Project Summary - The Tohono O’odham (O’odham) or the Desert People have occupied Sonoran Desert lands for hundreds of years, and are descendents of the Hohokam, who have been described as the “master farmers of the desert.” According to their creation stories, the O’odham emerged from the earth unto a land with little water.
Living in a land with no permanent streams or rivers, water became a central part of their culture. The arrival of the
Spanish in the late 17 th century introduced livestock. Over the past 200 years, livestock has evolved into an industry that has changed O’odham culture and their relationship with the land. Today, open range livestock grazing has the greatest impact on their land, and while creating jobs and providing food for the Nation, has produced severe negative consequences. Over consumption of natural vegetation increases flooding, soil erosion, and water pollution
(from soil erosion and manure), while decreasing water retention and the natural ecosystem’s ability to support some wildlife. These impacts all pose a threat to the identity and well being of a Nation that has historically lived within the delicate limits of the desert’s ecosystem. Because of animal overstock relative to rangeland carrying capacity, these problems are only expected to worsen, and ultimately will not be sustainable without coordinated and well devised human intervention.
NSF is soliciting proposals that integrate complex interactions among human and natural systems at diverse spatial, temporal and organizational scales. The O’odham culture is linked with their land, water, and creatures that inhabit their lands through both ancient tradition and modern socioeconomic conditions. For this study, the Nation has partnered with the University of Arizona (UA) to develop a comprehensive rangeland pilot project. The project will implement effective management tools for the Santa Rosa Drainage Basin that are in harmony with their age old traditions and values while sustaining agrarian viability. This project will integrate advanced technologies for the evaluation of physical landscape changes from climate variability and anthropogenic influences. The science and technological aspect cannot be successfully integrated without consideration of the O’odham culture, which requires understanding of their rangeland management goals and Tribal livestock management practices. In addition, significant effort will be devoted to transferring advanced science and technology to the Nation, as well as inclusion of young Nation students for nurturing interest and proficiency in science and engineering disciplines.
The primary objective of this project is to improve Tribal self reliance for sustainable range land management through technology transfer and education while respecting and preserving their cultural heritage. By the conclusion of the project, the Tribe will have the information, training, and capability to: 1) archive archaeological studies, oral histories, and written records as well as develop a cultural resources management plan which includes historical education curriculum for kindergarten though community college level; 2) recruit members to pursue science, engineering and math professions; 3) obtain digital elevation and vegetation maps through aircraft image acquisition and flight planning; 4) utilize artificial neural network (ANN) technology for data processing and analysis, as well as modeling and forecasting various system responses of interest 5) forecast drought through satellite image manipulation, interpretation, and other data integration with advanced computational tools; 6) design, construct, and operate low cost Unmanned Aerial Vehicles (UAV) for rangeland monitoring; and 7) establish range management protocols from models calibrated through data assimilation (i.e. SPUR and ANN). The tools and methods developed during this research project will allow the Nation to implement range land management practices and policies that balance livestock sustainability with environmental resources protection. This harmony between man and nature is embedded within the Nation culture, and restoring this balance in conjunction with archiving and education will ensure preservation of this rich and unique culture for future generations.
Integrated Professional Team Qualifications
Dr. Donald Slack, P.E., Department Head, UA Department of Agricultural and Biosystems Engineering, Tucson,
AZ 85721, phone: (520) 621-7230, fax: (520) 621-3963, e-mail: slackd@u.arizona.edu. Dr. Slack has over thirty years of experience in research and education projects. He served as Deputy Program Manager for $25 million project “Research for the Irrigation Support Project for Asia and the Near East (1987-1992),” led by Camp, Dresser and Mckee. His Tadla Resources Management project in Northwest Egypt was aimed at improving natural resources management in this primarily Bedouin region of Egypt. He has also worked with Native American tribes serving as the Principle Investigator for the USDA funded project, “Impact of Alternative Agricultural Practices on
Water and Soil Conservation in the Western Navajo” and another USDA funded project, “Southwestern Indian
Water — Allocation and Use.” He is an associate member of the Southwest Indian Agricultural Association.
Dr. Selso Villegas, Director, Tohono O’odham Nation Natural Resources Department, PO Box 837 Sells AZ 85634, phone: (520) 383-1521, fax: (520) 383-5563, Email: svillegas@tonation.org. Dr. Villegas will manage Task 2 –
Science, Technology, Engineering and Math member recruitment. Dr. Villegas is in charge of several programs that

deal with natural resources, including the Water Resources Study Program, the Range Conservation and
Management Program, and the Cultural Affairs Program. Dr. Villegas is also responsible for providing the framework for the Tohono O’odham Nation’s natural resources management plan.
Peter Steere, Manager, Tohono O’odham Nation Cultural Affairs Program, P.O. Box 837, Sells, AZ 85634, phone
(520) 383-1517, fax (520) 383-3377, Email: psteere@toua.ne.t Mr. Steere will manage Task 1 – the development of a cultural and historical education curriculum for kindergarten through community college level. This will involve the examination of wide variety cultural and historical resources. Mr. Steere has over 30 years of experience in anthropology, archaeology and history, working primarily in the western United States for private companies, Tribal governments, State, and Federal agencies. His Nation responsibilities focus on the identification, preservation and protection of prehistoric and historic cultural resource sites on the O’odham lands. His work includes providing training and educational presentations to Tribal members, State and Federal agencies. Through Cultural Affairs
Program, Mr. Steere has developed a series of cultural sensitivity training sessions for Federal agencies such as the
Border Patrol, Homeland Security the United States Army and Air Force
Tohono O’odham Community College (TOCC) is a two-year that primarily serves the residents of the Nation is seeking its own accreditation. TOCC primarily offers associate degrees for transfer to four-year universities; degrees, certificates, and apprenticeships for direct employment; and developmental education (Adult Basic Education and
GED classes). These Tribal programs are preserving the culture by requiring all students in degree programs to study O’odham language and culture; by starting a program in agriculture and natural resource management; and by reaching out to people across the Nation via distance education and through coursework on topics of special interest such as Tohono O’odham Food Systems and diabetes prevention.
Dr. Susan Moran, Director, USDA ARS Southwest Watershed Research Center, 2000 E. Allen Rd., Tucson, AZ.
