Administrative
Author: Abigail Rosenberg, Ph.D.
Co-Author(s): Abigail Rosenberg, Ph.D., Ferenc Szidarovszky Ph.D., Paul Brown, James
Atkinson, and John Hervert
Owner: Navy Secretariat Reviewers (USMC)
Project Title: Forecasting precipitation using near real-time weather and remote sensing data
with multi-objective optimization
Service/Sponsor: U.S. Marine Corps
Division: U.S. Marine Corps
Installation: Marine Corps Air Station Yuma
Secondary Installation: Luke Air Force Base and Yuma Proving Ground
State: AZ
Continuation Proj.: No
Expected Complete Date: 11/25/2012
Resource Type: Natural Resources
Field Location: Barry M. Goldwater Range and Yuma Proving Ground
Primary Theme: Endangered Species
Secondary Theme: weather
Project Category: Research
Other Funds: Yes.
Fund Explanation: MCAS has requested $75,000 for FY11 toward the primary establishment of a
weather station network; $45,000 in weather station instruments and equipment/supplies; $?? inkind cost of personnel support
Areas of Emphasis
Endangered species
Purposes
To establish a network of wireless rain gages and automated weather stations over the next three
years to provide the near real-time data required to develop a drought early warning system for
the survival of the endangered Sonoran pronghorn antelope
Federal Regulations
Endangered Species Act
Military Lands Withdrawal Act (MLWA)
Sikes Act, 16 U.S.C. 670 (SIKE)
Budget Items
Type
Item
Contract
Materials/Supplies
Contract
Contract
Materials/Supplies
Salary
Contract
Travel
Contract
Salary
Contract
Contract
SUB-TOTAL
Travel
Other
Expected Products
Product Type
Publication
Experimental Data
Technical Report
Fact Sheet
Item Cost
Description
($)
$1,000 Station installation costs (hardware, tools,
concrete) and website development
(software, computer supplies, computer
equipment)
$4,600 Automated downloaded stations
$52,164 Full time employee $36,000 salary and
$16,164 indirect
$2,600 Costs for station installation, data retrieval
and maintenance trips expensed at 600
miles at $0.445/mile, meals at $51.00 plus
one nights lodging at $71.00 for a total of
$389.00. Installation trips assume
installing two stations/day at $631. One
trip expected to last 3 days (install 6
stations) and a 2nd trip of two days (install 4
stations) at $412.
$30,000 System and Industrial Engineering Multiobjective Optimization
$3,000 Attend Pronghorn recovery meetings
$15,872 17% CESU indirect costs
$109,236
Description
Submission of at least one manuscript
to a peer-reviewed scientific journal
Historical log of weather, Doppler
radar, and satellite imagery; multiobjective optimization numerical
analysis;
A report that includes a literature
review, materials/methods, result
summary and disscussion
Depicting a brief overview/summary of
project undertaking and findings
Due Date
11/25/2012
11/25/2012
11/25/2012
11/25/2012
Project Details
Project Synopsis:
We propose installing a network of wireless rain gages and automated weather stations to support
the development of a drought early warning system within the Pronghorn habitat. Upon
completion, the early warning system will provide the data sets required for spatial interpolation
of precipitation data, thus leading to improved estimates of biomass production within the
Pronghorn habitat.
Abstract:
Sonoran pronghorn (Antilocapra americana) were listed as endangered in 1967 by the U.S. Fish
and Wildlife Service (USFWS). Currently, there are an estimated 68 animals in the U.S. limited
to Barry M. Goldwater Range (BMGR), Cabeza Prieta National Wildlife Refuge (NWR), Organ
Pipe Cactus National Monument (NM) and two Mexican populations totaling 400 individuals.
Both the Military Lands Withdrawal Act (MLWA) and the Sikes Act require the development
and implementation of an Integrated Natural Resources Management Plan (INRMP) that
facilitates programs that provide for the conservation and rehabilitation of natural resources and
the sustainable multi-purpose use of the resources. The Sikes Act states each INRMP should
ensure no “net loss in the capabilities of military lands to support the military mission” as a result
of natural resources management provided in the plan. In addition, Section 7 of the Endangered
Species Act (ESA) requires all Federal agencies, in consultation with the USFWS, to use their
authorities to further the purpose of the ESA and to ensure that their actions are not likely to
jeopardize the continued existence of listed species or result in destruction or adverse
modification of critical habitat.
