共查询到20条相似文献，搜索用时 31 毫秒
1.
A reliable computational model is necessary for evaluating the state and predicting the future performance of existing structures, especially after exposure to damaging effects such as an earthquake. A major problem with the existing iterative‐based model updating methods is that the search might be trapped in local optima. The genetic algorithms (GAs) offer a desirable alternative because of their ability in performing a robust search for the global optimal solution. This paper presents a GA‐based model updating approach using a real‐coding scheme for global model updating based on dynamic measurement data. An eigensensitivity method is employed to further fine‐tune the GA updated results in case the sensitivity problem arises due to restricted measurement information. The application on shear‐type frames reveals that with a limited amount of modal data, namely the lowest three natural frequencies and the first mode shape, it is possible to achieve satisfactory updating by the GA alone for cases involving a limited number of parameters (storey stiffness herein). With the incorporation of the eigensensitivity algorithm, the updating capability is extended to a sufficiently large number of parameters. In case the modal data contain errors, the GA is also shown to be able to update the model to a satisfactory accuracy, provided the required amount of modal data is available. An example is given in which a 6‐DOF stick model for an actual six‐storey RC frame is updated using the measured dynamic properties. The effectiveness of the updating is evaluated by comparing the measured and predicted seismic response using the updated model. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
2.
AbstractSpatial error regression is employed to regionalize the parameters of a rainfall–runoff model. The approach combines regression on physiographic watershed characteristics with a spatial proximity technique that describes the spatial dependence of model parameters. The methodology is tested for the monthly abcd model at a network of gauges in southeast United States and compared against simpler regression and spatial proximity approaches. Unlike other comparative regionalization studies that only evaluate the skill of regionalized streamflow predictions in ungauged catchments, this study also examines the fit between regionalized parameters and their optimal (i.e. calibrated) values. Interestingly, the spatial error model produces parameter estimates that better resemble the optimal parameters than either of the simpler methods, but the spatial proximity method still yields better hydrologic simulations. The analysis suggests that the superior streamflow predictions of spatial proximity result from its ability to better preserve correlations between compensatory hydrological parameters.
Editor D. Koutsoyiannis; Associate editor Y. Gyasi-Agyei 相似文献
3.
Abstract This paper describes a fuzzy rule-based approach applied for reconstruction of missing precipitation events. The working rules are formulated from a set of past observations using an adaptive algorithm. A case study is carried out using the data from three precipitation stations in northern Italy. The study evaluates the performance of this approach compared with an artificial neural network and a traditional statistical approach. The results indicate that, within the parameter sub-space where its rules are trained, the fuzzy rule-based model provided solutions with low mean square error between observations and predictions. The problems that have yet to be addressed are overfitting and applicability outside the range of training data. 相似文献
4.
ABSTRACTSrinivasan et al. provide an interesting overview of the challenges for long-term socio-hydrological predictions. Although agreeing with most of the statements made, we argue for the need to take socio-hydrological analysis a step further and add some fundamental considerations, especially concerning the crucial importance of many (conscious and unconscious) assumptions made upfront of the modelling exercise. Eventual assumptions of technological determinism need correction: Models are not “value-free”, but uncertain, subjective and a product of the society in which they were shaped. It is important to acknowledge this uncertainty and bias when making decisions based on socio-hydrological models, considering also that these models are “social and political actors” in and by themselves. Furthermore, socio-hydrological models require a transdisciplinary approach, since physical water availability is only one of the boundary conditions for society. Last but not least, interaction with stakeholders remains important to enable understanding of what the variable of interest is. 相似文献
5.