85719, phone: (520) 670-6380 X171, fax: (520) 670-5550, e-mail: smoran@tucson.ars.ag.gov. Dr. Moran will manage Task 3 - the digital elevation and vegetation mapping; and Task 7 – the establishment of range management protocols from SPUR modeling. Dr. Moran’s research goal is to understand the effects of changing climate, land use, and management practices on the hydrologic cycle, soil erosion processes, watershed resources, and to develop prototype decision support systems for natural resource models. Her areas of expertise include: evaluating energy balance and water balance by combining remote sensing and simulation modeling at local, regional and global scales; the detection of physical and biological stress in vegetation using direct and remote means; theoretical and practical aspects of spectral reflectance, thermal emittance, and radar backscatter from crops and rangelands; inflight calibration of satellite-based sensors; merging optical and radar remote sensing techniques to enhance estimates of surface evaporation and soil moisture; and the development of a remote sensing/modeling approach for rangeland management.
Dr. Alfredo R. Huete, Professor, UA Department of Soil, Water, and Environmental Science, 429 Shantz Bldg. #38,
Tucson, AZ 85721. Phone: (520) 621-3228; fax: (520) 621-1647, email: ahuete@ag.arizona.edu. Dr. Huete will manage Task 5 - drought forecasting through satellite imagery. His research has focused on the development and use of space-based remote sensing to study vegetation – climate interactions in arid and semi-arid ecosystems. He uses moderate resolution (MODIS) time series analysis to monitor seasonal and spatial variations in biologic activity and net primary production as a function of land cover, precipitation and water availability, and drought susceptibilityHe also has worked extensively to advance the use of remotely-sensed drought indices to improve the prediction of vegetation health in response to climate change and/ or land cover modifications, and to spatially map water-use efficiency relationships across and within biomes to identify potential mechanisms (e.g. soil water holding capacity) underlying variation in ecosystem sensitivity to precipitation. He is a member of the MODIS Science
Team (1991- present) and is responsible for the development of terrestrial vegetation products for calibrated time series analysis aimed at assessing climate-related and land use change influences on carbon, water, and nutrient cycles, photosynthesis, and plant health status over the global range of biomes. He was also a part of the EO-1 science team in which he used AVIRIS and Hyperion data to analyze and develop land surface moisture indices for hydrologic and carbon applications and for scaling and inter-sensor continuity studies. He is also on the scientific advisory team for the next generation of the national polar orbiting environmental satellite (NPOESS) and hyperspectral carbon/water sensors (SpectraSat).
Dr. Hermann F. Fasel, Professor, UA Department of Aerospace and Mechanical Engineering, 1130 N. Mountain,
Tucson AZ 85721, phone: (520) 621-2771, fax: (520) 621-8191, email: faselh@u.arizona.edu. Dr. Fasel will be

responsible for Task 6. Dr. Fasel has over thirty years of experience in Aerospace Engineering Research. His PhD advisor (R. Eppler) was a world renowned expert in small aircraft aerodynamics, such as for small UAVs. Dr. Fasel is internationally recognized for his pioneering research in Computational Aerodynamics and Fluid Dynamics. His research has been and is currently funded by Federal government agencies and private corporations. Examples of these funding agencies include: the Department of Defense, the Air Force Office of Scientific Research, NASA,
Army Research Office, Office of Naval Research, ,DaimlerChrysler and the Boeing Company. Directly related to theproposed effort is his past development and flight testing of a UAV for the United States Air Force and this current participation in the development and flight testing of a long endurance UAV (also for the Air Force; in subcontract to The Boeing Company). His UAV expertise will be crucial for developing and operating an UAV based system for on-demand aerial imaging for range land management.
NOAH, L.L.C. 610 Lawrence Road, Lawrenceville, N.J. 08648, phone: (609) 434-0400; fax (609) 637-0533, email: emerynoah@comcast.net. NOAH will address Task 4 with some overlap into Tasks 5 and 7 – the applications and integrating of ANNs into drought forecasting and rangeland management. NOAH is one of the few consulting firms in the world that specializes in applying advanced modeling methodologies to complex engineering and environmental management problems. In 2004 the company was awarded a prestigious Small Business Innovative
Research grant by the EPA to develop a “smart security” system that combines artificial neural network and formal optimization for monitoring and protecting water distribution systems against biochemical attack. NOAH will also be working with the USGS in the area of source water protection using ANN technology. The company is also under contract with the New Jersey Department of Environmental Protection to develop an ANN methodology for forecasting algae blooms in surface water systems. Company principals have over 20 years of combined experience in ANN technology and its applications to science and engineering problems, including remote sensing data processing and physical system modeling.
Figure 1: Vicinity Map Tribal Background - The Tohono O’odham Nation
(Nation) is a sovereign government and home to approximately 25,000 people living in more than 60 communities, with the tribal capital city of Sells constituting the largest. The major sources of employment for its citizens include tribal and government services, cattle ranching, farming, and self-employed artisans.
An elected chairperson and tribal council govern the
Nation. There are 11 legislative districts, with representatives from each district elected to the Tribal
Legislature. Each local district functions as a local government entity, with elected representatives from the local community serving on District Councils.
Major decisions affecting the Nation are referred back to the District Councils for consideration by local community members and representatives. Major decisions affecting the Nation are also addressed in the District Councils with the participation by local community members and representatives.
The Nation is located in south central Arizona approximately 70 miles southwest of Tucson (Figure
1). The Nation encompasses 2,848,989 acres of
Sonoran Desert habitat, and includes three smaller reservations geographically separate from the main reservation. These include the 71,000-acre San
Xavier Papago Reservation, the 10,400-acre the Gila
Bend Papago Reservation, and the 43-acre Florence
Papago Reservation.

The southern part of the main reservation shares approximately 70 miles with Mexican border, extending some 60 miles north. The east boundary is defined by the crest of the Baboquivari, Roskruge, and Sawtooth Mountain ranges.
The western boundary extends to the Ajo range and upper reaches of the Lower Colorado River Basin. Elevations range from 7,688 feet on Baboquivari peak to elevations averaging 1,850 feet in the lowest areas of the Colorado
River Basin. The Nation has contiguous boundaries with other federal lands, including Organ Pipe Cactus National
Monument, the Bureau of Land Management, Barry Goldwater Air Force Range as well as significant State of
Arizona and private land ownership. The world renowned Kitt Peak Observatory, home to some 25 major telescopes operated by the National Science Foundation in association with major universities, is located on leased tribal land on top of Kitt Peak in the Baboquivari Mountains. The remote location and 7,000 feet of elevation provide for scientific observation of the sun and universe unobstructed by urban air and light pollution.