Climate strongly influences the welfare and management of endangered species. The Sonoran
pronghorn has suffered drought-related mortality. Area closures and habitat enhancements
depend on accurate climate forecast within the population’s home range. The Marine Corps Air
Station Yuma, Luke Air Force Base, and the U.S. Army Yuma Proving Grounds have partnered
with the Pronghorn Recovery Team to develop a climate monitoring program in support of the
pronghorn. We propose installing a network of wireless rain gauges and automated weather
stations to support the development of a drought early warning system within the Pronghorn
habitat. Upon completion, the early warning system will provide the data sets required for spatial
interpolation of precipitation data, thus leading to improved estimates of biomass production
within the Pronghorn habitat.
Background:
The USFWS and recovery team are proposing to establish a Sonoran pronghorn breeding
enclosure on Kofa NWR and adjacent public and state lands south of Interstate 8. The USFWS is
proposing to reestablish an “experimental, nonessential population” in the Kofa NWR. This
designation falls under the Endangered Species Act (ESA) that allows greater management
flexibility through the introduction of new populations within the species’ historical range. The
Kofa NWR breeding enclosure may potentially impact the U.S. Army’s Yuma Proving Ground
(YPG). The second area under consideration includes the eastern portion of the BMGR and part
of the Tohono O'odham Indian Reservation (TON).
A large scale assessment of vegetation productivity for the pronghorn is feasible on a near realtime basis allowing more precise monitoring of the forage resources to improve decision making
about animal numbers and the vegetation resources. The inability to make decisions at critical
times could lead to low fawn survival rates or vegetation overuse, which in turn, could lead to the
irreversible degradation of vegetation and soil resources within the Pronghorn habitat. A key
factor limiting the development of a vegetation productivity model and drought early warning
system is the current inability to monitor the spatial distribution of rainfall over the region. The
purpose of this project is to establish an automated network of weather stations to gather near
real-time data on precipitation to improve weather forecasting to support the development of a
drought early warning system for managing the pronghorn population.
Approach:
During the past 30 years, there have been increasing efforts on estimating the spatial distribution
of rainfall to improve flood, drought, and water monitoring and management. Historically,
rainfall has been measured in gauges at point locations and this is generally viewed as the most
accurate representation of precipitation. The measurement of rainfall over large area becomes
problematic when the density of gauges is low and spatial variation in rainfall is high. The
problem has been partially overcome by advances in precipitation estimation using the National
Weather Service’s Next-Generation Radar (NEXRAD), a near real-time estimate of rainfall
calculated from Doppler radar data, and multi-objective analysis, a form of artificial intelligence,
to compliment data from local weather stations.
Weather conditions affect biomass growth across the study area. Variability in weather is not
spatially uniform across the study area. It is also known that small changes in precipitation can
induce significant changes in biomass. Therefore, even in areas where weather variability is
relatively small, the difference may be significant to alter biomass over space and/or time. In
these areas, then, higher spatial coverage of weather stations may be required. In other areas,
weather may vary significantly over space. However, historically, biomass variability in some of
these areas may be relatively small, due to other area specific conditions, such as soil.
Consequently, the siting of weather stations for characterizing weather with respect to biomass is
a multi-objective optimization problem, where weather variability and biomass variability with
respect to weather must be simultaneously optimized. That is, both the variability of weather
over the study area, and in areas where small weather changes induce large changes in biomass,
its effect on biomass must simultaneously be considered in order to optimally site weather
stations. Using historical weather and biomass data for the study area at moderate and fine scale
resolutions, a formal multi-objective optimization problem will be solved to identify the optimal
station locations.
The locations of the measuring stations have significant effect on overall accuracy. Spatial
variables are usually estimated with some variant of the Kriging method, which is a special
weighted least squares estimation process. The method also provides estimation variances which
are the measures of the goodness of the estimates. If several variables are estimated
simultaneously, then estimation variances are provided for all of them, therefore the problem of
finding best observation locations is a multi-objective optimization problem, when the decision
variables are the unknown locations and the objective functions are the goodness measures.
There are several alternative methods by using different heuristics in selecting the best locations
from a large set of possible alternatives. The greedy algorithm is a sequential process, when one
new location is added at each step which results in smallest uncertainty. Sequential exchanges
replace one alternative with another from the alternative set at each step. A branch and bound
algorithm is also applicable, in which both the estimation variances and the number of locations
are used as bounds. There is no theoretical result suggesting which method is the most
appropriate, a part of the proposed research will be devoted to conducting numerical studies and
selecting the best approach based on our experience.
The overall goal of this project is to quantify and forecast precipitation in support of developing a
drought early warning system for the Sonoran pronghorn. The specific objectives are:
I.
Review and compare historical precipitation records from existing weather stations
and NEXRAD.
II.
