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1.
In this paper, different methods for generating synthetic earthquakes are compared in terms of related non-linear seismic response of ductile structures. The objective of the investigation is to formulate recommendations for the use of synthetic earthquakes for reliable seismic analysis. The comparison is focused on the accuracy of the reproduction of the characteristics of the structural non-linear response due to recorded earthquakes. First the investigations are carried out for non-linear single-degree-of-freedom systems. Later, the results are validated for a set of realistic buildings modelled as multi-degree-of-freedom systems. Various options of the classical stationary simulation procedure of SIMQKE and a non-stationary simulation procedure proposed by Sabetta and Pugliese are examined and compared. The adopted methodology uses a set of recorded earthquakes as a reference. Hundred synthetic accelerograms are generated for each examined simulation option with the condition that the related elastic responses are similar to those of the reference set. The non-linear single-degree-of-freedom systems are defined using six recognized hysteretic models and four levels of increasing non-linearity. The non-linear responses computed for the reference set and the studied simulation options are then statistically compared in terms of displacement ductility and energy. The results show that the implementation of the classical stationary procedure always leads to a significant underestimation of the ductility demand and a significant overestimation of the energy demand. By contrast, non-stationary time histories produce much better results. The results with the multi-degree-of-freedom systems are shown to confirm these conclusions.  相似文献   

2.
Selection of ground motion time series and limits on scaling   总被引：4，自引：0，他引：4  
A procedure to select time series for use in non-linear analyses that are intended to result in an average response of the non-linear system is proposed that is not based simply on magnitude, distance, and spectral shape. A simple model of a yielding system is used as a proxy for the non-linear behavior of a more complicated yielding system. As an example, Newmark displacements are used as a proxy for more complex slope-stability models. The candidate scaled time series are evaluated to find those that yield a response of the simple non-linear system that is near the expected response for the design event. Those scaled time series with responses near the expected value are selected as the optimum time series for defining average response even if the scale factors are larger than commonly accepted (e.g. scale factors >factor of 2).  相似文献   

3.
In this paper, a new non-linear fuzzy-set based methodology is proposed to characterize and propagate uncertainty through a multiple linear regression (MLR) model to predict DO using flow and water temperature as the regressors. The output is depicted as probabilistic rather than deterministic and is used to calculate the risk of low DO concentration. To demonstrate the new method, data from the Bow River in Calgary, Alberta from 2006 to 2008 are used. Low DO concentration has been occasionally observed in the river and correctly predicting, and quantifying the associated uncertainty and variability of DO is of interest to the City of Calgary. Flow, temperature and DO data were used to construct five MLR models, using different combinations of linear and non-linear fuzzy membership functions. The results show that non-linear representation of variance is superior to the linear approach based on model performance. Normal and Gumbel based membership functions produced the best results. The outputs from two non-linear fuzzy membership models were used to calculate risk of low DO. The predicted risk was between 3.9 and 4.9 %. This is an improvement over the traditional method, which can not indicate a risk of low DO for the same time period. This study demonstrates that water resource managers can adequately use MLR models to predict the risk of low DO using abiotic factors.  相似文献   

4.
湖泊富营养化响应与流域优化调控决策的模型研究进展   总被引：2，自引：0，他引：2  
湖泊富营养化是全球水环境领域面临的长期挑战,富营养化响应与流域优化决策模型是制定经济和高效调控方案的关键.然而已有的模型研究综述主要集中于模型开发、案例应用、敏感性分析、不确定性分析等单一方面,而缺少针对非线性响应、生态系统长期演变等最新湖泊治理挑战的研究总结.本文对数据驱动的统计模型、因果驱动的机理模型和决策导向的优化模型进行了综述.其中,统计模型包含经典统计、贝叶斯统计和机器学习模型,常用于建立响应关系、时间序列特征分析以及预报预警;机理模型包含流域的水文与污染物输移模拟以及湖泊的水文、水动力、水质、水生态等过程的模拟,用于不同时空尺度的变化过程模拟,其中复杂机理模型的敏感性分析、参数校验、模型不确定性等需要较高的计算成本;优化模型结合机理模型形成“模拟优化”体系,在不确定性条件下衍生出随机、区间优化等多种方法,通过并行计算、简化与替代模型可一定程度上解决计算时间成本的瓶颈.本文识别了湖泊治理面临的挑战,包括:①如何定量表征外源输入的非线性叠加和湖泊氮、磷、藻变化的非均匀性?②如何提高优化调控决策和水质目标的关联与精准性?③如何揭示湖泊生态系统的长期变化轨迹与驱动因素?最后,本文针对这些挑战提出研究展望,主要包括:①基于多源数据融合与机器学习算法以提升湖泊的短期水质预测精度;②以生物量为基础的机理模型与行为驱动的个体模型的升尺度或降尺度耦合以表达多种尺度的物质交互过程;③机器学习算法与机理模型的直接耦合或数据同化以降低模拟误差;④时空尺度各异的多介质模拟模型融合以实现精准和动态的优化调控.  相似文献   

