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Implementation of a Cuahsi HIS system at LBL Nigel W. T. Quinn, Christian Pedersen Lawrence Berkeley National Laboratory

Implementation of a Cuahsi HIS system at LBL Nigel W. T. Quinn, Christian Pedersen Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720. Abstract. Methods . Results.

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Implementation of a Cuahsi HIS system at LBL Nigel W. T. Quinn, Christian Pedersen Lawrence Berkeley National Laboratory

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  1. Implementation of a Cuahsi HIS system at LBL Nigel W. T. Quinn, Christian Pedersen Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720 Abstract Methods Results The Hydrologic Information System (HIS) is a standardized information system thought up by CUAHSI to give access to university’s hydrologic information over the internet. This standardized system of data transfer enables scientists from around the globe to retrieve other's hydrology data without having to adapt to each universities specific method of providing that data. Hydrology data gathered during a 4 year wetland modified hydrology experiment has been webs-served using a commercial vendor YSI-EcoNet at a cost of over $25,000 per year. Expansion of the current system of networked stations to 200 using the same vendor – could cost upwards of $200,000 per year. The current project is designed to create a public domain equivalent of this commercial system that can be used to host current and future wetland real-time monitoring data. By migrating the data to a HIS server hosted at LBNL, we will provide a standardized way to access this information. The HIS is split up into several inter-related components. The components outlined in green have already been implemented in the current HIS system at LBL as part of this project: The wetland data was migrated to the ODM database and we were able to model the data with the ODM tools. • The ODM, or Observations Data Model is a database format that is primarily used for storage of hydrology data. • WaterML is a file format majorly used for the transmission of hydrology data to a client-side application like HydroSeek or DASH. • ODM databases are databases that implement this model and are generally attached to Microsoft SQL Server 2003. The database is used for storage of all hydrologic information. This graph indicates that the conductivity of outflow from a pond increased significantly between October and December of 2008. The ODM WaterOneFlow web services were also added to the server and succeeded in serving WaterML. Conclusion This research project focused on a 4-year seasonal wetland salinity monitoring system in the grasslands This is the network flow diagram for the entire HIS system. Introduction • The ODM data loader is a tool developed to load data into the ODM Database from a file. • The ODM Tools are an application developed to request data from the database locally and to model HIS data. • ODM WaterOneFlow web services are a group of internet pages meant to be put on a web server. When these files are read by a browser, the HIS server hosting these requests data from the ODM database and provides them in a browser-readable format. These services also provide a conversion from the ODM database format to WaterML. • The following items outlined in red are scheduled for implementation: • The Central ODM database will house some of the data already stored on the HIS server at LBL. • Central ODM WaterOneFlow web services will connect like the web services mentioned above to the Central ODM Database and converting the data to WaterML for other applications to use. • Hydroseek is a smooth, web-based user interface that will be accessible to the public and allow for remote viewing and water quality management. ecological area of San Joaquin Valley. This system produces 15 minute flow and salinity data from inlet and outlet sites. The server will make the data produced from these wetlands publicly accessible. Small hydrology projects, especially those initiated at Universities pay little attention to database design or data management and at the end of the study much of this raw data is lost to the scientific community – because it is rarely in a form that it can be understood, metadata is poor or completely lacking and the data ontologies (what is meant by a particular measurement) are often lacking. By migrating the data to a HIS server hosted at LBNL, we will provide a standardized way to access this information saving the wetlands agencies we are cooperating with upwards of $25,000 per year in data management fees. Acknowledgments Bryan E. Taylor Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, Timothy L. Whiteaker. The University of Texas at Austin Center for Research in Water Resources, Cockrell School of Engineering10100 Burnet Rd Bldg 119, Austin, TX 78758-4445

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