思茅境内澜沧江径流变化量与云南气候变化的关系

以思茅澜沧江流域下游思茅境内水文站1960年1月～2001年12月的逐月径流量和云南的月雨量(气温)场格点资料为基础,用相关分析的方法,研究了思茅境内澜沧江流域的东西部径流量变化及其与云南气候变化的关系。结论为:思茅境内澜沧江下游流域的径流量变化与滇西南的降水量变化有显著的相关关系,其季节特征为春夏季较好,秋冬季次之;与元江河谷一带的气温变化也有显著的反相关关系,其中西部流域还与滇南的气温变化有显著的相关关系,其季节特征则为冬春季较好,夏秋季不显著。20世纪80年代以来,该流域的气温变化呈上升趋势,且西部升温的上升趋势更显著,气温上升对径流量的变化起减小的作用;20世纪90年代以来,该流域的东西部降水量变化出现了显著的差异,其东部的降水量明显增多,与此相一致,其东部径流量变化的增幅也明显大于其西部。     

基于"3S"技术的于田绿洲湿地动态变化研究

以极端干旱区典型绿洲———于田绿洲为研究区,采用遥感(RS)、地理信息系统(GIS)和全球定位系统(GPS)相结合的方法,进行了湿地资源调查,查明了于田绿洲湿地类型、区域分布及面积,应用模型和分形理论,探讨了于田绿洲湿地的动态变化特征,并分析了其发生动态变化的原因。研究结果对于干旱区绿洲湿地的合理开发和可持续发展有着重要现实意义。     

基于可持续发展的广东省城市供水价格改革探讨

针对目前城市供水价格计算与计量方式不合理和突出的水资源供需矛盾,提出了按全成本水价模式测算广东省城市供水价格,并采用阶梯水价、两部制水价和季节水价计量方式逐步达到全成本水价的措施与实施步骤,确保水资源的持续利用支撑广东省经济社会的可持续发展.     

A real-time inertial-aided cycle slip detection method based on ARIMA-GARCH model for inaccurate lever arm conditions

GPS Solutions - The GPS satellite transmitter antenna phase center offsets (PCOs) can be estimated in a global adjustment by constraining the ground station coordinates to the current International...     

Using raw regional climate model outputs for quantifying climate change impacts on hydrology

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.     

Target setting and allocation of carbon emissions abatement based on DEA and closest target: an application to 20 APEC economies

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.

     

Open tensile fractures at depth in anticlines: A case study in the Tarim basin,NW China

Understanding fracture openness in the Earth's crust is crucial for understanding fracture properties and their impact on fluid flow and potentially also in reservoir modelling. Here, we present cases showing the presence of open tensile fractures at depth in anticlines by integrating borehole imaging logs, core observations, casting sections, physical modelling, in‐situ stress analysis and production data in petroleum wells, and analysing the time of fracturing by fluid inclusion analysis. The data come from the Cretaceous Bashejiqike Formation in the Kuqa Depression, Tarim basin; its current depth varies between 6,000 and 8,100 m. The results show that tensile fractures are the main fracture type in the studied formation and that their hydraulic conductivity is poorly affected by the current maximum horizontal stress direction. Furthermore, we find that fracture development is uninterrupted during continued anticline folding, although there is a dominant time of fracturing.     

Assessing regression‐based statistical approaches for downscaling precipitation over North America

This paper assesses linear regression‐based methods in downscaling daily precipitation from the general circulation model (GCM) scale to a regional climate model (RCM) scale (45‐ and 15‐km grids) and down to a station scale across North America. Traditional downscaling experiments (linking reanalysis/dynamical model predictors to station precipitation) as well as nontraditional experiments such as predicting dynamic model precipitation from larger‐scale dynamic model predictors or downscaling dynamic model precipitation from predictors at the same scale are conducted. The latter experiments were performed to address predictability limit and scale issues. The results showed that the downscaling of daily precipitation occurrence was rarely successful at all scales, although results did constantly improve with the increased resolution of climate models. The explained variances for downscaled precipitation amounts at the station scales were low, and they became progressively better when using predictors from a higher‐resolution climate model, thus showing a clear advantage in using predictors from RCMs driven by reanalysis at its boundaries, instead of directly using reanalysis data. The low percentage of explained variances resulted in considerable underestimation of daily precipitation mean and standard deviation. Although downscaling GCM precipitation from GCM predictors (or RCM precipitation from RCM predictors) cannot really be considered downscaling, as there is no change in scale, the exercise yields interesting information as to the limit in predictive ability at the station scale. This was especially clear at the GCM scale, where the inability of downscaling GCM precipitation from GCM predictors demonstrates that GCM precipitation‐generating processes are largely at the subgrid scale (especially so for convective events), thus indicating that downscaling precipitation at the station scale from GCM scale is unlikely to be successful. Although results became better at the RCM scale, the results indicate that, overall, regression‐based approaches did not perform well in downscaling precipitation over North America. Copyright © 2013 John Wiley & Sons, Ltd.