5.
Available water resources are often not sufficient or too polluted to satisfy the needs of all water users. Therefore, allocating water to meet water demands with better quality is a major challenge in reservoir operation. In this paper, a methodology to develop operating strategies for water release from a reservoir with acceptable quality and quantity is presented. The proposed model includes a genetic algorithm (GA)-based optimization model linked with a reservoir water quality simulation model. The objective function of the optimization model is based on the Nash bargaining theory to maximize the reliability of supplying the downstream demands with acceptable quality, maintaining a high reservoir storage level, and preventing quality degradation of the reservoir. In order to reduce the run time of the GA-based optimization model, the main optimization model is divided into a stochastic and a deterministic optimization model for reservoir operation considering water quality issues.The operating policies resulted from the reservoir operation model with the water quantity objective are used to determine the released water ranges (permissible lower and upper bounds of release policies) during the planning horizon. Then, certain values of release and the optimal releases from each reservoir outlet are determined utilizing the optimization model with water quality objectives. The support vector machine (SVM) model is used to generate the operating rules for the selective withdrawal from the reservoir for real-time operation. The results show that the SVM model can be effectively used in determining water release from the reservoir. Finally, the copula function was used to estimate the joint probability of supplying the water demand with desirable quality as an evaluation index of the system reliability. The proposed method was applied to the Satarkhan reservoir in the north-western part of Iran. The results of the proposed models are compared with the alternative models. The results show that the proposed models could be used as effective tools in reservoir operation.  相似文献   

6.
An ANN application for water quality forecasting   总被引：12，自引：0，他引：12  
Rapid urban and coastal developments often witness deterioration of regional seawater quality. As part of the management process, it is important to assess the baseline characteristics of the marine environment so that sustainable development can be pursued. In this study, artificial neural networks (ANNs) were used to predict and forecast quantitative characteristics of water bodies. The true power and advantage of this method lie in its ability to (1) represent both linear and non-linear relationships and (2) learn these relationships directly from the data being modeled. The study focuses on Singapore coastal waters. The ANN model is built for quick assessment and forecasting of selected water quality variables at any location in the domain of interest. Respective variables measured at other locations serve as the input parameters. The variables of interest are salinity, temperature, dissolved oxygen, and chlorophyll-a. A time lag up to 2Deltat appeared to suffice to yield good simulation results. To validate the performance of the trained ANN, it was applied to an unseen data set from a station in the region. The results show the ANN's great potential to simulate water quality variables. Simulation accuracy, measured in the Nash-Sutcliffe coefficient of efficiency (R(2)), ranged from 0.8 to 0.9 for the training and overfitting test data. Thus, a trained ANN model may potentially provide simulated values for desired locations at which measured data are unavailable yet required for water quality models.  相似文献   

7.
Two types of fuzzy inference systems (FIS) are used for predicting municipal water consumption time series. The FISs used include an adaptive neuro-fuzzy inference system (ANFIS) and a Mamdani fuzzy inference systems (MFIS). The prediction models are constructed based on the combination of the antecedent values of water consumptions. The performance of ANFIS and MFIS models in training and testing phases are compared with the observations and the best fit model is identified according to the selected performance criteria. The results demonstrated that the ANFIS model is superior to MFIS models and can be successfully applied for prediction of water consumption time series.  相似文献   