Figure 2 – Santa Rosa Basin
Santa Rosa Drainage Basin - As presently defined, the
Santa Rosa drainage basin has a north-south extent of about forty-two miles, and an east-west extent of about
18 miles. Surface waters enter the western side of the
Santa Rosa Drainage Basin and from the south. Little or no surface flow enters the Santa Rosa Basin from adjacent basins to the east. Santa Rosa Wash is the largest drainage way in the Basin, and all other drainage ways are tributary to the Santa Rosa Wash. Formerly,
Santa Rosa Wash flowed north beyond the boundaries of the basin to eventually become tributary to the Gila
River. Now, however, the wash ends at the upgrade side of a dam in a partly constructed basin. Neither
Santa Rosa Wash nor its tributaries are gauged and the average annual discharge of the watershed is unknown.
Flooding problems for the Nation, however, have increased over time with loss of vegetation due to overgrazing, and in some cases have caused serious structural damage.and threaten loss of live.
Temperatures: The Nation’s Sonoran Desert ecosystem is defined by hot arid climate with summer temperatures frequently above 100°F. The mild, sunny winters have a low occurrence of freezing temperatures, creating a unique cacti environment unsurpassed by other North American deserts. An average of 154 days per year occurs with temperature above 90°F. Winter temperatures average 52°F; with daytime temperatures averaging 67°F and minimum temperatures averaging
38°F. There is an average of 22 days a year with temperatures below freezing
Precipitation: Precipitation occurs as a bi-modal moisture regime characterized by two distinct seasons of moisture input. In winter, rains typically occur with low-pressure continental gradient winds that carry moisture from the
Pacific Ocean and deposit an average of 5.5 inches of rain near Sells as the winter storms pass over the desert. The monsoon rains typically occur in July and August. Monsoon rains contribute an average 5.9 inches to the total annual precipitation average of 11.9 inches, providing almost half of the annual total during the months of July and
August.
Hydrology: Surface waters, when present, typically transport large amounts of sediment, but aside from agricultural run off, there are no known sources of surface contamination. Groundwater flow direction is basin-ward from the adjacent highlands and then to the North. The groundwater basin is open to flow from the Gu Oidak groundwater basin to the south, but has limited outlet to the north because of an elevated low permeability bedrock divide in the subsurface. Relatively little groundwater flow occurs from or to groundwater basins to the east and west.

Santa Rosa Drainage Basin depth to groundwater ranges from 150 feet to nearly 400 feet, and generally increases from north to south. Water quality is generally good, except in the central portion of the basin. This area has a high arsenic concentration that frequently exceeds EPA’s maximum contaminant level for arsenic in drinking water.
Local sources of groundwater contamination include past and present mining sites. In particular, the Cyprus Tohono
Mine is identified by the EPA as a source of groundwater contamination by sulfates and uranium. A serious concern, however, is the possibility of increased recharge of surface contamination due to increased erosion and run-off. In addition, manure from the livestock represents a source of coliform contamination to the groundwater supply, which provides potable water to both public and private wells.
Geology: The Santa Rosa Basin is a depressed crustal segment trending south to north that has been filled with sediments from adjacent mountains to depths exceeding 4000 feet. These sediments are a complex assemblage of basin-fill sediments ranging in age from early Tertiary to Recent. It is frequently observed that the oldest of these sediments are offset by basin-range faults. The basin-fill sediments terminate fairly abruptly against bounding faults along the eastern and western mountains.
Biodiversity: Riparian vegetation communities, although not extensive on the Nation, are found along the ephemeral stream washes in mountain canyons and lowland washes. Montane riparian communities consist of broadleaf deciduous trees and shrubs, including sycamore (Platanus wrightii), Arizona walnut (Juglans major), Arizona ash
(Fraxinus velutina), netleaf hackberry (Celtis reticulata), Mexican alder (Alnus oblongifolia), and various oak species (Quercus spp.). Lowland washes host well developed riparian communities in some locations, with stands of
Fremont cottonwood (Populus Fremontii), desert willow (Chilopsis lineraris), black willow (Salix gooddingii) and dense mesquite woodlands. Many of these lowland riparian communities are in poor condition due to drought, underground water overdraft, Tribal development, and grazing impacts. A survey of the Nation’s biodiversity is limited. The project will work in partnership with the U.S. Fish & Wildlife Service, TOCC and various districts to inventory and map the vegetation in the Santa Rosa Drainage Basin.
Rangeland Management - The Nation’s Range Conservation and Management Program (RCMP) is a fairly young program, contracted from the BIA Papago Agency in January 2001. The RCMP priority is to improve the rangeland health and resources. Several objectives must be met to achieve this goal, including: a complete vegetative inventory, adoption of a Livestock Ordinance, adoption of a Range Code, an inventory of all the livestock on the
Nation and an inventory of all the infrastructures serving these livestock. The Natural Resources Conservation
Service, Sells Field Office has been on the Nation since 1987 and has worked with the Nation and several of its eleven Districts. The Livestock Ordinance and Range Code was initiated in 1985 by the Legislative Council and
BIA but never adopted, the last hearings and review was completed in 1997.
The most recent livestock inventory conducted by the BIA was in 1984 via airplane survey. A total of 17,490 cattle and 2,652 horses were inventoried, for a total of 21,472 animal units per year. This field reconnaissance method has an expected error of ± 10% to 15%. The last vegetative inventory completed to establish the rangeland carrying capacity for the Nation was in 1975. The total carrying capacity for the Nation from this inventory was 10,558 animal units per year. Thus, the projected difference between the rangeland carrying capacity and Tribal animal units produces an overstock estimate of 10,914 animal units. Livestock inventories and carrying capacities have recently been completed for two Tribal districts, the two ranches. The RCMP staff has initiated the vegetative inventories in two additional districts. The data collected during these inventories is currently being analyzed by the
Nation’s RCMP staff.
Historical and Cultural Summary - The O’odham traditionally spent the winters in villages near wells or permanent springs in the mountains. At other times of the year, they settled in other villages adjacent to fields where they and cultivated desert adapted varieties of corn, beans, squash, cowpeas and melons. These resourceful farmers utilized runoff from monsoon rains by building dams at the mouths of arroyos to divert water for flood irrigation onto adjacent fields. They planted in July or August when the fields were wet and harvested in October or November.
