Sentence examples for hydrologic database from inspiring English sources

The development and assessment of topographic and hydrologic database that extend over large areas are the areas of active research.

We intentionally designed the services to be generic and applicable to other hydrologic databases, in order to provide interoperability between disparate data sources.

These services provide a middle-layer of abstraction between the NWIS database and hydrologic analysis systems, allowing such analysis systems to proxy the NWIS server for on-demand data access.

This study presents a comprehensive investigation of the State Soil Geographic Database (STATSGO) and the Soil Survey Geographic Database (SSURGO) soil databases for their applications in hydrologic modeling practices, and provides detailed instructions on soil data aggregation.

Not only does this study expand the understanding of hydrologic response and erosion, it also provides an important database for the hydrology community.

Stochastic approach was used to generate independent extreme low database from historic periods of recorded hydrologic data.

Three primary tasks have been identified in most hydrologic applications with sophisticated computerized numerical models: the spatial database construction, integration of spatial model layers and the GIS and model interface.

WMAD is a relational database designed to make the management of large hydrologic datasets more efficient and less prone to manipulation errors.

A geographic information system database was established to display the results of the regionalization and to identify hydrologic regime changes between the 1936 2008, 1936 1980, and 1950 2008 analysis intervals.

The long-term hydrological impact assessment (L-THIA) web application, a DSS based on an integration of web-based programs, geographic information system (GIS) capabilities, and databases, is intended to support decision makers who need information regarding the hydrologic impacts of water quantity and quality resulting from land use change.

Despite an overall increase in uncertainty for extreme-event concentration estimates, estimates under extreme hydrologic conditions could be improved by taking into account the observed bias in the aggregated regional database.