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191.
行程时间不确定性导致了可达性随时间的变化,相关研究表明忽略行程时间不确定性会高估可达性水平。既有可达性研究往往用行程时间可靠性表示行程时间不确定性,但未考虑不同可达性模型结果的差异以及行程时间可靠性价值。本文结合各OD之间的行程时间分布特征,构建方差型的行程时间可靠性来描述行程时间不确定性,并进一步将行程时间可靠性纳入到广义出行时间成本中,建立了时间距离模型、潜力模型、累计机会模型和高斯模型4种基于位置的可达性测算方法,以比较在不同测算方法下,行程时间不确定性对可达性的影响。深圳的案例研究表明:① 忽略行程时间不确定性会使全区域的可达性至少被高估5.04%,最大被高估95.04%。潜力模型、时间距离模型、累计机会模型和高斯模型的高估幅度由低到高;② 行程时间不确定性对可达性的影响存在阈值效应,阈值越高,可达性受影响的程度越小;③ 从空间分布来看,行程时间不确定性对可达性水平高和低的区域都有一定影响。若不考虑行程时间不确定性,可达性高的区域高估值大,而在可达性低的区域,可达性高估的百分比较大,高估百分比中位数的差异程度最大可达77.1%;④ 行程时间不确定性对潜力模型可达性分类的影响最小,对累计机会模型差异的影响最大。可达性使用者应充分考虑研究区域实际情况,结合可解释性与理论性偏好,进而选择合适的可达性模型和评判标准。  相似文献   
192.
位置不确定性与属性不确定性的场模型   总被引:23,自引:2,他引:21  
张景雄  杜道生 《测绘学报》1999,28(3):244-250
不确定性是自地理信息系统发展与应用以来一个引起关注的课题。位置不确定性与属性不确定常常不加区分地被看作是可以单个讨论的问题。本文将借助场的概念和模型使二者得以统一的描述和分析;对于明确定义的离散目标,二者虽然可分别讨论,但却在数学上有着联合的基础;对于非明确定义的地理现象,二者以连续体的形式而存在,位置不确定性可以作为属性不确定性的空间映射而提取出来。  相似文献   
193.
城市空气质量数值预报的不确定性与可预报性   总被引:1,自引:0,他引:1  
主要综述了数据误差、随机误差和模式物理误差所造成的城市空气质量数值预报的不确定性,简要介绍分析预报不确定性的统计方法。并对由内在随机性和外在误差引起的可预报性问题进行了分析讨论  相似文献   
194.
A stochastic flow representation is considered with the Eulerian velocity decomposed between a smooth large scale component and a rough small-scale turbulent component. The latter is specified as a random field uncorrelated in time. Subsequently, the material derivative is modified and leads to a stochastic version of the material derivative to include a drift correction, an inhomogeneous and anisotropic diffusion, and a multiplicative noise. As derived, this stochastic transport exhibits a remarkable energy conservation property for any realizations. As demonstrated, this pivotal operator further provides elegant means to derive stochastic formulations of classical representations of geophysical flow dynamics.  相似文献   
195.
Complex hydrological models are being increasingly used nowadays for many purposes such as studying the impact of climate and land‐use change on water resources. However, building a high‐fidelity model, particularly at large scales, remains a challenging task, due to complexities in model functioning and behaviour and uncertainties in model structure, parameterization, and data. Global sensitivity analysis (GSA), which characterizes how the variation in the model response is attributed to variations in its input factors (e.g., parameters and forcing data), provides an opportunity to enhance the development and application of these complex models. In this paper, we advocate using GSA as an integral part of the modelling process by discussing its capabilities as a tool for diagnosing model structure and detecting potential defects, identifying influential factors, characterizing uncertainty, and selecting calibration parameters. Accordingly, we conduct a comprehensive GSA of a complex land surface–hydrology model, Modélisation Environmentale–Surface et Hydrologie (MESH), which combines the Canadian land surface scheme with a hydrological routing component, WATROUTE. Various GSA experiments are carried out using a new technique, called Variogram Analysis of Response Surfaces, for alternative hydroclimatic conditions in Canada using multiple criteria, various model configurations, and a full set of model parameters. Results from this study reveal that, in addition to different hydroclimatic conditions and SA criteria, model configurations can also have a major impact on the assessment of sensitivity. GSA can identify aspects of the model internal functioning that are counter‐intuitive and thus help the modeller to diagnose possible model deficiencies and make recommendations for improving development and application of the model. As a specific outcome of this work, a list of the most influential parameters for the MESH model is developed. This list, along with some specific recommendations, is expected to assist the wide community of MESH and Canadian land surface scheme users, to enhance their modelling applications.  相似文献   
196.