The O’odham supplemented their crops with wild plants from the desert such as prickly pear fruit and pads, mesquite, agave, amaranth, acorns, cholla buds, and saguaro fruit. They hunted animals such as deer, bighorn sheep, doves and rabbits. The Sonoran Desert is the only region in the world where the saguaro cactus grows. The saguaro is a sacred plant to the O’odham. Their ceremonial year begins with the ripening of the saguaro fruit. A sacred

ceremony with the saguaro fruit and wine were performed to bring rain for their crops. In earlier generations,
O’odham men made an 8-day pilgrimage to the Gulf of California to seek the ocean wind to bring rain.
The arrival of the Spanish in the late 17 th century brought a new crop, winter wheat, and livestock that dramatically changed the O’odham agricultural systems. Water, always important in O’odham culture for agriculture, became important for the development of the livestock industry that dramatically impacted their land. Increasing large
Anglo cattle herds moved onto traditional lands after the Civil War and prior to the establishment of the reservation.
Violent disputes over water sources between O’odham cattleman and Anglo cattleman were common in the late 19 th century. In the early 1900s, numerous wells and charcos were constructed with government programs that increased available water to support the development of larger cattle operations.
Innovative Use of Technology
Though the main O’odham reservation was established in 1916, the Tribe did not take control of their Range
Conservation and Management Program until 2001 from BIA Papago Agency. Now in conservation leadership positions, the Nation actively take into consideration traditional practices. The Tribe understands the complexity of its communities, livestock practices, and the condition of their lands. Their drive to balance economic development with natural resource conservation will result in a more effective management program than previous efforts imposed by government agencies or outside entities.
By the conclusion of the project, the Tribe will have the information, training, and capability to: 1) develop cultural and historical education curriculum; 2) recruit members to pursue science, engineering and math professions; 3) obtain digital elevation and vegetation maps; 4) implement ANN technology for data processing, analysis, modeling, and forecasting; 5) forecast drought through satellite image manipulation; 6) design, construct, and operate low cost
Unmanned Aerial Vehicles (UAV) for rangeland monitoring; and 7) establish range management protocols with
SPUR and ANNs. The educational, science, and technological approaches to address these objectives, their intellectual merit, and information dissemination are provided here.
Task 1) Cultural and Historical Educational Curriculum
The traditional lands of the O’odham contain archaeological records documenting continued human occupation for over 10,000 years. These records span from the Paleo Indian cultures that focused on the hunting of large mammals such as mammoth and mastodon, to Archaic hunters and gatherers that date back nearly 8,000 years, to early agriculturalists who settled down in more permanent villages with canal-based agricultural systems around 2,000 years ago, to the Hohokam culture which developed and flourished from approximately A.D. 500-1400.
The agrarian and hunting ways of the O’odham dramatically changed with Spanish and Anglo migration on to their land. Over the past 50 years, urban development from adjacent cities and O’odham migration off the Reservation has dealt a strong blow to O’odham language, culture and beliefs. Sadly, with the passing of Tribal elders, the historical accounts of traditional ceremonies, family lineages, land transformations, and the O’odham language may be lost forever, depriving future generations of a wealth of cultural and historical treasures.
This project will partner with the Tohono O’odham Cultural Affairs Program and TOCC to facilitate the preservation of O’odham culture and tradition. The project will assist these Tribal programs in fulfilling their Tribal responsibilities by summarizing archaeological studies, developing a cultural resources management and protection plan, and providing cultural education workshops for the Nation. The development of a curriculum will include materials on prehistory and history for kindergarten through community college levels. The collection of information from various sources will depend on the funding available and information accessibility. Historical and cultural sources and records will include: a) Oral Histories collected by both the O’odham and Anthropologists over the past 100 years. As appropriate, information from present day storytellers will also be collected. b) Structured interview with elders on issues relating to livestock, agriculture, climate, rainfall and other ecological issues c) Spanish Colonial Period documentary records d) Mexican Period documentary records e) Published books and articles by O’odham, anthropologists and archaeologists f) Government Records in the National Archives from the Sacaton and Papago Agencies

g) Scientific data collected from weather stations on wind, rain and other drought related data h) Review of historic photographic collections from the 1870s-present to document visual changes – example the UA Humphrey Range Photo Collections
Task 2) Recruitment of Members Pursue Science, Technology, Engineering and Math Professions
The American educational system has been heavily criticized on how it is preparing students to enter into an increasingly technology-based workforce. The U.S. Department of Commerce projects more than one million new technology related jobs available will be available by 2005 (Dietz, 05/98). With less Americans pursing engineering and computer related bachelor degrees, the Department of Commerce predicts a critical shortage of qualified workers (Dietz, 05/98). These discrepancies are more evident among Native American populations. The Native
American population must cope with a number of unique personal issues that undermine their confidence and competence in science, technology, engineering, and math (STEM). This impacts their curriculum choices in high school, narrowing their career and college academic program options, and ultimately diminishing their role and influence in the future workforce as well as Tribal matters. Although Native Americans have made great strides in improving their performance completing Bachelor, Master’s and Post Doc programs, there is new gap emerging related to science, engineering, computers and technology.
On the Nation, only 52% of young adults complete high school, with only 5% pursuing advanced degrees. Most young Tribal members seek employment opportunities in public services and construction, and those who earn advanced degrees pursue professions in accounting and business. Only a fraction of these graduates pursue degrees in science, technology, engineering and math. The Nation is pursing an active role in recruiting Tribal members with the establishment of TOCC in 1998. The project seeks partner with TOCC, Tribal schools, the Colleges of
Agriculture, Engineering, and Education to focus on improve STEM education for Tribal schools and TOCC. The project builds on an established industry and academic partnership that demonstrates the latest technologies and emphasizes social and family connections. The projects educational workshops and activities will include: a) Sponsoring STEM-based tours of UA’s College of Agriculture, Engineering and Mines, Education, and
Mathematics The Department of Aerospace and Mechanical Engineering will take advantage of existing collaborations in UAV research by coordinating field trips for interested students from Tohono O’odham
Nation to their established partners, for example, Raytheon, Lockheed Martin, and Advanced Ceramics
Research; b) Establish an Aerial Robotics Club that will introduce Tohono O’odham Nation students to new dynamic technologies such as of 3-D computer modelling, composite materials, CNC machining operations, and general fundamentals of Mechanical and Aerospace Engineering c) Increase STEM competence of program participants through the use of various computer programs (i.e.,
SolidWorks, ™ Fused Deposition Modeling, Computer Aided Design CAD), and rapid prototyping and d) Encourage increased parental/guardian participation in their children’s education; e) Recruit and hire high school and college students interested in science and engineering careers to assist in completing project tasks.
