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The Colorado River is facing a crisis resulting from demands that have outstripped diminishing supplies, exacerbated by a severe multi-decadal drought and the effects of climate change. As participants directly involved in recent agreements seeking to address this challenge, we describe how a critical basin-wide lens has been developed through information transparency, including the evolution and voluntary exchange of computational models. To achieve greater sustainability, further resolve and commitment from water managers in the United States and Mexico is necessary to ensure the required enhancement of the knowledge systems that will be used to inform extremely difficult and critical decisions. [ABSTRACT FROM AUTHOR]

In recent years, reservoir management considerations have expanded to include environmental and recreational objectives, many of which are often difficult to quantify. With a larger set of operational objectives comes the need to identify tradeoffs and uncertainties among the various objectives. Uncertainty modeling may contribute to better reservoir management by identifying and quantifying the sources of significant uncertainty in predicting reservoir and fiver conditions that affect environmental habitats and recreational conditions. We implement a first-order, second-moment algorithm in RIVERWARE, an object-oriented fiver and reservoir modeling environment. The method is developed and applied to a case study from the lower Colorado River, where a preexisting deterministic model is used for reservoir operations and planning. The case study involves evaluation of uncertainties associated with prescribed reservoir pool elevations for purposes of recovering endangered fish species. Comparison of historical forecasts with observed data can provide managers with insight into operational policies that result in greater system uncertainty. Identifying these sources of uncertainty can guide managers in the development of future operational guidelines. DOI: 10.1061/(ASCE)0733-9437(2006)132:2(104) CE Database subject headings: Colorado River; Reservoir operation; Stochastic models; Uncertainty principles; Endangered species.

Beginning in January 1992, the Bureau of Reclamation (Reclamation) and the US Geological Survey (USGS) formulated plans for the Watershed and River Systems Management Program--a cooperative interagency effort to develop and implement flexible and robust river basin management tools for the benefit of managers and decision makers using a data centered approach. In addition to Reclamation and the USGS, a number of other agencies and universities have made substantial contributions to the success of the program. The result has been the need driven research and development of state-of-the-art technology which benefits water managers and technical specialists in many river basins. DOI: 10.1061/(ASCE)0733-9437(2006)132:2(92) CE Database subject headings: Water resources; Hydrology; River systems; Decision support systems; Reservoir operation; Models; Runoff; Watershed management.

Many rivers in the Western U.S. suffer from high salinity content due to both natural and human-induced causes. Computer simulation models are often used to estimate future salinity levels and identity mitigation needs. To date, estimation of future natural salt loading has utilized linear relationships between natural flow and natural salt. We develop a nonparametric regression technique to fit a functional relationship between natural flow and natural salt. The main advantages of the nonparametric technique are: (1) No prior assumptions have to be made as to the underlying form of the relationship and (2) any arbitrary relationship (linear or nonlinear) can be modeled. In addition, we develop a resampling scheme to provide confidence intervals of the natural salt estimates from the nonparametric model. We apply this model to data from a stream gauge at Glenwood Springs, Colo., on the Colorado River. We show that the new natural salt model reduces the average overprediction of salt mass shown in the existing natural salt model for the period 1941-1995 by approximately 15% (78,000 metric tons). DOI: 10.1061/(ASCE)0733-9372(2005) 131:1(130) CE Database subject headings: Colorado River; Regression models; Nonlinear systems; Salinity; Simulation.

The Power and Reservoir System Model (PRSYM) is an object-oriented software package for optimizing hydroenergy production in river, reservoir, and hydropower systems. PRYSM's data include basin topology, methods for modeling various characteristics of water systems, and operating policies. A model can be tailored to assess specific systems by constructing user-specific object libraries containing solution methods inherent to the system being modeled.