential productivity patterns of various feedstocks
 Maps showing changes in production patterns under
historical and future climates
How Are We Accomplishing This?
Currently
•
Collecting production information from field trials and the literature; some
regions developing models to make spatial estimates
Issues
•
Data are taken from scattered locations under various management
practices and at varying times
•
Difficult to coordinate these regional results into a national, “wall-to-wall” (full
national) assessment that is consistent across the country
•
Unclear how potential biomass production of new crops will be estimated
nationwide, both now and under historical and future climates
Suitability Modeling Framework
At The National Level
Two main objectives:
 Develop gridded estimates of current and potential feedstock
resources across the conterminous US

Provide a context for biomass data collected by the regional
centers, which will aid in prioritizing what data to collect and
where, assessing data quality, and siting new field trials
Suitability Modeling Framework (Cont.)
What We are Doing
 Modifying and enhancing a simple suitability model that
incorporates the important environmental constraints on
biomass production, namely climate and soils
Expected Result
 High-resolution, gridded “first-guess” potential biomass maps
for the conterminous US

Accompanying GIS model that relates biomass potential to
limiting environmental factors
Suitability Modeling Framework (Concl.)
How Will this Help?
 A starting point for more refined mapping of current and future
potential biomass resources with the aid of field data,
management and economic analysis, land use/land cover, etc.

Inform data collection efforts on where additional field data
would be helpful, and what variables are most needed

Provide a spatial context for quality control of field data

Generate “what if” maps of potential and future resources
Current Suitability Mapping System
PRISM Spatial Climate Datasets
• All State of the
Science
• Physiographically
sensitive mapping
• Official Climate
Datasets of the
USDA
• 800-m and 4-km
resolutions
• Monthly tmin,
tmax, precip, dew
pt.
• 1971-2000 means
CONUS 1895-2008 Monthly Climate
Time Series
•
•
•
Tmin, tmax, precip, dew point
800-m grid resolution
150 Billion grid cells
PRISM Mean Annual Minimum Temperature
122W, 44.5N - Oregon Cascades
3.5
2.5
2
1.5
1
0.5
0
-0.5
-1
05
00
20
95
20
90
19
85
19
80
19
75
19
70
19
65
19
60
19
55
Year
19
50
19
45
19
40
19
35
19
30
19
25
19
20
19
15
19
10
19
05
19
00
19
19
95
-1.5
18
Minimim Temperature (C)
3
Simple Environmental Model
Tall Fescue
Simple Environmental Model for Tall Fescue
Example Functions
Ambient Temperature
Soil Drainage
Unsuit
able
Soil Salinity
Soil pH
Unsui
table
“Trickle down” hierarchy of tolerance tables
(We don’t have to start from scratch)
Tall Fescue Suitability – All Climate & Soil Constraints
Tall Fescue Suitability – No Soil Constraint (Climate Only)
Tall Fescue Suitability – No precip constraint (Irrigated)
Tall Fescue Suitability
No soils, irrigated, no overwinter constraint (annual)
Start of a Switchgrass Suitability Map?
Moisture does
not come in
warm season
Next Steps – FY2010
• Upgrade to latest PRISM climate grids
•
Move from qualitative suitability categories to biomass yield using continuous
equations
•
Move to a monthly water balance model to handle timing of precip
•
Run suitability model with both 1971-2000 mean climate, and 30 years (e.g.,
1979-2008) of monthly time series climate data to develop probability
distributions of biomass yield
•
Produce suitability maps for tall fescue and switchgrass via the internet map
server
•
Use species experts and field data being collected to validate and improve
biomass model
•
Determine which field information is most important for suitability mapping
Regional Center Interactions

Come to a consensus on a priority list of biomass species to map

Identify a representative variety for each species or subspecies

For each species, agree on what will be considered “maximum possible
yield” (e.g., maximum genetically possible, maximum observed yield, etc.)

Define management criteria assumed for initial mapping (e.g., best practices,
typical practices)

Overlay field data onto the national modeled map and help to refine and
improve the suitability model
Regional Center Interactions (concl.)

Use modeled map to identify locations where field validation of estimated
yield should be checked and verified

Use modeled map to assess field data quality (areas of strong disagreement
may indicate unrepresentative data)

Incorporate mapped biomass estimates into regional center activities (e.g.,
POLYSYS, economic modeling, processing facility siting, etc.)

Provide GIS data sets that complement or improve gridded biomass
estimates