Water observations data are time series of measurements made at point locations of water level, flow, and quality and corresponding data for climatic observations at point locations such as gaged precipitation and weather variables. A services-oriented architecture has been built for such information for the United States that has three components: hydrologic information servers, hydrologic information clients, and a centralized metadata cataloging system. These are connected using web services for observations data and metadata defined by an XML-based language called WaterML. A Hydrologic Information Server can be built by storing observations data in a relational database schema in the CUAHSI Observations Data Model, in which case, web services access to the data and metadata is automatically provided by query functions for WaterML that are wrapped around the relational database within a web server. A Hydrologic Information Server can also be constructed by custom-programming an interface to an existing water agency web site so that responds to the same queries by producing data in WaterML as do the CUAHSI Observations Data Model based servers. A Hydrologic Information Client is one which can interpret and ingest WaterML metadata and data. We have two client applications for Excel and ArcGIS and have shown how WaterML web services can be ingested into programming environments such as Matlab and Visual Basic. HIS Central, maintained at the San Diego Supercomputer Center is a repository of observational metadata for WaterML web services which presently indexes 342 million data measured at 1.75 million locations. This is the largest catalog water observational data for the United States presently in existence.