The Effects of Data Degradation on Model Performance: Adjusting the quality and quantity of input data in a snow model
M.S. (Watershed Science) 2006 Colorado State University, Fort Collins, CO, USA 80523-1472
B.S. (Meteorology) 2002 Lyndon State College, Lyndonville, Vermont 05851
Many regions in the United States experience meteorological and hydrological data scarcity issues. Operationally this becomes important when the available data is insufficient enough to produce reliable model outputs. Similar to Tsintikidis et al. (2002) concluding that the installation of additional rain gauges in a modeled basin would decrease the error of precipitation measurements in the model, we hope to find that increasing data input into a model, both the quantity and quality given by site representivity, will increase the accuracy of our model runs.
A portion of the Yampa River in northwestern Colorado was modeled with NWSRFS. This basin was chosen for its snowmelt dominance characteristic. Mean areal precipitation and temperature values for the modeled zones are developed individually in each analysis scheme by the arrangement of stations used in each sensitivity analysis. A statistical analysis of the relative difference between model runs and archived observed values is performed in an effort to illustrate the effect of different model input data arrangements on model simulations. Streamflows and snow water equivalence are analyzed to test the model's sensitivity.
Since the NWSRFS uses predetermined weights to determine MAPs, the number of stations used does not significantly affect model output. The usage of predetermined weights maintains a consistent year-to-year MAP. Varying the MAT station configuration showed a much bigger effect than the MAP scheme illustrated.
It is believed that though this procedure could and should be replicated for other hydroclimates and for basins with different sizes, that the specific results are not transferable to other basins. The basin modeled is very heavily snowmelt dominated. This quality, as well as it size, climate, topography, and available hydrometeorological stations all influence model results; altering any of these would change the model performance.
Tsintikidis, D., Georgakakos, K.P., Sperfslage, J.A., Smith, D.E., and Carpenter, T.M. 2002. Precipitation uncertainty and rain gauge network design within Folsom Lake watershed. Journal of Hydrological Engineering, 7(2), 175-184.
Advisor: Steven Fassnacht
Freeman Smith (Watershed Science)
William Sanford (Geosciences)
Larry Rundquist (NOAA-NWS AK)
Jorge Ramirez (Civil Engineering)