8.
A finite element procedure to model the non-linear earthquake response of concrete gravity dam systems is presented. A two-dimensional idealization is adopted for the dam and water in order to simplify the analysis and reduce the computational effort. The foundation of the dam is modelled as a rigid rectangular massless plate attached to a three-dimensional viscoelastic half-space. The non-linear behaviour is represented by smearing techniques and includes tensile cracking with subsequent opening, closing and sliding, as well as water cavitation in the reservoir. Special treatments are applied to suppress spurious oscillations in the water response associated with cavitation and to prevent cracks in the dam from spreading into wide zones. Experience from non-linear analyses is cited as it affects the design of the algorithm.  相似文献   

9.
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   

10.
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11.
Hassan AE 《Ground water》2004,42(2):277-290
Many sites of ground water contamination rely heavily on complex numerical models of flow and transport to develop closure plans. This complexity has created a need for tools and approaches that can build confidence in model predictions and provide evidence that these predictions are sufficient for decision making. Confidence building is a long-term, iterative process and the author believes that this process should be termed model validation. Model validation is a process, not an end result. That is, the process of model validation cannot ensure acceptable prediction or quality of the model. Rather, it provides an important safeguard against faulty models or inadequately developed and tested models. If model results become the basis for decision making, then the validation process provides evidence that the model is valid for making decisions (not necessarily a true representation of reality). Validation, verification, and confirmation are concepts associated with ground water numerical models that not only do not represent established and generally accepted practices, but there is not even widespread agreement on the meaning of the terms as applied to models. This paper presents a review of model validation studies that pertain to ground water flow and transport modeling. Definitions, literature debates, previously proposed validation strategies, and conferences and symposia that focused on subsurface model validation are reviewed and discussed. The review is general and focuses on site-specific, predictive ground water models used for making decisions regarding remediation activities and site closure. The aim is to provide a reasonable starting point for hydrogeologists facing model validation for ground water systems, thus saving a significant amount of time, effort, and cost. This review is also aimed at reviving the issue of model validation in the hydrogeologic community and stimulating the thinking of researchers and practitioners to develop practical and efficient tools for evaluating and refining ground water predictive models.  相似文献   

12.
In this paper, optimal operating rules for water quality management in reservoir–river systems are developed using a methodology combining a water quality simulation model and a stochastic GA-based conflict resolution technique. As different decision-makers and stakeholders are involved in the water quality management in reservoir–river systems, a new stochastic form of the Nash bargaining theory is used to resolve the existing conflict of interests related to water supply to different demands, allocated water quality and waste load allocation in downstream river. The expected value of the Nash product is considered as the objective function of the model which can incorporate the inherent uncertainty of reservoir inflow. A water quality simulation model is also developed to simulate the thermal stratification cycle in the reservoir, the quality of releases from different outlets as well as the temporal and spatial variation of the pollutants in the downstream river. In this study, a Varying Chromosome Length Genetic Algorithm (VLGA), which has computational advantages comparing to other alternative models, is used. VLGA provides a good initial solution for Simple Genetic Algorithms and comparing to Stochastic Dynamic Programming (SDP) reduces the number of state transitions checked in each stage. The proposed model, which is called Stochastic Varying Chromosome Length Genetic Algorithm with water Quality constraints (SVLGAQ), is applied to the Ghomrud Reservoir–River system in the central part of Iran. The results show, the proposed model for reservoir operation and waste load allocation can reduce the salinity of the allocated water demands as well as the salinity build-up in the reservoir.  相似文献   

