General circulation model outputs are rarely used directly for quantifying climate change impacts on hydrology, due to their coarse resolution and inherent bias. Bias correction methods are usually applied to correct the statistical deviations of climate model outputs from the observed data. However, the use of bias correction methods for impact studies is often disputable, due to the lack of physical basis and the bias nonstationarity of climate model outputs. With the improvement in model resolution and reliability, it is now possible to investigate the direct use of regional climate model (RCM) outputs for impact studies. This study proposes an approach to use RCM simulations directly for quantifying the hydrological impacts of climate change over North America. With this method, a hydrological model (HSAMI) is specifically calibrated using the RCM simulations at the recent past period. The change in hydrological regimes for a future period (2041–2065) over the reference (1971–1995), simulated using bias‐corrected and nonbias‐corrected simulations, is compared using mean flow, spring high flow, and summer–autumn low flow as indicators. Three RCMs driven by three different general circulation models are used to investigate the uncertainty of hydrological simulations associated with the choice of a bias‐corrected or nonbias‐corrected RCM simulation. The results indicate that the uncertainty envelope is generally watershed and indicator dependent. It is difficult to draw a firm conclusion about whether one method is better than the other. In other words, the bias correction method could bring further uncertainty to future hydrological simulations, in addition to uncertainty related to the choice of a bias correction method. This implies that the nonbias‐corrected results should be provided to end users along with the bias‐corrected ones, along with a detailed explanation of the bias correction procedure. This information would be especially helpful to assist end users in making the most informed decisions. 相似文献
Subsurface dams are rather effective and used for the prevention of saltwater intrusion in coastal regions around the world. We carried out the laboratory experiments to investigate the elevation of saltwater wedge after the construction of subsurface dams. The elevation of saltwater wedge refers to the upward movement of the downstream saltwater wedge because the subsurface dams obstruct the regional groundwater flow and reduce the freshwater discharge. Consequently, the saltwater wedge cannot further extend in the longitudinal direction but rises in the vertical profile resulting in significant downstream aquifer salinization. In order to quantitatively address this issue, field-scale numerical simulations were conducted to explore the influence of various dam heights, distances, and hydraulic gradients on the elevation of saltwater wedge. Our investigation shows that the upward movement of the saltwater wedge and its areal extension in the vertical domain of the downstream aquifer become more severe with a higher dam and performed a great dependence on the freshwater discharge. Furthermore, the increase of the hydraulic gradient and the dam distance from the sea boundary leads to a more pronounced wedge elevation. This phenomenon comes from the variation of the freshwater discharge due to the modification of dam height, location, and hydraulic gradient. Large freshwater discharge can generate greater repulsive force to restrain the elevation of saltwater wedge. These conclusions provide theoretical references for the behaviour of the freshwater–seawater interface after the construction of subsurface dams and help optimize the design strategy to better utilize the coastal groundwater resources. 相似文献
Regarded as an effective method for treating the global warming problem, carbon emissions abatement (CEA) allocation has become a hot research topic and has drawn great attention recently. However, the traditional CEA allocation methods generally set efficient targets for the decision-making units (DMUs) using the farthest targets, which neglects the DMUs’ unwillingness to maximize (minimize) some of their inputs (outputs). In addition, the total CEA level is usually subjectively determined without any consideration of the current carbon emission situations of the DMUs. To surmount these deficiencies, we incorporate data envelopment analysis and its closest target technique into the CEA allocation problem. Firstly, a two-stage approach is proposed for setting the optimal total CEA level for the DMUs. Then, another two-stage approach is given for allocating the identified optimal total CEA among the DMUs. Our approach provides more flexibility when setting new input and output targets for the DMUs in CEA allocation. Finally, the proposed approaches are applied for CEA target setting and allocation for 20 Asia-Pacific Economic Cooperation economies.