Capturing the essential spatial variability in distributed hydrological modelling: Infiltration parameters     

Nadim S. Farajalla  Baxter E. Vieux 《水文研究》1995,9(1):55-68

Selecting the correct resolution in distributed hydrological modelling at the watershed scale is essential in reducing scale-related errors. The work presented herein uses information content (entropy) to identify the resolution which captures the essential variability, at the watershed scale, of the infiltration parameters in the Green and Ampt infiltration equation. A soil map of the Little Washita watershed in south-west Oklahoma, USA was used to investigate the effects of grid cell resolution on the distributed modelling of infiltration. Soil-derived parameters and infiltration exhibit decreased entropy as resolutions become coarser. This is reflected in a decrease in the maximum entropy value for the reclassified/derived parameters vis a vis the original data. Moreover, the entropy curve, when plotted against resolution, shows two distinct segments: a constant section where no entropy was lost with decreasing resolution and another part which is characterized by a sharp decrease in entropy after a critical resolution of 1209 m is reached. This methodology offers a technique for assessing the largest cell size that captures the spatial variability of infiltration parameters for a particular basin. A geographical information system (GIS) based rainfall-runoff model is used to simulate storm hydrographs using infiltration parameter maps at different resolutions as inputs. Model results up to the critical resolution are reproducible and errors are small. However, at resolutions beyond the critical resolution the results are erratic with large errors. A major finding of this study is that a large resolution (1209 m for this basin) yields reproducible model results. When modelling a river basin using a distributed model, the resolution (grid cell size) can drastically affect the model results and calibration. The error structure attributable to grid cell resolution using entropy as a spatial variability measure is shown.  相似文献   

大气热力学的若干新发展          下载免费PDF全文

曹鸿兴 《应用气象学报》2005,16(4):554-416

对自20世纪80年代以来的大气热力学发展进行了综合评述, 阐述了如城市热岛效应、全球增暖等非传统大气热力学问题; 基于大气非平衡态热力学的非线性理论, 提出应发展突显热力学作用的数值模式, 并阐述其必要性和可能性。  相似文献   

高温铀物种形成(Speciation)的热力学数据     

黄克玲  周鲁民  张景廉 《铀矿地质》1993,(6)

本文依据C.M.Criss和J.W.Cobble的“离子熵对应原理”,对1978年D.Langmuir给出的铀物种形成常温热力学数据进行了高温值的处理,得出了一套较全面而系统的高温热力学参数,以供参考使用。  相似文献   

隐伏煤田的TM信息提取及地质效果   总被引：3，自引：0，他引：3  

刘玉荣  王四龙  凌怡淙  宁书年  许孝庭 《国土资源遥感》1997,8(3):29-33

在遥感图像上,被巨厚第四系冲积层覆盖的煤田区隐伏地质构造和火成岩分布信息是一种非直接的、微弱的隐伏信息,本文以淮北煤田为实例,探讨了从TM图像上提取这种信息的可行性与方法,并分析了其地质效果。  相似文献   

ALow-order　Model　of　Two-dimensional　Fluid　Dynamics　on　the　Surface　of　a　Sphere     

Mozheng Wei 《大气科学进展》1996,13(1):67-90

ＡＬｏｗ－ｏｒｄｅｒＭｏｄｅｌｏｆＴｗｏ－ｄｉｍｅｎｓｉｏｎａｌＦｌｕｉｄＤｙｎａｍｉｃｓｏｎｔｈｅＳｕｒｆａｃｅｏｆａＳｐｈｅｒｅＭｏｚｈｅｎｇＷｅｉ（ＣＲＣｆｏｒＳｏｕｔｈｅｒｎＨｅｍｉｓｐｈｅｒｅＭｅｔｅｏｒｏｌｏｇｙ，ＣＳＩＲＯＤｉｖｉｓｉｏ...  相似文献   