13.
The methods behind the predefined impulse response function in continuous time (PIRFICT) time series model are extended to cover more complex situations where multiple stresses influence ground water head fluctuations simultaneously. In comparison to autoregressive moving average (ARMA) time series models, the PIRFICT model is optimized for use on hydrologic problems. The objective of the paper is twofold. First, an approach is presented for handling multiple stresses in the model. Each stress has a specific parametric impulse response function. Appropriate impulse response functions for other stresses than precipitation are derived from analytical solutions of elementary hydrogeological problems. Furthermore, different stresses do not need to be connected in parallel in the model, as is the standard procedure in ARMA models. Second, general procedures are presented for modeling and interpretation of the results. The multiple-input PIRFICT model is applied to two real cases. In the first one, it is shown that this model can effectively decompose series of ground water head fluctuations into partial series, each representing the influence of an individual stress. The second application handles multiple observation wells. It is shown that elementary physical knowledge and the spatial coherence in the results of multiple wells in an area may be used to interpret and check the plausibility of the results. The methods presented can be used regardless of the hydrogeological setting. They are implemented in a computer package named Menyanthes (www.menyanthes.nl).  相似文献   

14.
By utilizing functional relationships based on observations at plot or field scales, water quality models first compute surface runoff and then use it as the primary governing variable to estimate sediment and nutrient transport. When these models are applied at watershed scales, this serial model structure, coupling a surface runoff sub-model with a water quality sub-model, may be inappropriate because dominant hydrological processes differ among scales. A parallel modeling approach is proposed to evaluate how best to combine dominant hydrological processes for predicting water quality at watershed scales. In the parallel scheme, dominant variables of water quality models are identified based entirely on their statistical significance using time series analysis. Four surface runoff models of different model complexity were assessed using both the serial and parallel approaches to quantify the uncertainty on forcing variables used to predict water quality. The eight alternative model structures were tested against a 25-year high-resolution data set of streamflow, suspended sediment discharge, and phosphorous discharge at weekly time steps. Models using the parallel approach consistently performed better than serial-based models, by having less error in predictions of watershed scale streamflow, sediment and phosphorus, which suggests model structures of water quantity and quality models at watershed scales should be reformulated by incorporating the dominant variables. The implication is that hydrological models should be constructed in a way that avoids stacking one sub-model with one set of scale assumptions onto the front end of another sub-model with a different set of scale assumptions.  相似文献   

15.
The hydrodynamic characterization of the epikarst, the shallow part of the unsaturated zone in karstic systems, has always been challenging for geophysical methods. This work investigates the feasibility of coupling time‐lapse refraction seismic data with petrophysical and hydrologic models for the quantitative determination of water storage and residence time at shallow depth in carbonate rocks. The Biot–Gassmann fluid substitution model describing the seismic velocity variations with water saturation at low frequencies needs to be modified for this lithology. I propose to include a saturation‐dependent rock‐frame weakening to take into account water–rock interactions. A Bayesian inversion workflow is presented to estimate the water content from seismic velocities measured at variable saturations. The procedure is tested first with already published laboratory measurements on core samples, and the results show that it is possible to estimate the water content and its uncertainty. The validated procedure is then applied to a time‐lapse seismic study to locate and quantify seasonal water storage at shallow depth along a seismic profile. The residence time of the water in the shallow layers is estimated by coupling the time‐lapse seismic measurements with rainfall chronicles, simple flow equations, and the petrophysical model. The daily water input computed from the chronicles is used to constraint the inversion of seismic velocities for the daily saturation state and the hydrodynamic parameters of the flow model. The workflow is applied to a real monitoring case, and the results show that the average residence time of the water in the epikarst is generally around three months, but it is only 18 days near an infiltration pathway. During the winter season, the residence times are three times shorter in response to the increase in the effective rainfall.  相似文献   

16.
Stochastic models are often fitted to historical data in order to produce streamflow scenarios. These scenarios are used as input data for simulation/optimization models that support operational decisions for water resource systems. The streamflow scenarios are sampled from probability distributions conditioned on the available information, such as recent streamflow data. In this paper we introduce a procedure for further conditioning the probability distributions by considering the recent measurements of climatic variables, such as sea temperatures, that are used to describe the occurrence of El Ni?o. We adopt an auto-regressive model and use the “El Ni?o information” to refine the parameter estimation process for each time step. The corresponding methodology is tested for the monthly energy time series, “inflowing” to the power plants of Colombia. This is a linear combination of streamflow values for the 18 most important rivers of the country.  相似文献   

