Hydrologic information server for benchmark precipitation dataset

This paper will present the methodology and overall system development by which a benchmark dataset of precipitation information has been made available. Rainfall is the primary driver of the hydrologic cycle. High quality precipitation data is vital for hydrologic models, hydrometeorologic studies and climate analysis,and hydrologic time series observations are important to many water resources applications. Over the past two decades, with the advent of NEXRAD radar, science to measure and record rainfall has improved dramatically. However, much existing data has not been readily available for public access or transferable among the agricultural, engineering and scientific communities. This project takes advantage of the existing CUAHSI Hydrologic Information System ODM model and tools to bridge the gap between data storage and data access, providing an accepted standard interface for internet access to the largest time-series dataset of NEXRAD precipitation data ever assembled. This research effort has produced an operational data system to ingest, transform, load and then serve one of most important hydrologic variable sets.

► Dataset is the largest compilation of MPE precipitation values assembled in “time-series” format.
► Precipitation estimates may be queried in both time and space, essential for hydrologic sciences.
► The service architecture is machine accessible, returning values in WaterML language.
► Provides a mesh of “virtual” rain gauges covering an extensive land area.