Eutrophication of aquatic ecosystems is one of the most pressing water quality concerns in the United States and around the world. Bank erosion has been largely overlooked as a source of nutrient loading, despite field studies demonstrating that this source can account for the majority of the total phosphorus load in a watershed. Substantial effort has been made to develop mechanistic models to predict bank erosion and instability in stream systems; however, these models do not account for inherent natural variability in input values. To quantify the impacts of this omission, uncertainty and sensitivity analyses were performed on the Bank Stability and Toe Erosion Model (BSTEM), a mechanistic model developed by the US Department of Agriculture – Agricultural Research Service (USDA‐ARS) that simulates both mass wasting and fluvial erosion of streambanks. Generally, bank height, soil cohesion, and plant species were found to be most influential in determining stability of clay (cohesive) banks. In addition to these three inputs, groundwater elevation, stream stage, and bank angle were also identified as important in sand (non‐cohesive) banks. Slope and bank height are the dominant variables in fluvial erosion modeling, while erodibility and critical shear stress had low sensitivity indices; however, these indices do not reflect the importance of critical shear stress in determining the timing of erosion events. These results identify important variables that should be the focus of data collection efforts while also indicating which less influential variables may be set to assumed values. In addition, a probabilistic Monte‐Carlo modeling approach was applied to data from a watershed‐scale sediment and phosphorus loading study on the Missisquoi River, Vermont to quantify uncertainty associated with these published results. While our estimates aligned well with previous deterministic modeling results, the uncertainty associated with these predictions suggests that they should be considered order of magnitude estimates only. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   
197.
We assess the effects of prospective climate change until 2100 on water management of two major reservoirs of Iran, namely, Dez (3.34 × 109 m3) and Alavian (6 × 107 m3). We tune the Poly‐Hydro model suited for simulation of hydrological cycle in high altitude snow‐fed catchments. We assess optimal operation rules (ORs) for the reservoirs using three algorithms under dynamic and static operation and linear and non‐linear decision rules during control run (1990–2010 for Dez and 2000–2010 for Alavian). We use projected climate scenarios (plus statistical downscaling) from three general circulation models, EC‐Earth, CCSM4, and ECHAM6, and three emission scenarios, or representative concentration pathways (RCPs), RCP2.6, RCP4.5, and RCP8.5, for a grand total of nine scenarios, to mimic evolution of the hydrological cycle under future climate until 2100. We subsequently test the ORs under the future hydrological scenarios (at half century and end of century) and the need for reoptimization. Poly‐Hydro model when benchmarked against historical data well mimics the hydrological budget of both catchments, including the main processes of evapotranspiration and streamflows. Teaching–learning‐based optimization delivers the best performance in both reservoirs according to objective scores and is used for future operation. Our projections in Dez catchment depict decreased precipitation along the XXI century, with ?1% on average (of the nine scenarios) at half century and ?6% at the end of century, with changes in streamflows on average ?7% yearly and ?13% yearly, respectively. In Alavian, precipitation would decrease by ?10% on average at half century and ?13% at the end of century, with streamflows ?14% yearly and ?18% yearly, respectively. Under the projected future hydrology, reservoirs' operation would provide lower performance (i.e., larger lack of water) than now, especially for Alavian dam. Our results provide evidence of potentially decreasing water availability and less effective water management in water stressed areas like Northern Iran here during this century.  相似文献   
198.
River discharge and nutrient measurements are subject to aleatory and epistemic uncertainties. In this study, we present a novel method for estimating these uncertainties in colocated discharge and phosphorus (P) measurements. The “voting point”‐based method constrains the derived stage‐discharge rating curve both on the fit to available gaugings and to the catchment water balance. This helps reduce the uncertainty beyond the range of available gaugings and during out of bank situations. In the example presented here, for the top 5% of flows, uncertainties are shown to be 139% using a traditional power law fit, compared with 40% when using our updated “voting point” method. Furthermore, the method is extended to in situ and lab analysed nutrient concentration data pairings, with lower uncertainties (81%) shown for high concentrations (top 5%) than when a traditional regression is applied (102%). Overall, for both discharge and nutrient data, the method presented goes some way to accounting for epistemic uncertainties associated with nonstationary physical characteristics of the monitoring site.  相似文献   
199.
This study aimed to map water features using a Landsat image rather than traditional land cover. We involved the original bands, spectral indices and principal components (PCs) of a principal component analysis (PCA) as input data, and performed random forest (RF) and support vector machine (SVM) classification with water, saturated soil and non-water categories. The aim was to compare the efficiency of the results based on various input data. Original bands provided 93% overall accuracy (OA) and bands 4–5–7 were the most informative in this analysis. Except for MNDWI (modified normalized differenced water index, with 98% OA), the performance of all water indices was between 60 and 70% (OA). The PCA-based approach conducted on the original bands resulted in the most accurate identification of all classes (with only 1% error in the case of water bodies). We therefore show that both water bodies and saturated soils can be identified successfully using this approach.  相似文献   
200.
刘航 《地震工程学报》2018,40(5):1118-1123
由于地震灾害的不确定性,使得应急救援设备运行速率及使用效率均受到影响,需要进行并行优化处理。对此,提出基于双向并行计算的地震灾害应急救援设备优化方法。以地震灾区灾情等级评估结果为基础,将地震等级及应急救援设备,设备及设备之间的关系进行标准化处理,转化为求解最优解问题;在考虑不确定性的情况下,通过通信时间与救援设备需求进行双向并行处理,优化地震灾害应急救援设备。实验结果表明,采用改进方法进行地震灾害应急救援设备并行优化,能够对地震灾害应急救援设备需求量进行准确预测,提高应急救援设备的运行速率,缩短通信时间,提高应急救援设备的使用效率,具有一定的优势。  相似文献   
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