Precipitation is one of the most important components contributing to hydrological
dynamics. Spatially distributed precipitation data can be obtained by satellite, radar,
rain gages, etc, to serve various purposes. Currently, the most commonly used
precipitation data still rely on gage-based measurement techniques that provide
timely precipitation information with high quality and reliability. The National
Oceanic and Atmospheric Administration (NOAA) and its cooperative climate
stations are the primary resources of this form of precipitation data at the federal
level. For hydrological simulation of precipitation-runoff for a watershed,
precipitation is a critical model input that has a significant impact on the certainty
and accuracy of simulation. To better understand the hydrological process within
Whitewater River Basin in Kansas, the Precipitation-Runoff Model System (PRMS)
was applied to this area, where the Cooperative Atmosphere-Surface Exchange
Study (CASES) has set up an intensively instrumented site managed by Hydrologic
Science Team (HST) of Oregon State University for rainfall data collection. Two
rainfall data sources, NOAA and HST, were used in this study to simulate the stream
response to rainfall within the basin. Different simulation results were acquired
compared and analyzed. The study concluded that better simulation results were
obtained with MMS-PRMS using integrated spatially distributed precipitation data,
which was not available as a standard NOAA product. For a large basin, it is
necessary to collect precipitation data within the area of interest in addition to
standard NOAA data to produce an accurate hydrological model. It was suggested
that to guarantee the quality of precipitation-runoff simulation using MMS-PRMS,
the coverage of each rain gage should not be larger than 40 to 50 square kilometers
(about 15-20 square miles). It was also learned that the precipitation data from local
supplementary measurements are unlikely to be a satisfactory substitute for current
NOAA data in hydrological simulation due to the short time period of measurement.
The combination of standard NOAA data and additional data from an intensively
measured site, such as CASES, or from radar, would allow more for better
simulation. / Graduation date: 2004
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/31644 |
| Date | 26 February 2003 |
| Creators | Lin, Wei |
| Contributors | Cuenca, Richard H. |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
Page generated in 0.0016 seconds