Risk minimization in water quality control problems of a river system     

Subimal Ghosh  P.P. Mujumdar 《Advances in water resources》2006

Methodologies are presented for minimization of risk in a river water quality management problem. A risk minimization model is developed to minimize the risk of low water quality along a river in the face of conflict among various stake holders. The model consists of three parts: a water quality simulation model, a risk evaluation model with uncertainty analysis and an optimization model. Sensitivity analysis, First Order Reliability Analysis (FORA) and Monte–Carlo simulations are performed to evaluate the fuzzy risk of low water quality. Fuzzy multiobjective programming is used to formulate the multiobjective model. Probabilistic Global Search Laussane (PGSL), a global search algorithm developed recently, is used for solving the resulting non-linear optimization problem. The algorithm is based on the assumption that better sets of points are more likely to be found in the neighborhood of good sets of points, therefore intensifying the search in the regions that contain good solutions. Another model is developed for risk minimization, which deals with only the moments of the generated probability density functions of the water quality indicators. Suitable skewness values of water quality indicators, which lead to low fuzzy risk are identified. Results of the models are compared with the results of a deterministic fuzzy waste load allocation model (FWLAM), when methodologies are applied to the case study of Tunga–Bhadra river system in southern India, with a steady state BOD–DO model. The fractional removal levels resulting from the risk minimization model are slightly higher, but result in a significant reduction in risk of low water quality.  相似文献   

Calibration framework for a Kalman filter applied to a groundwater model     

Jean-Philippe Drécourt  Henrik Madsen  Dan Rosbjerg 《Advances in water resources》2006

The paper presents a novel approach to the setup of a Kalman filter by using an automatic calibration framework for estimation of the covariance matrices. The calibration consists of two sequential steps: (1) Automatic calibration of a set of covariance parameters to optimize the performance of the system and (2) adjustment of the model and observation variance to provide an uncertainty analysis relying on the data instead of ad-hoc covariance values. The method is applied to a twin-test experiment with a groundwater model and a colored noise Kalman filter. The filter is implemented in an ensemble framework. It is demonstrated that lattice sampling is preferable to the usual Monte Carlo simulation because its ability to preserve the theoretical mean reduces the size of the ensemble needed. The resulting Kalman filter proves to be efficient in correcting dynamic error and bias over the whole domain studied. The uncertainty analysis provides a reliable estimate of the error in the neighborhood of assimilation points but the simplicity of the covariance models leads to underestimation of the errors far from assimilation points.  相似文献   

1976年云南龙陵7．4级地震序列分析   总被引：5，自引：0，他引：5       下载免费PDF全文

左兆荣  张国民 《地球物理学报》1996,39(5):653-659

地震成核是地震孕育过程中的一个至关重要的阶段，加速是成核过程的一个属性，也是地震失稳破裂的一个必要条件．地震加速释放是成核在脆性层中的大地震的普遍前兆，且可将该加速过程简要地概括为地震释放速率正比于失稳破裂剩余时间的负幂．基于这一原理，对１９７６年５月２９日云南龙陵Ｍ_ｓ７．４级地震序列进行回顾性分析，表明主震及后续显著地震的失稳破裂时间和震级可成功地被估算，但要求所测系数ｒ^２  相似文献   

地理信息系统中几何特征不确定性的通用模型：从1维到N维   总被引：6，自引：1，他引：6  

史文中 《测绘学报》1997,26(2):160-167

本文提出了描述地理信息系统中几何特征位置不确定性的一个通用模型，从１维到Ｎ维，在每１维中，ＧＩＳ中的特征被划分为点，线段及线性特征。由于ＧＩＳ中数据含有误差。这些特征在ＧＩＳ中位置未必与其现实世界中的真实位置一致，而其真实位置只是在围绕着ＧＩＳ中量测位置的某一个区域内，本文提出的模型给出了这些区域的统计描述。  相似文献   

UNCERTAINTY IN THE SPECIFICATION OF SURFACE CHARACTERISTICS: A STUDY OF PREDICTION ERRORS IN THE BOUNDARY LAYER   总被引：1，自引：0，他引：1  

Kiran Alapaty  Sethu Raman  Devdutta S. Niyogi 《Boundary-Layer Meteorology》1997,82(3):475-502