历史文献中气候信息的评价   总被引：17，自引：1，他引：17  

葛全胜  张丕远 《地理学报》1990,45(1):22-30

本文对我国史料中所载气候信息进行了评价。结论是:①对于史料所载的某一气候事件,我们将其状态分辨取越细,所获取的信息越少;②在分析过程中,对误差要求低些,所获取的信息反而高些;③就已记录的气候事件而言,官方组织的记载所提供的气候信息最多,私人笔札次之,方志类书最次。  相似文献   

Assessment of reliability in water distribution networks using entropy based measures   总被引：2，自引：0，他引：2  

K. Awumah  I. Goulter  S. K. Bhatt 《Stochastic Environmental Research and Risk Assessment (SERRA)》1990,4(4):309-320

Entropy based expressions for measurement of reliability and redundancy have recently been reported. These measures approach assessment of the reliability of the distribution network from the intrinsic redundancy of the network layout. The paper extends earlier work on entropy functions by including a more explicit statement of the alternate paths available in the network and by recognizing that under certain circumstances, e.g., failure of some part of the network work, an outflow link from a node under normal working condition may become an inflow link to the same node. The measures are assessed by comparison with parameters measuring Nodal Pair Reliability and percentage of flow supplied at adequate pressure for a range of networks and link failure conditions in this networks. The entropy measures are shown to reflect changes in the network reliability, as measured by these two comparative parameters, very well.  相似文献   

从熵原理得出的雨量时程方程   总被引：17，自引：0，他引：17  

张学文  马淑红  马力 《大气科学》1991,15(6):17-25

本文从熵极大原理出发导出了在一次降水过程中降水强度与其历时为负指数关系。并从中引出几个实用方程。这一结果与Paulhus等给出的经验方程在函数形状上类似。 本文通过对400多次遍及中国各地的降水自记记录分析证实,此理论公式与实况的平均相对偏差为10.7％,比Paulhus等的公式相对偏差小了5％。 此结果可用于暴雨、防洪服务和水利工程设计中。这启示人们熵极大原理在气象水文领域有应用潜力。  相似文献   

A univariate model for long-term streamflow forecasting   总被引：1，自引：0，他引：1  

P. F. Krstanovic  V. P. Singh 《Stochastic Environmental Research and Risk Assessment (SERRA)》1991,5(3):173-188

This paper, the first in a series of two, employs the principle of maximum entropy (POME) via maximum entropy spectral analysis (MESA) to develop a univariate model for long-term streamflow forecasting. Three cases of streamflow forecasting are investigated: forward forecasting, backward forecasting (or reconstruction) and intermittent forecasting (or filling in missing records). Application of the model is discussed in the second paper.  相似文献   

Bayesian data fusion in a spatial prediction context: a general formulation   总被引：1，自引：1，他引：1  

P. Bogaert  D. Fasbender 《Stochastic Environmental Research and Risk Assessment (SERRA)》2007,21(6):695-709

In spite of the exponential growth in the amount of data that one may expect to provide greater modeling and predictions opportunities, the number and diversity of sources over which this information is fragmented is growing at an even faster rate. As a consequence, there is real need for methods that aim at reconciling them inside an epistemically sound theoretical framework. In a statistical spatial prediction framework, classical methods are based on a multivariate approach of the problem, at the price of strong modeling hypotheses. Though new avenues have been recently opened by focusing on the integration of uncertain data sources, to the best of our knowledges there have been no systematic attemps to explicitly account for information redundancy through a data fusion procedure. Starting from the simple concept of measurement errors, this paper proposes an approach for integrating multiple information processing as a part of the prediction process itself through a Bayesian approach. A general formulation is first proposed for deriving the prediction distribution of a continuous variable of interest at unsampled locations using on more or less uncertain (soft) information at neighboring locations. The case of multiple information is then considered, with a Bayesian solution to the problem of fusing multiple information that are provided as separate conditional probability distributions. Well-known methods and results are derived as limit cases. The convenient hypothesis of conditional independence is discussed by the light of information theory and maximum entropy principle, and a methodology is suggested for the optimal selection of the most informative subset of information, if needed. Based on a synthetic case study, an application of the methodology is presented and discussed.  相似文献