Perspectives On Interdisciplinary Research Great Plains MidNet Conference

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Perspectives On Interdisciplinary ResearchGreat
Plains MidNet Conference

• Ralph K. Davis
• Director, Arkansas Water Resources Center and
  Associate Professor, Department of Geosciences
• University of Arkansas, Fayetteville

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NSF Environmental Observing Systems

• NEON National Ecological Observatory Network
• OOI Oceans Oservatories Initiative
• LTHO Long Term Hydrologic Observatories
• CLEANER Collaborative Large-Scale Engineering
  Analysis Network for Environmental Research

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NEON

• Goal is to answer ecological questions at
  regional to continental scale
• Need to understand ecosystem response to changes
  in dynamic equilibrium
• Examples
• Climate change
• Invasive species
• viruses

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NEON

• Overarching goal for this and other NSF
  observatory programs is
• Create and utilize a robust sensor network
• Compile data from the network and place in
  repositories for access by larger
  multi-disciplinary user groups
• Facilitate collaboration between researchers,
  educators, and stakeholders
• Network system is critical for data access,
  simulation and display

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LITHO

• Fundamental Science Areas

• Linking Hydrologic and Biogeochemical Cycles
• Hydrologic Extremes
• Sustainability of Water Resources
• Transport of Chemical and Biological
  Contaminants
• Hydrologic Influence on Ecosystem Functions

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LITHO

• Hydrologic observatories will be a community
  resource
• Large scale about 10,000 km2
• Sensor development, deployment, and maintenance
  are critical components
• Provide access to data that will be freely
  available to researchers
• Incorporate sensor data on a networked system

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LITHO

• There will be a balance between investigative
  work and networking
• There are numerous concerns about how to maintain
  a viable, reliable, robust network that includes
• Leverage existing data sets
• Data repository
• Simulation
• Display/Output products
• Maintenance of Quality Assurance/Quality Control

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CLEANER

• CLEANER effort is viewed as supporting efforts in
  NEON, LTHO and OOI
• Need
• Collection of data bases
• Linkage of databases
• Distribution with open access to data sets

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CLEANER

• Goal
• Merge diverse data, methods, and sources across
  spatial, temporal and societal scales
• Provide broad access to many user groups
• Researchers
• Educators
• Students
• Resource Managers
• Policy Makers
• Public at large

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Cyberinfrastructure for Environmental Water
Resource Management Building on Resources of the
Great Plains Network

• identification of available/needed resources to
  create a grid computing system
• that will provide various users access at
  multiple levels, and facilitate large-scale
  database management, rapid processing of image
  data, and seamless integration of complex,
  dispersed data sets and model applications
• Requirements for the system will be worked out in
  a series of four planning meetings.
• Planning partners include researchers in
  hydrology, remote sensing, modeling, meteorology,
  and engineering, plus experts in grid computing,
  advanced networking, and high-performance
  computing.

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Cyberinfrastructure for Environmental Water
Resource Management Building on Resources of the
Great Plains Network

• Models and data exist but are not integrated over
  large areas because
• the immense size and varied formats of the
  datasets minimize effective use for understanding
  watershed-scale processes.
• Accessing the data necessary to assess, manage,
  and predict water resources will be facilitated
  by identifying and building-out the
  cyberinfrastructure to
• permit use of a complete suite of grid computing
  services, real-time sensor data, and model
  input/output, for post-analysis and real-time
  application.

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Cyberinfrastructure for Environmental Water
Resource Management Building on Resources of the
Great Plains Network

• The Great Plains Network and partner (state)
  networks servicing this region provide a
  foundation on which to build the real-time
  multi-user interface envisioned.
• The Great Plains Network is the backbone for the
  envisioned grid system
• allowing rapid transfer of large data sets, high
  speed computation, and integration of models for
  real-time use in performing tasks such as
• river forecasting, aquifer depletion analysis,
  navigation level assessment, contaminant loading
  rates, drought mitigation, and disaster
  management.