Abstract Intensity–Duration–Frequency (IDF) curves for precipitation constitute a probabilistic tool and have proven useful in water resources management. In particular, IDF curves for precipitation enable questions on the extreme character of precipitation to be answered. The construction of IDF curves for precipitation is difficult or impossible in tropical areas due to the lack of long-term extreme precipitation data. A technique is proposed to overcome this shortcoming by combining limited high-frequency information on rainfall extremes with long-term daily rainfall information. It may be regarded as an extension of Koutsoyiannis' approach. Using this technique, IDF curves for precipitation are produced for Lubumbashi in Congo. Citation Van de Vyver, H. & Demarée, G. R. (2010) Construction of Intensity–Duration–Frequency (IDF) curves for precipitation at Lubumbashi, Congo, under the hypothesis of inadequate data. Hydrol. Sci. J. 55(4), 555–564. 相似文献
6.
ABSTRACTThroughout the last decade copula functions were widely used to assess a wide range of hydrological problems, often focusing on two distinct variables. In many of these studies it was ignored whether the two variables of interest actually occurred simultaneously (e.g. two annual maximum time series were analysed in a multivariate statistical framework). Here we introduce a novel approach to derive bivariate design events using copula functions allowing both simultaneous and non-simultaneous occurrence of the variables to be modelled. The methodology is exemplarily applied to assess the combined flood occurrence at the confluence of the rivers Rhine and Sieg (Germany). The results underline the validity of the methodology. Employing a hydrodynamic numerical model furthermore shows that commonly used statistical approaches to select a single design event out of a vast number of possible combinations can be critical for practical design purposes.
Editor Z.W. Kundzewicz; Associate editor S. Grimaldi 相似文献
7.
Abstract Rainfall-runoff models are used to describe the hydrological behaviour of a river catchment. Many different models exist to simulate the physical processes of the relationship between precipitation and runoff. Some of them are based on simple and easy-to-handle concepts, others on highly sophisticated physical and mathematical approaches that require extreme effort in data input and handling. Recently, mathematical methods using linguistic variables, rather than conventional numerical variables applied extensively in other disciplines, are encroaching in hydrological studies. Among these is the application of a fuzzy rule-based modelling. In this paper an attempt was made to develop fuzzy rule-based routines to simulate the different processes involved in the generation of runoff from precipitation. These routines were implemented within a conceptual, modular, and semi-distributed model-the HBV model. The investigation involved determining which modules of this model could be replaced by the new approach and the necessary input data were identified. A fuzzy rule-based routine was then developed for each of the modules selected, and application and validation of the model was done on a rainfall-runoff analysis of the Neckar River catchment, in southwest Germany. 相似文献
8.
Christopher J. Hutton 《地球表面变化过程与地形》2014,39(11):1559-1562
The pervasive application of the Null Hypothesis Significance Test in geomorphic research runs counter to widespread, long running, and often severe criticism of the method in the broader scientific literature. The application of the methodology typically leads to a binary separation of evidence into ‘significant’ and ‘not significant’ results based on a p‐value that is dependent on the null hypothesis being true. The method should not therefore be used to provide statistical support for substantive hypotheses, and is unsuitable for scientific inference in open systems where confirmation can only ever be partial. Alternative approaches based on Bayesian statistics can importantly be applied to measure partial support for hypotheses, conditional on the available data. Though not without their own assumptions, wider application of such methods can help facilitate a transition towards a broader approach to statistical, and in turn, scientific inference in geomorphic systems. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
9.
Abstract To investigate the consequences of climate change on the water budget in small catchments, it is necessary to know the change of local precipitation and temperature. General Circulation Models (GCM) cannot provide regional climate parameters yet, because of their coarse resolution and imprecise modelling of precipitation. Therefore downscaling of precipitation and temperature has to be carried out from the GCM grids to a small scale of a few square kilometres. Daily rainfall and temperature are modelled as processes conditioned on atmospheric circulation. Rainfall is linked to the circulation patterns (CPs) using conditional probabilities and conditional rainfall amount distribution. Both temperature and precipitation are downscaled to several locations simultaneously taking into account the CP dependent spatial correlation. Temperature is modelled using a simple autoregressive approach, conditioned on atmospheric circulation and local areal precipitation. The model uses the classification scheme of the German Weather Service and a fuzzy rule-based classification. It was applied in the Aller catchment for validation using observed rainfall and temperature, and observed classified geopotential pressure heights. GCM scenarios of the ECHAM model were used to make climate change predictions (using classified GCM geopotential heights); simulated values agree fairly well with historical data. Results for different GCM scenarios are shown. 相似文献
10.
