4.1 Implications for the Future
 Climate change has resulted not only in warming (which is unequivocal at the global scale [IPCC, 2007]), but also in an intensification of the global water cycle during the last century due to a warming-induced increase in the atmosphere's water-holding capacity with impacts on P generation [Huntington, 2006]. Previous studies reported on the importance of warming in affecting the shape of the seasonal hydrograph (with less water availability during the summer of peak water demand) in snowmelt-dominated mountainous areas of the western U.S. [Hamlet et al., 2005, 2007]. However, as indicated by this study, a combination of the effects of changes in T and P vary spatially and seasonally. Even with an increase in P over water-limited regions in the warm season, R may not increase accordingly because of the water demand for ET, not to mention that we are anticipating fairly strong decreases in warm-season P in the future, as estimated by Mote and Salathe . Only an increase in P during the cool season could generate substantial effective R because of an insignificant loss in ET. Conversely, in energy-limited regions, an increase in P and an earlier shift in the seasonal hydrograph due to early snowmelt results in more R and a rise in R/P, especially during the cool season (Figures 7, 9, and 11). Because of the robust prediction of warming in the near future (i.e., global climate models (GCMs) are consistent in predicting warming across the region), but inconsistent in annual P projections, although with some consistency in projecting decreases in summer precipitation and increases in precipitation in the other seasons [Mote and Salathe, 2010], we can expect that in the water-limited areas of the PNW, R/P will continue to decrease. It is in these water-limited areas that there is a growing concern over dwindling water availability during the growing season; reductions in warm-season R/P and increasing water demand, particularly for irrigation, will exacerbate current water scarcity problems. In the energy-limited areas, the warming effects on annual R/P are less certain because R/P depends more strongly on changes in P; however, it is more certain that R/P will increase during the cool season in this region because of the influence of warming on the snowpack and therefore the seasonal hydrograph. However, there are fewer water scarcity concerns in these energy-limited regions.
4.2 Dynamics of Budyko Space over the PNW During 1921-2006
 Budyko space, the relationship between the mean annual evaporative index (ET/P) and the mean annual dryness index (PET/P), has been widely used to assess the relative contributions of water supply and energy demand to ET variations [Budyko, 1974; Gerrits et al., 2009; Williams et al., 2012; Zhang et al., 2012]. Figure 12 shows the distributions of annual ET/P and PET/P in water- and energy-limited zones, respectively. The simulated results indicate that, in both the water- and energy-limited zones, the slope of the ET/P vs. PET/P relationship has significantly increased in the most recent 43 years of the simulations (P < 0.05), which means that, under the same dryness condition, the evaporative index has increased (i.e., a greater percentage of P is evaporated) (Figure 12). This is likely due to the combined effects of warmer conditions in the cool season (increasing PET in the energy-limited seasons) and increasing trends in warm-season P. If the trend continues in the future, water-limited zones may experience future reductions in the R/P ratio relative to current conditions.
Figure 12. Dynamics of Budyko space. Points represent pairs of annual ET/P and PET/P in each zone during the first and second half of 1921-2006. Solid lines are the regression over the period of 1964-2006; dotted lines are the regression over the period of 1921-1963.
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 On the other hand, future projections of increasing cool-season precipitation and decreasing summer precipitation for the PNW [Mote and Salathe, 2010] may tend to bring the opposite effect, reducing the ET/P ratio in water-limited areas because P is increasingly distributed to seasons with relatively low surface energy and PET, as discussed above. It is also worth noting that projections of changing summer ET in water-limited areas are essentially opposite to those observed in the historical period. GCM/VIC projections suggest drier summers (and therefore lower summer ET in water-limited areas) [Hamlet et al., 2012], while summer precipitation has been increasing overall historically, resulting in increases in summer ET in water-limited areas (Figure 9). By comparison, for energy-limited areas, summer ET has increased historically, and the GCM/VIC projections show broadly similar effects associated with ongoing regional warming (resulting in increasing ET in energy-limited areas).