17.
A two-dimensional vertically integrated hydrodynamic finite-element model of the west coast of Britain is used to examine the response of the region to extreme meteorological forcing. The extent to which tide–surge interaction modifies the computed surge elevation and current distributions is examined in detail. The nature of the finite-element model with its ability to refine the mesh in nearshore regions is ideal for examining the influence of non-linear effects upon surges in these regions. Calculations using spatially uniform orthogonal wind stresses show that the surge elevation and current in shallow water are particularly sensitive to the method used to remove the tide as a result of the highly non-linear nature of the tide–surge interaction in these regions. The most accurate means of de-tiding the solution is by subtracting a tide derived by harmonic analysis of the tide and surge time series at the time of the surge. Subtracting a tide-only solution (the usual approach) leads to tidal energy leaking into the surge solution. Calculations show that this arises because the surge modifies the tidal amplitude and phase in shallow-water regions to such an extent that they are appreciably different to those found in the tide-only calculation. Results suggest that this problem becomes more important, as nearshore meshes are refined in an attempt to improve surge prediction. This suggests that in the future, highly accurate fine-mesh models will be required to compute total water levels without the present linear separation into tidal and surge signal used in operational surge prediction.  相似文献   

18.
Representation of agricultural conservation practices with SWAT   总被引：5，自引：0，他引：5  
Results of modelling studies for the evaluation of water quality impacts of agricultural conservation practices depend heavily on the numerical procedure used to represent the practices. Herein, a method for the representation of several agricultural conservation practices with the Soil and Water Assessment Tool (SWAT) is developed and evaluated. The representation procedure entails identifying hydrologic and water quality processes that are affected by practice implementation, selecting SWAT parameters that represent the affected processes, performing a sensitivity analysis to ascertain the sensitivity of model outputs to selected parameters, adjusting the selected parameters based on the function of conservation practices, and verifying the reasonableness of the SWAT results. This representation procedure is demonstrated for a case study of a small agricultural watershed in Indiana in the Midwestern USA. The methods developed in the present work can be applied with other watershed models that employ similar underlying equations to represent hydrologic and water quality processes. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

19.
A procedure for the dynamic identification of the physical parameters of coupled base isolation systems is developed in the time domain. The isolation systems considered include high damping rubber bearings (HDRB) and low friction sliding bearings (LFSB). A bi‐linear hysteretic model is used alone or in parallel with a viscous damper to describe the behavior of the HDRB system, while a constant Coulomb friction device is used to model the LFSB system. After deriving the analytical dynamical solution for the coupled system under an imposed initial displacement, this is used in combination with the least‐squares method and an iterative procedure to identify the physical parameters of a given base isolation system belonging to the class described by the models considered. Performance and limitations of the proposed procedure are highlighted by numerical applications. The procedure is then applied to a real base isolation system using data from static and dynamic tests performed on a building at Solarino. The results of the proposed identification procedure have been compared to available laboratory data and the agreement is within ±10%. However, the need for improvement both in models and testing procedures also emerges from the numerical applications and results obtained. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

20.
Watershed water quality models are increasingly used in management. However, simulations by such complex models often involve significant uncertainty, especially those for non-conventional pollutants which are often poorly monitored. This study first proposed an integrated framework for watershed water quality modeling. Within this framework, Probabilistic Collocation Method (PCM) was then applied to a WARMF model of diazinon pollution to assess the modeling uncertainty. Based on PCM, a global sensitivity analysis method named PCM-VD (VD stands for variance decomposition) was also developed, which quantifies variance contribution of all uncertain parameters. The study results validated the applicability of PCM and PCM-VD to the WARMF model. The PCM-based approach is much more efficient, regarding computational time, than conventional Monte Carlo methods. It has also been demonstrated that analysis using the PCM-based approach could provide insights into data collection, model structure improvement and management practices. It was concluded that the PCM-based approach could play an important role in watershed water quality modeling, as an alternative to conventional Monte Carlo methods to account for parametric uncertainty and uncertainty propagation.  相似文献   

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