Task 3) Digital elevation and vegetation maps
Accurate representation of watershed topography and above ground vegetation are critical to adequately model and predict watershed storm response, erosion, sediment transport, and vegetation transpiration (USDA-ARS, 2003).
Airborne scanning laser altimetry (LIDAR) has proven useful for multiple hydrologic applications including deriving fine-resolution digital elevation models, estimating surface aerodynamic roughness, detecting microtopographic differences, measuring the height of growing vegetation, determining canopy cover amounts, measuring the density of stems and branches versus leaves, measuring soil erosion losses, and providing quantitative inputs to hydrologic, erosion, irrigation, and rangeland models. The LIDAR, which can be tailored to fly on both helicopter and fixed-wing aircraft, is a powerful tool for applications in range and watershed management. The technology has been successfully tested at a site very similar to Nation, the Walnut Gulch Experimental Watershed in southeast
Arizona (Goodrich et al., 2003). A digital elevation model at 1-m resolution with vertical accuracy of 10 cm was produced, along with a map of vegetation height and volume with similar resolutions. The LIDAR system deployed for this application is available for cooperative research agreement with the University of Florida, Center for
Airborne Laser Mapping. Scientists from this center have proven the application of LIDAR products for mapping spatially distributed floodplain topography and vegetation heights and for river flood inundation prediction (Mason et al., in press; and Cobby et al., in press). The project will provide informal LIDAR mapping workshops and

training to Tribal Natural Resources Department, Council and schools. The LIDAR specifications we would propose for this project are 300 m swath width, 600 m flying height, and point spacing on the ground of 1 m. The products will be ortho-rectified and geo-referenced with processing to contain surface pointes and the bare earth points to aid in estimation of vegetation height and volume. The coverage will be the size of the Santa Rosa Wash Watershed which covers approximately 650 square miles.
Deliverables include: a) At least 300 m swath width b) 600 m flying height c) 33,000 pulses per seconds d) Point spacing on the ground ~1m e) Each pulse will have GPS time, X,Y,Z, and intensity for first and last returns (stops) f) Horizontal datum: NAD83: Spheroid: GRS 80, UTM, Zone 12 g) Vertical Datum: NAVD88 or NGVD29, Orthometric height using GEOID96 or GEOID99, Absolute vertical accuracy (10-20 cm) h) Ortho-rectified and geo-referenced color (or IR) digital photography (pixel size ~18 cm) i) Processing to include raw data plus ASCII text files of tiled files containing first surface points and the bare earth points to aid in estimation of vegetation ht and volume j) Coverage: Size of Santa Rosa Wash Watershed is 442,000 acres or 656 square miles.
Task 4) Artificial Neural Networks
Artificial neural network (ANN) technology, a form of artificial intelligence, is a compelling alternative to the other modeling approaches, such as physical-based numerical models and statistical methods (Coppola et al. 2003a, b).
An ANN, through proper development and training, “learns” the system behavior of interest by processing representative data patterns through its architecture. What sets an ANN apart from a physical-based model is that because it does not rely upon the governing physical laws (e.g. Conservation of Momentum), information regarding physical parameters is often not required for its development and operation. That is, the ANN does not require often difficult to measure model parameters that may vary significantly over space and/or time, nor is it limited by simplifying physical and/or mathematical assumptions that have to be applied in reasonable physical-based and statistical models. Instead, ANNs are based on actually-measured input-output data, and are adept at modeling both linear and non-linear phenomena (Kolmogorov’s Theorem). Consequently, ANNs have been used with great success in a diverse number of environmental applications, such as estimating biomass and soil moisture content on the basis of remote sensing data.
A variety of ANN models, consisting of different architectures (e.g. number of hidden layers, nodes, input variable and output variables, etc.) and types (e.g. radial basis, multiperceptron etc.) will be developed and tested for the different applications. It may be most appropriate to use multiple models for the same application; for example, real-time forecasting of drought conditions over different time horizons. In addition, it is possible that different models consisting of different sets of input variables may be developed for the same forecasting problem. For example, some models may utilize aerial reconnaissance, but depending upon the real-time availability of this data, other models that don’t use this information should be available. This “redundancy” will provide the Nation with a number of feasible models that can be used either simultaneously, when data and conditions exist, or in lieu of each other. Sensitivity analyses conducted with the ANN models will also help identify important predictor variables, which can help optimize data acquisition strategies that increase model performance for assessing and forecasting system states of interest.
An important issue addressed in this research is the development of ANN forecasting models that perform effectively used in real-time conditions. Many ANN models presented in the literature are often developed and tested using historical data only. For example, because drought forecasting depends not only on known conditions, but future conditions (e.g. weather) characterized by inherent uncertainty, the models must be tested in real-time conditions, and, as necessary, modified. It may be found that certain variables when known a-priori significantly improve ANN performance in terms of accuracy. However, under real-time conditions, because of their inherent uncertainty in space and/or time, some of these variables may be poor predictor variables. A critical component of this project, then, will be adapting the models to real-time conditions.

In this project, ANN’s will be applied to a number of challenging forecasting and management problems, including processing and interpretation of remote sensing data, drought estimation, drought forecasting, and vegetation responses to natural and anthropogenic factors. Equally important, Nation personnel will be trained in the general use of the technology, so that in addition to its sustained application to the above mentioned problems, the Nation can use it in the future for new applications, such as flood forecasting, water resources management, etc. Integration of the Nation into the ANN modeling work early in the project will ensure their mastery of the technology.
Deliverables: a) Train Nation personnel and students in background and use of ANN technology. b) Work with Nation personnel and students during development and testing of ANN models for different applications to ensure proficiency in ANN modeling protocol and software implementation. In addition,
Nation personnel will be essential for identifying possible model inputs, as well as model performance expectations. c) Process remote sensing data using ANNs for classifying different land characteristics and conditions, such as vegetative cover type, drought indices, etc. d) Develop and test ANN models for drought estimation and forecasting under real-time conditions using different input variable sets. e) Develop ANN models for estimating and forecasting vegetative responses to natural and anthropogenic factors under real-time conditions using different input variable sets. f) Use ANNs to conduct sensitivity analyses to help quantify cause and effect relationships between different predictor and prediction variables, thereby refining system understanding, improve model development (both ANNs and process-based), and optimize data collection strategies.