Establish a network of weather stations to gather precipitation and other essential
meteorological data. AZMET will hire a full time research specialist to handle
the following responsibilities: 1)installation of stations, 2) maintenance and data
collection, 3) calibration and repair of equipment, 4) data quality assessment/control
and 5) dissemination via the internet. The specialist will have access to AZMET’s
calibration and maintenance facilities and will work with existing personnel to
develop a project website. During the first year the weather data will be collected in
a semi-automatic mode by the research specialist following each substantial
precipitation event. The stations, as installed, will have the capability to transmit
data in real time over distance approaching 10 miles using short distance radio links
(requires line of site between station and base station/computer). Conversion of the
network to true real time service will be addressed in subsequent years of the project
and will involve the installation of a base station and necessary repeaters. The
weather stations require a single pole tripod tower bolted to concrete landscape block.
All sensors except the rain gauge will be installed at 2 m above ground level. This is
a standard elevation for agricultural and biological weather stations and makes
installation and maintenance far easier (no need for ladders). An inventory of
sensors will be acquired to facilitate the development of a preventive and
emergency maintenance program.
III.
Use the weather data, NEXRAD, satellite imagery to interpolate the output from the
multi-objective optimization modeling to estimate precipitation within the areas of
interest. The specialist will transfer network precipitation data to project personnel
involved with spatial estimation of precipitation. Estimates of precipitation in the
targeted areas will be provided to assess moisture conditions in areas supporting the
pronghorn.
IV.
Use multi-objective analysis we can determine the optimal number and location of
weather stations to characterize precipitation impacts on biomass production.
Military Benefits:
Establishing and maintaining fully-instrumented climate stations with easy data access provides
the infrastructure required for accurate weather forecasting to support range management
decisions and optimize the scheduling of military operations. In addition, this has the potential to
attract academic and agency researchers that can bring resources and expertise that are beyond
our realistic means, and that support key information needs that help us preserve and protect the
military ranges.
Follow-on Work:
Work in year 1 of the project will focus on the development of: 1) the weather station network
and 2) models that can make accurate spatial estimates of precipitation in support of efforts to
better monitor and manage Pronghorn habitats. Work in subsequent years of the project will
include: 1) developing near-real time data acquisition capability for the weather station network,
2) finding optimal locations of measurement sites and experimentation with alternative
algorithms, 3) adding and/or relocating weather stations to needed or more favorable locations, 4)
validation and refinement of model used to make spatial estimates of precipitation.
Work Description:
FY 2012: $120,000; FY 2013:$120,000.
Primary Personnel:
Paul Brown, Ph.D, University of Arizona,
Ferenc Szidarovszky, PhD, Professor, Systems and Industrial Engineering, University of Arizona
szidar@sie.arizona.edu (p) 520.621.6557 (f) 520.621.6555
Abigail Rosenberg, Ph.D, Marine Corps Air Station Yuma, Natural Resource Specialist
Partners:
Luke Air Force Base, Arizona
Yuma Proving Ground, Yuma, Arizona
The University of Arizona, Tucson, Arizona
Sonoran Pronghorn Recovery Team
Arizona Game and Fish Department
U.S. Fish and Wildlife Service
Cabeza Prieta National Wildlife Refuge
Organ Pipe Cactus National Monument
Kofa National Wildlife Refuge
Imperial National Wildlife Refuge
Cibola National Wildlife Refuge
Tohono O'odham Nation
Technical POC
TPOC Name: Dr. Paul Brown, Extension Specialist, Biometeorology // Supervisor
Organization: The Arizona Meteorological Network (AZMET), University of Arizona
Address: Soils, Water and Environmental Science Dept, Room 429; Shantz Bldg #38
PO Box 210038 Tucson, Arizona 85721
COM Phone: 520-621-1319
Fax: 520-621-1647
Email: pbrown@ag.arizona.edu
Financial POC
FPOC Name: Andrew Hovanec
Organization: Comptroller, U.S. Marine Corps Air Station Yuma
Address: Bldg #980, Shaw Avenue and Quilter Street
COM Phone: (928) 269-2236
Fax: (928) 269-2687
Email: Andrew.hovanec@usmc.mil
Timeline
Sep,2010 - Oct, 2010
Nov, 2010 – Dec, 2010
Jan 2011 – Feb, 2011
Mar, 2011 – Apr, 2012
May, 2012 – Nov, 2012
Coordinate Research Team
Order Meteorological Equipment
Identify Locations for Weather Stations
Research Precipitation Estimation Model
Install Weather Stations, Initiate Data Collection
Finalize Precipitation Estimation Model
Develop Project Website
Continue Data Collection
Generate Precipitation Estimates
Initiate Quarterly Preventive Station Maintenance
Continue Data Collection
Generate Precipitation Estimates
Complete Website For Dissemination of Weather Data
Continue Weather Station Maintenance Program
Develop Plans/Needs For Near-Real Time Data
Acquisition (For Project Year 2)
Figures