Abdüsselam Altunkaynak 《水文研究》2010,24(17):2400-2404
Simple methods for calculating well losses are important for well design and optimization of groundwater source operation. Well losses arise from both laminar flow within the aquifer and turbulent flow within the well, and are often ignored in theoretical aquifer test analysis. The Jacob ( 1947 ) and Rorabaugh ( 1953 ) techniques for predicting well losses are widely used in the literature; however, inherent in these techniques are the assumptions of linearity, normality and homoscedascity. In the Rorabaugh technique, prior knowledge, or prediction of, the parameters A, C and n is required for calculation of well losses. Unfortunately, as of yet, no method for adequately obtaining these parameters without experimental data and linear regression exist. For these reasons, the Rorabaugh methodology has some practical and realistic limitations. In this paper, a fuzzy logic approach is employed in the calculation of well losses. An advantage of the fuzzy logic approach is that it does not make any assumptions about the form of the well loss functionality and does not require initial estimates for the calculation of well losses. Results show that the fuzzy model is a practical alternative to the Rorabaugh technique, producing lower errors (mean absolute error, mean square error and root mean square error) relative to observed data, for the case presented, comparatively to the Rorabaugh model. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
11.
The primary objective of this study is to propose a real‐coded hypercubic distributed genetic algorithm (HDGA) for optimizing reservoir operation system. A conventional genetic algorithm (GA) is often trapped into local optimums during the optimization procedure. To prevent premature convergence and to obtain near‐global optimal solutions, the HDGA is designed to have various subpopulations that are processed using separate and parallel GAs. The hypercubic topology with a small diameter spreads good solutions rapidly throughout all of the subpopulations, and a migration mechanism, which exchanges chromosomes among the subpopulations, exchanges information during the joint optimization to maintain diversity and thus avoid a systematic premature convergence toward a single local optimum. Three genetic operators, i.e. linear ranking selection, blend‐α crossover and Gaussian mutation, are applied to search for the optimal reservoir releases. First, a benchmark problem, the four‐reservoir operation system, is considered to investigate the applicability and effectiveness of the proposed approach. The results show that the known global optimal solution can be effectively and stably achieved by the HDGA. The HDGA is then applied in the planning of a multi‐reservoir system in northern Taiwan, considering a water reservoir development scenario to the year 2021. The results searched by an HDGA minimize the water deficit of this reservoir system and provide much better performance than the conventional GA in terms of obtaining lower values of the objective function and avoiding local optimal solutions. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
12.
Generating surfaces of daily meteorological variables over large regions of complex terrain 总被引：57，自引：0，他引：57
A method for generating daily surfaces of temperature, precipitation, humidity, and radiation over large regions of complex terrain is presented. Required inputs include digital elevation data and observations of maximum temperature, minimum temperature and precipitation from ground-based meteorological stations. Our method is based on the spatial convolution of a truncated Gaussian weighting filter with the set of station locations. Sensitivity to the typical heterogeneous distribution of stations in complex terrain is accomplished with an iterative station density algorithm. Spatially and temporally explicit empirical analyses of the relationships of temperature and precipitation to elevation were performed, and the characteristic spatial and temporal scales of these relationships were explored. A daily precipitation occurrence algorithm is introduced, as a precursor to the prediction of daily precipitation amount. Surfaces of humidity (vapor pressure deficit) are generated as a function of the predicted daily minimum temperature and the predicted daily average daylight temperature. Daily surfaces of incident solar radiation are generated as a function of Sun-slope geometry and interpolated diurnal temperature range. The application of these methods is demonstrated over an area of approximately 400 000 detailed illustration of the parameterization process. A cross-validation analysis was performed, comparing predicted and observed daily and annual average values. Mean absolute errors (MAE) for predicted annual average maximum and minimum temperature were 0.7°C and 1.2°C, with biases of +0.1°C and −0.1°C, respectively. MAE for predicted annual total precipitation was 13.4 cm, or, expressed as a percentage of the observed annual totals, 19.3%. The success rate for predictions of daily precipitation occurrence was 83.3%. Particular attention was given to the predicted and observed relationships between precipitation frequency and intensity, and they were shown to be similar. We tested the sensitivity of these methods to prediction grid-point spacing, and found that areal averages were unchanged for grids ranging in spacing from 500 m to 32 km. We tested the dependence of the results on timestep, and found that the temperature prediction algorithms scale perfectly in this respect. Temporal scaling of precipitation predictions was complicated by the daily occurrence predictions, but very nearly the same predictions were obtained at daily and annual timesteps. 相似文献
13.