Task 5) Drought Forecasting
Various satellite-based vegetation health and drought indices have been developed and successfully applied to measurements of production anomalies, indicative of above- or below-normal rainfall conditions (Huete et al. 2002).
However, differential sensitivities of production to inter-annual variability in precipitation have been reported as life history, land use, land cover changes (e.g. degradation, invasive), soils, and biogeochemical mechanisms can interact to influence the production response of arid ecosystems to precipitation (Ehleringer et al 1991; Golluscio et al. 1998). The ecological attributes of species (e.g. woody vs. herbaceous) present in the vegetation assemblage can further influence production potential as a result of constraints on growth rate and stress tolerance (Jackson et al.
2001). These complex feedback relationships involve extensive accumulations of historical and present datasets, including land management practices, household and ranching cultural information, meteorological data, and satellite data sets. Artificial neural networks (ANN) and data mining are ideal techniques to handle such large and disparate datasets. We intend to implement these ANN techniques to understand how human and desert rangeland systems interact under variable climate and water availability conditions. An important task of historical, temporal, and spatial remote sensing data (at a range of scales and resolutions) is to make sure the appropriate information becomes input to the ANN models.
ANNs have been demonstrated to excel in applications where remote sensing and complementary land coverage information are integrated (Kimes et al. 1998, Linderman et al. 2004, Jiang et al. 2004). The remote sensing data used in this project will include satellite imagery and data collected via the airplanes, as well as GIS information.
The ANNs can then utilize dynamic input variables, such as multi-year satellite NDVI, geospatial data such as topography, soils, land cover, and climate products involving PDO, ENSO, and other climate phenomena. Using these data, ANN models will be developed, tested, and improved to predict vegetation response to various controlling agents (e.g. rainfall) and disturbance over spatial and temporal scales of interest. In this way, the Nation will have a modeling tool for assessing and forecasting vegetation responses over different time and spatial scales for assistance in rangeland management.
One important and crucial measure of water-vegetation dynamics is precipitation use efficiency (PUE) that describes the production achieved per unit amount of precipitation. PUE has been found to vary across range cover types, due to differences in vegetation physiognomy (structure) and/ or soil, temperature, and biogeochemical constraints.
Vegetation constraints influence the impact of precipitation on biological activity in a manner that can increase with decreasing precipitation. At sites with low precipitation, high efficiency of water use associated with individual plant growth rate is translated to high efficiency of water use at the larger ecosystem level. However, when water is

most limiting (drought periods), all land cover types may exhibit the same rate of maximum biomass production per unit rainfall, regardless of land cover conditions and a maximum PUE may exist. Sites with low production potential would have a mean PUE close to PUEmax, whereas higher productivity areas would have mean PUE that can deviate significantly from PUEmax. Thus, the relative control of water on productivity is a function of overall
PUEmax coupled with the dynamic nature of multiple limiting resources, such as temperature.
Our understanding and predictions of future range ecosystem behavior and land cover practices, including drought severity and degradation, thus should account for PUE and PUEmax. The PUE/PUEmax concept can be tied directly to surface hydrology and provide information on historic forage availability, rangeland carrying capacities, as well as provide measures of current vegetation-climate equilibrium states and future vegetation responses to changes in water availability. PUEmax provides an upper boundary condition of maximum biomass accumulation per unit rainfall and PUE/PUEmax relationships coupled with remotely-sensed drought indices, such as the vegetation condition index, provide a mechanism in which spatiotemporal variability in water availability and/ or precipitation may be retrieved.
The primary goal of this phase involves the use of satellite data to monitor and better understand rainfall interactions with rangeland production and water availability. Specific deliverables include: a) Provide formal instructions and training to Tribal Natural Resource Department in the utilization of satellite data for predicting rangeland production. b) Partner with the community college to develop lesson plans in remote sensing technologies with respect to rangeland management. c) Quantify and map the spatial and temporal patterns of range production sensitivity to precipitation (using
MODIS/Landsat/ and AVHRR); d) Contrast production/ precipitation relationships across and within major range units to identify potential mechanisms (e.g. soil water holding capacity) underlying variation in sensitivity to precipitation; e) Evaluate the relationships between current and potential PUE with remotely-sensed drought indices in order to improve the prediction of vegetation health in response to climate and human management practices/modifications.
Expected Outcomes and Deliverables: a) Primary rangeland production (forage) time series data records for the AVHRR and MODIS sensors. b) An assembled time series of inter-annual and seasonal phenology profiles for all the major land cover types on the Nation. c) Mapping and assessments of patterns of change in the spatial and temporal sensitivity of forage production to annual precipitation, including identifying sites and areas of greatest vulnerability to drought and sensitivity to grazing. d) Analyses of the relationship between historical forage availability and grazing pressure on these rangelands, from the AVHRR time series. e) Calibration of ANN’s to historical AVHRR (1981- present) and current MODIS satellite data (2000- present) to predict antecedent conditions preceding drought events. f) Improved, linearly scaled drought measures (AVHRR & MODIS) that account for hot desert behavior and variability. g) Interfacing of remote sensing range health and productivity with ANN models.
Task 6) Monitoring of Rangelands Using Unmanned Aerial Vehicles (UAV)
In comparison to other available satellites, AVHRR and MODIS are available at no cost, pass every 1-2 days, and have set spectral bands with coarse, spatial resolutions ranging from 0.25 km to 1 km. These data sets are useful for monitoring purposes as they generate continuous seasonal and year-to-year data, but their use requires extensive training in image retrieval and processing. On the other hand, very high resolution satellite datasets are very costly and site reconnaissance (i.e., imaging) via manned aircraft costs considerably less. Aircraft-based imaging, by comparison, can be scheduled, have no weight restrictions, but requires specialized training (i.e., pilot). A low cost alternative to satellite and manned aircraft reconnaissance are low altitude flying Unmanned Aerial Vehicles
(UAVs). Technology advancements in sensors and avionics have dramatically reduced instrumentation size and

cost. UAVs are low risk (i.e., no pilot), provide very high resolution imaging and, because of their low cost, enable monitoring at frequent and regular intervals.
The project team includes the UA Department of Aerospace and Mechanical Engineering (AME), who will implement a robust and automated autonomous UAV system which will constitute a tool for increased monitoring of land transformations at frequent and regular intervals. Recent developments in GPS (Global Positioning System) based avionics allows UAV rangeland monitoring to operate entirely autonomously. GPS based avionics and advances in engine technology, make it highly feasible to implement long endurance UAVs (flight duration more than 24 hours if desired). The Tribal - UAV team will develop a highly automated system for flight operation, gathering, retrieval, and data and image processing. With proper training in operation and maintenance, the Nation will have control of when, where, how often, and what they wish to monitor, and they can validate and spot-check on the quality of the satellite data.
