Throughout the world, efforts are under way to restore watersheds, but restoration planning rarely accounts for future climate change. Using a series of linked models of climate, land cover, hydrology, and salmon population dynamics, we investigated the impacts of climate change on the effectiveness of proposed habitat restoration efforts designed to recover depleted Chinook salmon populations in a Pacific Northwest river basin. Model results indicate a large negative impact of climate change on freshwater salmon habitat. Habitat restoration and protection can help to mitigate these effects and may allow populations to increase in the face of climate change. The habitat deterioration associated with climate change will, however, make salmon recovery targets much more difficult to attain. Because the negative impacts of climate change in this basin are projected to be most pronounced in relatively pristine, high-elevation streams where little restoration is possible, climate change and habitat restoration together are likely to cause a spatial shift in salmon abundance. River basins that span the current snow line appear especially vulnerable to climate change, and salmon recovery plans that enhance lower-elevation habitats are likely to be more successful over the next 50 years than those that target the higher-elevation basins likely to experience the greatest snow-rain transition.Chinook salmon ͉ hydrologic model ͉ population model ͉ Snohomish River ͉ stream flow O ver the past decade, billions of dollars have been spent on the restoration of aquatic habitats throughout the United States (1). In the northwestern U.S., aquatic habitat restoration has been driven largely by the Endangered Species Act, under which several species of Pacific salmon have been listed. The listings have led to the development of salmon recovery plans for watersheds throughout the region. Long-term freshwater habitat protection and restoration projects are central to all plans. Planners rely heavily on fish habitat models to evaluate the potential effectiveness of proposed restoration strategies, and numerous models have been developed to predict restoration effects. In almost all cases, these models assume stationary future climate conditions when assessing how restoration will affect fish abundance and productivity. Given the increasing certainty that climate change is accelerating, models that ignore the potential effects of future climate may generate misleading predictions of the relative benefits of different recovery strategies.The northwestern U.S. has warmed by between 0.7 and 0.9°C during the 20th century. Since 1950, average annual air temperatures at the majority of meteorological stations in the region have risen by Ϸ0.25°C/decade (2), and climate models predict another 1.5-3.2°C increase by the middle of the 21st century (3). Higher air temperatures are likely to increase water temperatures, which could be harmful to salmon during the spawning, incubation, and rearing stages of their life cycle (4). Warmer temperatures a...

Abstract:This paper reviews methods that have been used to evaluate global climate simulations and to downscale global climate scenarios for the assessment of climate impacts on hydrologic systems in the Pacific Northwest, USA. The approach described has been developed to facilitate integrated assessment research in support of regional resource management. Global climate model scenarios are evaluated and selected based on historic 20th century simulations. A statistical downscaling method is then applied to produce a regional data set. To facilitate the use of climate projections in hydrologic assessment, additional statistical mapping may be applied to generate synthetic station time series. Finally, results are presented from a regional climate model that indicate important differences in the regional climate response from what is captured by global models and statistical downscaling.

Abstract:Some relatively straightforward modifications to the Distributed Hydrology-Soil-Vegetation Model (DHSVM) are described that allow it to represent urban hydrological processes. In the modified model, precipitation that falls on impervious surfaces becomes surface runoff, and a spatially varying (depending on land cover) fraction of surface runoff is connected directly to the stream channel, with the remainder stored and slowly released to represent the effects of stormwater detention. The model was evaluated through application to Springbrook Creek watershed in a partially urbanized area of King County, Washington. With calibration, the modified DHSVM simulates hourly streamflow from these urbanized catchments quite well. It is also shown how the revised model can be used to study the effects of continuing urbanization in the much larger Puget Sound basin. Model simulations confirm many previous studies in showing that urbanization increases peak flows and their frequency, and decreases peak flow lag times. The results show that the urbanization parameterizations for DHSVM facilitate use of the model for prediction and/or reconstruction of a range of historic and future changes in land cover that will accompany urbanization as well as other forms of vegetation change.

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Mid‐range streamflow predictions are extremely important for managing water resources. The ability to provide mid‐range (three to six months) streamflow forecasts enables considerable improvements in water resources system operations. The skill and economic value of such forecasts are of great interest. In this research, output from a general circulation model (GCM) is used to generate hydrologic input for mid‐range streamflow forecasts. Statistical procedures including: (1) transformation, (2) correction, (3) observation of ensemble average, (4) improvement of forecast, and (5) forecast skill test are conducted to minimize the error associated with different spatial resolution between the large‐scale GCM and the finer‐scale hydrologic model and to improve forecast skills. The accuracy of a streamflow forecast generated using a hydrologic model forced with GCM output for the basin was evaluated by forecast skill scores associated with the set of streamflow forecast values in a categorical forecast. Despite the generally low forecast skill score exhibited by the climate forecasting approach, precipitation forecast skill clearly improves when a conditional forecast is performed during the East Asia summer monsoon, June through August.