The effects of uncertainty in the specification of surface characteristics on simulated atmospheric boundary layer (ABL) processes and structure were investigated using a one-dimensional soil-vegetation-boundary layer model. Observational data from the First International Satellite Land Surface Climatology Project Field Experiment were selected to quantify prediction errors in simulated boundary-layer parameters. Several numerical 12-hour simulations were performed to simulate the convective boundary-layer structure, starting at 0700 LT 6 June 1987.In the control simulation, measured surface parameters and atmospheric data were used to simulate observed boundary-layer processes. In the remaining simulations, five surface parameters – soil texture, initial soil moisture, minimum stomatal resistance, leaf area index, and vegetation cover – were varied systematically to study how uncertainty in the specification of these surface parameters affects simulated boundary-layer processes.The simulated uncertainty in the specification of these five surface parameters resulted in a wide range of errors in the prediction of turbulent fluxes, mean thermodynamic structure, and the depth of the ABL. Under certain conditions uncertainty in the specifications of soil texture and minimum stomatal resistance had the greatest influence on the boundary-layer structure. A lesser but still moderately strong effect on the simulated ABL resulted from (1) a small decrease (4%) in the observed initial soil moisture (although a large increase [40%] had only a marginal effect), and (2) a large reduction (66%) in the observed vegetation cover. High uncertainty in the specification of leaf area index had only a marginal impact on the simulated ABL. It was also found that the variations in these five surface parameters had a negligible effect on the simulated horizontal wind fields. On the other hand, these variations had a significant effect on the vertical distribution of turbulent heat fluxes, and on the predicted maximum boundary-layer depth, which varied from about 1400–2300 m across the 11 simulations. Thus, uncertainties in the specification of surface parameters can significantly affect the simulated boundary-layer structure in terms of meteorological and air quality model predictions.  相似文献   

基于承载复合体的隧道位移反分析研究     

沈才华  刘松玉  童立元 《工程地质学报》2008,16(2):263-267

初期支护与松动圈围岩的协调作用表现出很大的不确定性,其主要影响因素包括:初期支护施工本身导致初期支护的不均匀性,实际围岩的不确定性对初期支护的影响,围岩释放应力的不均匀性导致的初期支护内力分布的不确定性。文章把初期支护的支护和围岩自身自稳能力看成是双介质的承载复合体,采用最小二乘法建立目标函数,结合单纯形算法,进行初期支护与扰动区的联合位移反分析,充分揭示了初期支护与围岩松动圈之间的协调作用;结合实际工程与不考虑初期支护不确定性因素影响的反演分析进行对比,结果显示本文方法反演精度提高39％,预测精度提高了13％。  相似文献   

Application of a data‐based mechanistic modelling (DBM) approach for predicting runoff generation in semi‐arid regions     

S. Mwakalila  P. Campling  J. Feyen  G. Wyseure  K. Beven 《水文研究》2001,15(12):2281-2295

This paper addresses the application of a data‐based mechanistic (DBM) modelling approach using transfer function models (TFMs) with non‐linear rainfall filtering to predict runoff generation from a semi‐arid catchment (795 km²) in Tanzania. With DBM modelling, time series of rainfall and streamflow were allowed to suggest an appropriate model structure compatible with the data available. The model structures were evaluated by looking at how well the model fitted the data, and how well the parameters of the model were estimated. The results indicated that a parallel model structure is appropriate with a proportion of the runoff being routed through a fast flow pathway and the remainder through a slow flow pathway. Finally, the study employed a Generalized Likelihood Uncertainty Estimation (GLUE) methodology to evaluate the parameter sensitivity and predictive uncertainty based on the feasible parameter ranges chosen from the initial analysis of recession curves and calibration of the TFM. Results showed that parameters that control the slow flow pathway are relatively more sensitive than those that control the fast flow pathway of the hydrograph. Within the GLUE framework, it was found that multiple acceptable parameter sets give a range of predictions. This was found to be an advantage, since it allows the possibility of assessing the uncertainty in predictions as conditioned on the calibration data and then using that uncertainty as part of the decision‐making process arising from any rainfall‐runoff modelling project. Copyright © 2001 John Wiley & Sons, Ltd.  相似文献   

Reducing geological uncertainty by conditioning on boreholes: the coupled Markov chain approach     

