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A synthesis of studies on Colorado River streamflow projections that examines methodological and model differences and their implications for water management.

Whether climate outlooks are "good" or "bad" depends on your perspective, including which regions, seasons, lead times, and aspects of forecast quality are relevant to your specific decision making situation.

Adaptation requires science that analyzes decisions, identifies vulnerabilities, improves foresight, and develops options.

The Ensemble Streamflow Prediction (ESP) system, developed by the National Weather Service (NWS), uses conceptual hydrologic models and historical data to generate a set, or ensemble, of possible streamflow scenarios conditioned on the initial states of a given basin. Using this approach, simulated historical probabilistic forecasts were generated for 14 forecast points in the Colorado River basin, and the statistical properties of the ensembles were evaluated. The median forecast traces were analyzed using ''traditional'' verification measures; these forecasts represented ''deterministic ESP forecasts.'' The minimum-error and historical traces were examined to evaluate the median forecasts and the forecast system. Distribution-oriented verification measures were used to analyze the probabilistic information contained in the entire forecast ensemble. Using a single-trace prediction, for example, the median, resulted in a loss of valuable uncertainty information about predicted seasonal volumes that is provided by the entire ensemble. The minimum-error and historical traces revealed that there are errors in the data, calibration, and models, which are part of the uncertainty provided by the probabilistic forecasts, but are not considered in the median forecast. The simulated ESP forecasts more accurately predicted future streamflow than climatology forecasts and, on average, provided useful information about the likelihood of future streamflow magnitude with a lead time of up to 7 months. Overall, the forecast provided stronger probability statements and became more reliable at shorter lead times. The distribution-oriented verification approach was shown to be applicable to ESP outlooks and appropriate for extracting detailed performance information, although interpretation of the results is complicated by inadequate sample sizes.

Scenarios of water supplies reflecting CO2-induced climatic change are used to determine potential impacts on levels of the Laurentian Great Lakes and likely water management policy implications. The water supplies are based on conceptual models that link climate change scenarios from general circulation models to estimates of basin runoff, overlake precipitation, and lake evaporation. The water supply components are used in conjunction with operational regulation plans and hydraulic routing models of outlet and connecting channel flows to estimate water levels on Lakes Superior, Michigan, Huron, St. Clair, Erie, and Ontario. Three steady-state climate change scenarios, corresponding to modeling a doubting of atmospheric CO 2, are compared to a steady-state simulation obtained with historical data representing an unchanged atmosphere. One transient climate change scenario, representing a modeled transition from present conditions to doubled CO 2 concentrations, is compared to a transient simulation with historical data. The environmental, socioeconomic, and policy implications of the climate change effects modeled herein suggest that new paradigms in water management will be required to address the prospective increased allocation conflicts between users of the Great Lakes.

Unrelenting pressure on limited surface water supplies requires increasingly sophisticated water management approaches. Climate forecasts of seasonal precipitation and temperature are potentially useful, but the operational water management community currently underutilizes them. However, some agencies in Arizona took unprecedented advantage of forecasts for a potentially wet winter during the 1997–1998 El Niño event. This study investigates use of this information through a series of semi‐structured in‐depth interviews with key personnel from agencies responsible for emergency management and water supply; their jurisdictions ranged from urban to rural and local to regional. Interviews investigated information acquisition, interpretation, and incorporation into specific decisions and actions. While unprecedented actions were taken by some water management agencies and no agencies implemented inappropriate measures, some missed opportunities for more effective response, primarily through inaction. This study reveals a variety of technical factors and institutional characteristics affecting forecast use. Study findings emphasize the need for: (a) closer ongoing relationships between forecast producers and users, (b) increased institutional flexibility to exploit the increasing skill of seasonal climate forecasts, (c) demonstration projects of effective forecast use, and (d) a regional forum to facilitate information transfer between the hydro‐climatic research community and operational water managers.

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