The proposed UAV will be a fixed wing airplane of medium size (approximately 7 ft. span) to ensure easy transportation and handling. The plane will be designed with a relatively high wing loading so that it can be safely operated even in adverse weather and wind conditions. Employment of GPS avionics and autopilot system after launch will allow for entirely autonomous reconnaissance missions. In a typical monitoring mission, the desired flight pattern is uploaded to the UAV autopilot memory via a laptop computer. Remote sensing data (i.e., spectral and video) will be transmitted in real-time from the airplane to the ground station for immediate processing. This real-time data acquisition and transmission is unlike typical satellite or manned aircraft remote sensing, where the data transfer is delayed, or stored onboard on a mass storage system for post-processing, or some combination thereof. Upon completion of the mission, the UAV will be recovered by a parachute system that is triggered autonomously from the GPS based autopilot. In addition, this parachute retrieval system will be automatically deployed in case of catastrophic failures of crucial UAV components to minimize risks of human injury and damage of UAV or property. The GPS based system will continuously report UAV location in flight and upon landing.
AME has extensive experience in developing and operating UAV technologies. AME has developed these technologies for the annual International Aerial Robotics Competition with considerable success. Financial and technical support is provided by companies that specialize in the development and production of UAVs. The project will develop training and educational programs to introduce these technologies and by coordinating field trips to existing industry sponsors.
Task 7) Develop Range Land Models for Establishment of Range Management Protocols
O’odham livestock have always been managed by O’odham communities on the open range. Each community appoints a Range Boss who organizes round-ups in his area, acts as a village representative for round-ups in other communities, and keeps track of brands and brand owners from his community. In the past, members from different communities organized round-ups on horse back in various areas throughout the reservation. These involved the shawunth (chasing method) and wiilantas (trapping method) that usually lasted for more than a month. These required a number of cowboys and provided effective control methods since there were more individuals that ensured effective handling. Today only a few areas continue this practice. With fewer cowboys, the cattle find it easier to escape by hiding in dense mesquite bosques. In turn, cattle become more aggressive with fewer cowboys available to manage these herds.
With migration off the reservation and with more employment opportunities available, there are fewer young members interested in livestock management and production. This presents a challenge for existing livestock owners. The Nation recently participated in the “Western SARE Range Curriculum Project” funded through the
USDA. The program partners included: the Tohono O’odham Natural Resources Department, TOCC, the UA
Cooperative Extension Program, and USDA Natural Resource Conservation Service. These partners coordinated educational workshops on range management and examined the social benefits of this outreach effort. This project will continue to work with the Nation by: a) Addressing the challenges associated with communal land use; b) Coordinating educational workshops and training on basic ecology, such as the relationships between weather patterns, plant growth, land use, and soil erosion practices; c) Providing educational opportunities to younger members in natural resource and livestock production to assist them in future Tribal leadership roles;

d) Assist in the communication between ranchers, grazing community members and Tribal natural resource and conservation programs; and e) Assist in the integration of simulation models and imaging for science based range management.
Effective range management depends on high quality information about and understanding of the nature of the range resource. Simulation modeling provides a link that applies our best scientific understanding to available data, such as high temporal frequency remotely sensed data, to deliver results. Model results help to monitor current conditions that can’t be easily or frequently observed, such as the health of grass root systems. Model results also predict the effects of different management options, such as stocking rate levels, on rangeland resources. The fundamental result of the simulation modeling process is our improved understanding of the interactions of climatic, landscape, and human-directed processes in rangelands. SPUR (Simulation of Production and Utilization of Rangelands) is an established, process-based model that will enable Tohono O'odham Nation to understand, monitor, and predict range processes and management outcomes.
Rangeland simulation models are necessarily simplistic compared to on-the-ground vegetation dynamics. For example, there may be only a small number of key species or plant functional groups, which is a simplification of the real plant diversity on the landscape. Nonetheless, these models provide useful information about vegetation dynamics and assist in the calculation of stocking rates. Finally, these models have been used most often in higher precipitation zones with higher vegetative production. This project will test the performance of the SPUR model on
Tohono O’odham Nation lands with lower productivity and higher variability
The process-based SPUR model is driven by climate inputs and predicts daily changes in plant growth and mortality, soil moisture, and grazing animal intake and production, with interacting subcomponents for hydrology, soils, vegetation, livestock, and wildlife (Carlson and Thurow, 1992; Teague and Foy, 2002). The model can be run for a single location (field scale), or for average conditions over a larger area such as a watershed (basin scale).
Biophysical inputs include climate (daily temperature and precipitation), vegetation ecophysiological parameters for species or functional groups, and soils information. Additional optional inputs include specification of livestock and wildlife populations and intake preferences. The field scale version of SPUR has been revised and upgraded several times by researchers (Carlson and Thurow, 1992, 1996; Hanson et al., 1992; Foy, 1993; Foy et al., 1999; Pierson et al., 2001). The Colorado Beef Cattle Production Model and a steer model were added for livestock economic analysis (Hanson et al., 1993); parts of the CENTURY model (Parton et al., 1987, 1988) were incorporated for carbon and nitrogen cycling (Foy, 1993; Foy et al., 1999); and the hydrology and erosion components have been modified to incorporate process-based hydrologic models (Pierson et al., 2001). In addition to the facility at USDA-
ARS Southwest Watershed Research Center (Tucson, AZ), researchers at a number of locations have ongoing
SPUR-related programs, including sites at USDA-ARS Northern Great Plains Research Laboratory (Mandan, ND),
Texas A&M Agricultural Research and Extension Center (Vernon, TX), and USDA-ARS Northwest Watershed
Research Center (Boise, ID).
This project will use SPUR and SESPUR (the spatially explicit implementation of SPUR; Skirvin and Moran, 2003) models for evaluating rangeland management options as well as ecosystem modeling. Land managers can modify stocking rate, livestock forage preferences, timed grazing systems, forage intake, and production (Foy et al., 1999).
Enterprise-level economic analysis includes cost and revenue accounting for grazed animals. The effects of wildlife grazing on forage production can also be modeled (Carlson and Thurow, 1992).