Amro M. M. Elfeki  F. M. Dekking 《Hydrogeology Journal》2007,15(8):1439-1455

The CMC (coupled Markov chain) model, which is based on the extension of Markov chains in two-dimensions, is used in the reduction of uncertainty in geological structures when conditioned (i.e., honours the data and their location) on a number of boreholes. The model has been applied to an unconsolidated aquifer deposit located in the central Rhine-Meuse delta (the Gorkum study area) in the Netherlands. A comparison is also made between the CMC and the SIS (sequential indicator simulation) model, which is based on Kriging and co-Kriging theories on the same deposit. The results show the potential applicability of the CMC model in reducing the uncertainty in geological configurations when a sufficient number of boreholes is available. Reproduction of the global geological features requires relatively few boreholes (in this case study, nine boreholes with 30-m spacing over a distance of 240 m). However, reproduction of the proportion of each state requires a relatively large number of boreholes (in this case study 31 boreholes with 8-m spacing over a distance of 240 m). It has been shown that variograms can be deceptive in modeling the spatial pattern and that they reflect only part of the complete spatial structure in the field. The use of transition probabilities via the CMC model provides a better alternative approach, because it uses multiple point information. Amro M. M. Elfeki on leave from Department of Irrigation and Hydraulics, Faculty of Engineering, Mansoura University, Mansoura, Egypt  相似文献   

Assessment of radionuclide transport uncertainty in the unsaturated zone of Yucca Mountain     

Ming Ye  Feng Pan  Yu-Shu Wu  Bill X. Hu  Craig Shirley  Zhongbo Yu 《Advances in water resources》2007

The present study assesses the uncertainty of flow and radionuclide transport in the unsaturated zone at Yucca Mountain using a Monte Carlo method. Matrix permeability, porosity, and sorption coefficient are considered random. Different from previous studies that assume distributions of the parameters, the distributions are determined in this study by applying comprehensive transformations and rigorous statistics to on-site measurements of the parameters. The distribution of permeability is further adjusted based on model calibration results. Correlation between matrix permeability and porosity is incorporated using the Latin Hypercube Sampling method. After conducting 200 Monte Carlo simulations of three-dimensional unsaturated flow and radionuclide transport for conservative and reactive tracers, the mean, variances, and 5th, 50th, and 95th percentiles for quantities of interest (e.g., matrix liquid saturation and water potential) are evaluated. The mean and 50th percentile are used as the mean predictions, and their associated predictive uncertainties are measured by the variances and the 5th and 95th percentiles (also known as uncertainty bounds). The mean predictions of matrix liquid saturation and water potential are in reasonable agreement with corresponding measurements. The uncertainty bounds include a large portion of the measurements, suggesting that the data variability can be partially explained by parameter uncertainty. The study illustrates propagation of predictive uncertainty of percolation flux, increasing downward from repository horizon to water table. Statistics from the breakthrough curves indicate that transport of the reactive tracer is delayed significantly by the sorption process, and prediction on the reactive tracer is of greater uncertainty than on the conservative tracer because randomness in the sorption coefficient increases the prediction uncertainty. Uncertainty in radionuclide transport is related to uncertainty in the percolation flux, suggesting that reducing the former entails reduction in the latter.  相似文献   

Accounting for the uncertainty in the local mean in spatial prediction by Bayesian Maximum Entropy   总被引：2，自引：2，他引：2  

T. G. Orton  R. M. Lark 《Stochastic Environmental Research and Risk Assessment (SERRA)》2007,21(6):773-784

Bayesian Maximum Entropy (BME) has been successfully used in geostatistics to calculate predictions of spatial variables given some general knowledge base and sets of hard (precise) and soft (imprecise) data. This general knowledge base commonly consists of the means at each of the locations considered in the analysis, and the covariances between these locations. When the means are not known, the standard practice is to estimate them from the data; this is done by either generalized least squares or maximum likelihood. The BME prediction then treats these estimates as the general knowledge means, and ignores their uncertainty. In this paper we develop a prediction that is based on the BME method that can be used when the general knowledge consists of the covariance model only. This prediction incorporates the uncertainty in the estimated local mean. We show that in some special cases our prediction is equal to results from classical geostatistics. We investigate the differences between our approach and the standard approach for predicting in this common practical situation.  相似文献