 Land-use practices and vegetation dynamics can also influence ET and R/P [Vorosmarty and Sahagian, 2000; Vorosmarty et al., 2000; Jackson et al., 2001; Foley et al., 2005; Liu et al., 2008]. The interactions between climate change, hydrologic processes, land-use practices, and vegetation dynamics should be explicitly incorporated into future model development to better predict how changes in water quantities and regimes affect terrestrial ecosystems (and vice versa) at regional scales. For example, the warming-induced early onset of plant growth could increase ET and hence intensify soil dryness in late summer if P does not change; this dynamic is modulated by the impacts of P and T changes on snowpack and SM processes. This dynamic is not captured in this study because the monthly vegetation parameters (e.g., leaf area index) are held constant throughout the simulation period; that is, the current vegetation parameters have no interannual variations or long-term trends. As another example, the CO2 fertilization effects on stomatal conductance have been shown, in some studies, to increase water-use efficiency and therefore R [Farquhar and Sharkey, 1982; Field et al., 1995; Gedney et al., 2006]. However, its overall impacts on the water cycle at regional and global scales are still uncertain [Milly et al., 2005; Piao et al., 2007; Dai et al., 2009]. The VIC model used in this study, which does not have a dynamic vegetation component, has no specific consideration of the CO2 fertilization effect on plant growth and therefore on ET.
 Another limitation in this modeling study is that other climate variables in these offline simulations, such as surface short- and long-wave radiation and vapor pressure deficit (VPD), are estimated from T and P with empirical algorithms [Liang et al., 1994, 1996b; Hamlet et al., 2005; Adam et al., 2009; Elsner et al., 2010]. VPD has been used as a dominant factor representing water stress in estimating remote-sensing-based ET [Mu et al., 2007]. Our modeling work also showed that annual PET has a very high correlation with VPD in both water- and energy-limited zones, with an R2 of 0.96. PET trends in both water- and energy-limited zones are generally negative in the warm season and positive in the cool season, which corresponds to the decreases in derived radiation and VPD in the warm season and increases in the cool season (Table 3). As discussed by Hamlet et al. , the uncertainties from the derived meteorological variables, just based on Tmax and Tmin with Thornton and Running's  method and the coarse resolution of the reanalysis data used for wind-speed data, could affect our simulation results. Therefore, there is a need to better represent meteorological conditions, as well as to capture land-surface feedback effects through coupled land-surface/atmospheric models that explicitly represent dynamic vegetation processes.
 Furthermore, similar to most other hydrological models, VIC was calibrated only with river streamflow data and not with ET observations. According to Zhang et al. , the combination of calibrations against remotely sensed ET and streamflow can improve general R/P models of ungauged catchments. Our studies also indicated considerable bias from ET estimations at seasonal patterns. Further modeling studies and analyses should use available ET observations to calibrate key parameters related to ET processes, such as the maximum stomatal conductance for individual biome types. Likewise, water limitations in late summer in the model simulations are clearly introducing a low bias in the simulation of ET over most of the sites examined.
 In summary, to assess the impacts of climate change on water resources, an integrated Earth systems model that couples the processes of water, ecosystem dynamics, biogeochemical cycles, atmospheric chemistry, regional climate, and human-natural system interactions is critical. However, this should be done with careful consideration of the scales of each of these processes. For example, the discrepancy between eddy-flux observations and VIC-simulated ET is most likely due to a scale mismatch. As proposed by Wood et al. , hyper-resolution land-surface models and spatial data are needed to monitor the terrestrial water cycle from local to global scales. However, Beven and Cloke  argue that improvements in our understanding of scaling effects on spatial heterogeneities are more important than just improving the simulation resolution. Therefore, Earth systems model development efforts for improving our understanding of the water cycle must be performed in tandem with experimental studies to ensure that the appropriate scales for each of these processes are captured.