Ground Water-Related Data Services for the Arizona Hydrologic Information System (AHIS)

Tuesday, April 21, 2009: 11:30 a.m.
Turquoise III (Hilton Tucson El Conquistador Golf & Tennis Resort )
Matthew Garcia , Arizona Water Institute, Tucson, AZ
Katherine Jacobs , Arizona Water Institute, Tucson, AZ
Gary C. Woodard , SAHRA Center, University of Arizona, Tucson, AZ
Corinna Gries , Arizona State University
Wolf-Dieter Otte , Northern Arizona University
Ramon Vazquez , SAHRA Center, University of Arizona, Tucson, AZ
James McGill , Arizona Water Institute, Tucson, AZ
The Arizona Hydrologic Information System (AHIS) is a web-based portal developed by the Arizona Water Institute (AWI) and focused on developing better access, retrieval, and analytical capability for water-related data.  To support this functionality, centralized access to numerous and distributed datasets from public and private sector interests and various academic sources are provided.  AHIS provides for the service of meteorological, surface water, and subsurface hydrologic information such as groundwater well levels, withdrawals, and recharge measurements.  AWI is affiliated with the three state universities in Arizona (ASU, NAU, and UA), with the state’s Departments of Water Resources (ADWR), Environmental Quality (ADEQ), and Commerce, and with numerous commercial and nongovernmental organizations.  The AHIS project enhances communication between these and many other data providers, information consumers, and decision-makers.  In cooperation with SAHRA at the University of Arizona (UA), AHIS provides for the correlation and combination of various water-related datasets including well withdrawal and recharge permits and surface water resources with the Arizona Wells database, which includes well water-level information provided by the ADWR, ADEQ, and USGS.  Such wide collaboration provides an inherent requirement for information accessibility and data interoperability across subject disciplines, modeling systems, and decision-support tools.  Data cataloging and dissemination are based on metadata standards and dataset markup languages for ease of use in modeling and visualization applications.  These descriptions and classifications facilitate the discovery, collection, combination, and service of datasets and lead to their use in analyses and modeling studies for the development of derivative products, which provide scientists and decision-makers with a wealth of information focused on answering larger scientific and societal questions at hand.