Investigation of techniques for improvement of seasonal streamflow forecasts in the Upper Rio Grande Basin [electronic resource] /

by Lee, Song-Weon

Abstract (Summary)
The purpose of this dissertation is to develop and evaluate techniques for improvement of seasonal streamflow forecasts in the Upper Rio Grande (URG) basin in the U.S. Southwest. Three techniques are investigated. The first technique is an investigation of the effects of the El Nin?o/Southern Oscillation (ENSO) on temperature, precipitation, snow water equivalent (SWE), and the resulting streamflow at a monthly time scale, using data from 1952 to 1999 (WY). It was seen that the effects of ENSO on temperature and precipitation were confined to certain months, predominantly at the beginning and end of the winter season, and that the effect of these modulations of temperature and precipitation by ENSO can be seen in the magnitude and time variation of SWE and streamflow. The second part is a comparison of the use for snowmelt-runoff modeling of the newly available snowcover product based on imagery from the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) with the long-time standard snowcover product from the National Hydrological Remote Sensing Center (NOHRSC). This comparison is made using the Snowmelt Runoff Model (SRM) in two watersheds located inside the URG basin. This comparison is important because the MODIS snowcover product could greatly improve the availability of snowcover information because of its high spatial (500m) and temporal (daily) resolutions and extensive (global) coverage. Based on the results of this comparison, the MODIS snowcover product gives comparable snowcover information compared to that from NOHRSC. The final part is an investigation of streamflow forecasting using mass-balance models. Two watersheds used in the comparison of MODIS and NOHRSC snowcover products were again used. The parameters of the mass-balance models are obtained in two different ways and streamflow forecasts are made on January 1st, February 1st, March 1st and April 1st. The first means of parameter estimation is to use the parameter values from 1990 to 2001 SRM streamflow simulations and the second means is by optimization. The results of this investigation show that mass-balance models show potential to improve the long-term streamflow forecasts in snowmelt-dominated watersheds if dependable precipitation forecasts can be provided.
Bibliographical Information:


School:Texas A&M International University

School Location:USA - Texas

Source Type:Master's Thesis

Keywords:major civil engineering moderate resolution imaging radiometer modis mass balance models el nino southern oscillation enso snowmelt runoff model srm long term streamflow forecast optimization


Date of Publication:

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