The benefits of developing, testing, and implementing both ANN “data-driven” models and process-based models
(e.g. SPUR) for range land management is that each may provide certain advantages, which, when taken in conjunction, provide the Nation with a more comprehensive management capability. For example, the ANNs may be more accurate for shorter-time forecasting horizons, improving management strategies over these periods. In contrast, the process-based model SPUR will be more effective for assessing different possible conditions or strategies over longer-time horizons. In addition, each can be used to improve the capability of the other. Through sensitivity analyses, both model types may help identify important system variables or factors, which would justify additional characterization/measurement, ultimately improving forecasting and management capability over both shorter- and longer-time horizons.
Goals: To provide information and capacity-building to Tohono O’odham Nation range managers in support of management decisions, including determination of appropriate stocking rates, by:

a) Preparing the well-known SPUR process-based rangeland model for use under Tohono O’odham Nation rangeland conditions and providing measurements of model accuracy; b) Understanding, monitoring, and predicting management effects on rangeland processes and production by using the model with all available data, including field measurements and remotely sensed data; c) Working with Tohono O’odham Nation participants in data collection and model validation, and providing training and experience in model operation.
Deliverables: a) Data set used for rangeland modeling, including GIS maps, field data, and remotely sensed data b) Methodology for assimilation of remotely sensed data into the range modeling process for parameterization, calibration and validation c) Range model that runs with known accuracy for the study area d) Intercomparison of the utility of ANN and process-based models for range management e) Understanding of range processes and management effects in an arid grazing regime f) Technology transfer of SPUR model and training in its evaluation and use g) Outreach to community
Expected outcomes: a) Improved understanding of arid rangeland processes under existing climate and management, and options under different management and/or climate conditions b) Technology transfer of simulation model tool parameterized for use on the Tohono O’odham Nation c) TON participation in all phases of data gathering and model validation
TimelinesTask 1- Cultural and Historical Education curriculum
Review oral histories from O’odham and Anthropologists
Structured interviews w/ Tribal elders
Spanish and Mexican documents
Government records
Task 2 – STEM Recruitment
Meet w/ Tribal schools & TOCC to coordinate STEM educational activities (i.e.,
State universities technology industries, & STEM conferences)
Coordinate a Robotics Club with Tribal junior high and high schools
STEM computer applications
Recruit/hire Tribal high school and college students interested in science/and engineering disciplines
Task 3 - Digital Elevation and Vegetation Maps
LIDAR deployment
LIDAR map processing
Presentations to Tribal natural resource and conservation departments
Task 4 – Artificial Neural Networks
Train Nation personnel and students in ANN background and use
Work with Nation to implement ANN technology for project applications
Task 5 - Drought Forecasting
AVHRR&MODIS analysis of forage production
Historical forage availability study, from 1981
Improved, linearly scaled drought measures (AVHRR & MODIS) that account for hot desert behavior and variability
Task 5 – Continued
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Development and implementation of drought indices
ANPP and PUE time series data records for the AVHRR and MODIS sensors
(AVHRR- and MODIS-based analysis in year 1 for the meteorological sites and surroundings; a complete regional analysis in years
Interfacing of remote sensing range health a& productivity w/ ANN models
Quantitative maps of carrying capacity over the rangelands, based on PUE/
PUEmax and scalable drought indices
Analyses of the relationship between historical forage availability and grazing pressure on these rangelands, from the AVHRR time series
ANN interface with remote sensing for drought prediction
Task 6 – UAV Design, Construction, and Testing
Introduction and training in UAV construction and operation
Develop highly automated system for flight operation, gathering, retrieval, and data and image processing
STEM recruitment
Task 7 – SPUR/ANN Modeling for rangeland management
Compile data needed for models
Develop remote sensing assimilation method
Process remote sensing data through ANN models
Model parameterization and calibration
Model error assessment
Technology transfer training in model use and modification
Outreach activity coordinated through the Tribal-Academic Committee
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Conclusion: There is an urgent need to understand how rangeland ecosystems and human management schemes and land modifications interact and respond to precipitation and other external drivers (incident radiation, water availability and temperature) to permit the near real-time forecasting of range health, drought, and forage availability in highly variable desert systems. This is especially important given historical trends and global climate models that predict increased inter-annual variability in precipitation with more frequent, extreme drought events and changes in temperature for the southwestern United States. There is little known regarding vegetation-climate equilibria and the interactions of land cover dynamics with precipitation patterns and variability. Overall, the southwest deserts are expected to be affected by significant shifts in vegetation composition in the near future both as a result of anthropogenic and climate change.
Water is the most limiting resource to biological activity in arid/ semiarid systems with human livelihood critically tied to water. Water availability limits plant growth and production and its availability mediates the responsiveness of rangelands to human influences and management. Variations in the abundance and seasonal distribution of water availability are often used as a causal explanation for differences in land cover and rangeland productivity. Range production generally increases with increasing mean annual precipitation (MAP), a relationship that is fundamental to the management of semiarid rangeland ecosystems and our understanding of their response to changes in water availability. Complicating these phenomena, however, is man’s interaction with the environment, in this case, through the introduction of livestock. This becomes particularly complex within the context of ancient and sacred cultural tradition and heritage, as exemplified by the O’odham Nation, where Tribal values and customs must be delicately balanced with very real socioeconomic considerations.
In this project, experts from various multidisciplinary fields will work with the Nation, and assist them in developing and implementing an effective modeling and management program that balances agrarian needs with environmental impacts within the context of their ancient values and traditions. A number of challenging technical problems will be addressed, including drought estimation and forecasting, vegetative responses to various natural and anthropogenic factors, and establishment of appropriate range management protocols. State of the art data acquisition and analysis methods and models will be used, including satellite data, aerial imaging, artificial neural networks, empiricallyderived relationships, and process-based models. Nation personnel will be trained in the use of these methods and models to improve Tribal self reliance for sustainable range land management. In addition, social and anthropological issues will be integrated into the project, including archiving archaeological studies, oral histories,

and written records, developing a cultural resources management and protection plan, and providing cultural education workshops for the Nation. The development of a curriculum will include materials on prehistory and history for kindergarten through community college levels. Integration of high school and college tribal students into specific project tasks will nurture their interest and proficiency in technical disciplines, and perhaps most importantly, inculcate a new generation of scientists and engineers that will serve the Nation well. The final product, then, will be a multidisciplinary yet integrated system consisting of scientific, engineering, social, and educational components that will help the “master farmers of the desert” overcome the environmental and economic challenges of the 21 st century, while preserving a rich and storied culture far older than recorded time.