Stochastic Modeling and Simulation of the Colorado River Flows

The Colorado River is one of the most important rivers systems in the western United States. Streamflows of this river represent a significant portion of the water supply in the region. Many river diversions and dams have been developed throughout the system in order to be able to deliver and meet the expected demands from a variety of water users. To plan and operate the river system planners and managers must be able to analyze and assess the effect of possible streamflow scenarios that may occur in the future. For this purpose stochastic simulation studies of the system have been undertaken. The spatial and temporal variability of streamflows in this river is quite complex not only because of its size but the effect of large-scale atmospheric and oceanic fluctuations. Monthly and annual data of naturalized flows at 29 sites have been analyzed to characterize the spatial and temporal variability in key statistics such as means, variances, covariances, skewness, and surplus and drought related statistics. The statistical relationships between sites are just as important as the statistical characteristics of each site. In principle a multivariate model could be applied directly to the 29-site system but such a model will require estimating a large number of parameters, in some cases the parameters may be difficult if not impossible to obtain, and for a river network system such a direct application of a model for the entire system may not be necessarily appropriate. Therefore, the system must be simplified so that it becomes statistically tractable and consistent with a river network. For this purpose alternative modeling strategies (schemes) have been developed in literature and appropriate software are available (e.g. SAMS and SPIGOT). In this study we have applied SAMS and compared three major modeling schemes. We describe the assumptions behind them, the differences between them, and present results.