OLAP-based Analysis and Visualization of Large Volumes of Hydrologic Data

AWRA 2010 Spring Specialty Conference, Orlando, Forida, March 29-31, 2010

Matthew Rodriguez, David Valentine, Thomas Whitenack, and Ilya Zaslavsky

“One of the goals of the CUAHSI Hydrologic Information System project (Maidment, 2009) is to create a comprehensive portrait of hydrologic observations for the U.S., integrating observational data and metadata from multiple sources, at the national, regional, and local levels. The data are made available via a uniform set of web service interfaces, called CUAHSI Water Data Services. Once a source of hydrologic observations is exposed via such set of methods, it is registered in the HIS Central registry (hiscentral.cuahsi.org) and its metadata is harvested into the central metadata catalog. The catalog currently indexes 9 million time series for 1.8 million measurement points, supporting web service access to about 4.3 billion data points. Such large catalogs and databases of observational and model-generated data are time consuming to query using common relational database tools. This paper describes a technique for rapid analysis and visualization of data summaries in large hydrologic data repositories using Online Analytical Processing (OLAP). OLAP databases, often called data cubes, are special representations that support high performance querying of large multidimensional data collections. The OLAP techniques are applied to the analysis of observation data catalogs and databases from several federal agencies, including EPA STORET, USGS NWIS, and USDA SNOTEL. We present sample OLAP analysis related to hydrologic data availability from the observations data catalogs, and geographic and temporal analysis of available data totals from the federal repositories. In addition, we demonstrate a novel web application for spatial analysis of OLAP data cubes built over observational and model-generated hydrologic datasets.”

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