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