S. K. JAIN 《水文科学杂志》2013,58(5):431-441
Abstract Conceptual mathematical models are a useful tool for rainfallrunoff modelling of a basin. The calibration of such models has attracted the attention of a number of hydrologists since unique and optimal parameters are difficult to obtain. The calibration of a conceptual model is discussed through a simple conceptual model whose parameters are determined using a search technique. It is shown that the optimization algorithm converges to a global optimum even when the errors in the initial parameters are quite significant and the input environment is noisy. 相似文献
14.
ABSTRACTBias correction is a necessary post-processing procedure in order to use regional climate model (RCM)-simulated local climate variables as the input data for hydrological models due to systematic errors of RCMs. Most of the present bias-correction methods adjust statistical properties between observed and simulated data based on a predefined duration (e.g. a month or a season). However, there is a lack of analysis of the optimal period for bias correction. This study attempted to address the question whether there is an optimal number for bias-correction groups (i.e. optimal bias-correction period). To explore this we used a catchment in southwest England with the regional climate model HadRM3 precipitation data. The proposed methodology used only one grid of RCM in the Exe catchment, one emissions scenario (A1B) and one member (Q0) among 11 members of HadRM3. We tried 13 different bias-correction periods from 3-day to 360-day (i.e. the whole of one year) correction using the quantile mapping method. After the bias correction a low pass filter was used to remove the high frequencies (i.e. noise) followed by estimating Akaike’s information criterion. For the case study catchment with the regional climate model HadRM3 precipitation, the results showed that a bias-correction period of about 8 days is the best. We hope this preliminary study on the optimum number bias-correction period for daily RCM precipitation will stimulate more research to improve the methodology with different climatic conditions. Future efforts on several unsolved problems have been suggested, such as how strong the filter should be and the impact of the number of bias correction groups on river flow simulations.
Editor M.C. Acreman Associate editor S. Kanae 相似文献
15.
Growing human pressure and potential change in precipitation pattern induced by climate change require a more efficient and sustainable use of water resources. Hydrological models can provide a fundamental contribution to this purpose, especially as increasing availability of meteorological data and forecast allows for more accurate runoff predictions. In this article, two models are presented for describing the flow formation process in a sub‐alpine catchment: a distributed parameter, physically based model, and a lumped parameter, empirical model. The scope is to compare the two modelling approaches and to assess the impact of hydrometeorological information, either observations or forecast, on water resources management. This is carried out by simulating the real‐time management of the regulated lake that drains the catchment, using the inflow predictions provided by the two models. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
16.
《水文科学杂志》2013,58(6)
Abstract Determining the precipitation phase—rain or snow—is an important factor in modelling discharge in mountainous basins. In a study carried out in the outer tropical Andes Cordillera of Bolivia, half-hourly determination of precipitation phase was obtained by applying a suitable expert system, taking 11 meteorological parameters into consideration that are measured over 21 months at an altitude close to 4800 m. Straightforward relationships between the determined precipitation phase and observed air temperature were analysed in histograms that contain percentage occurrences of snowfall, rainfall and mixed precipitation events for 0.5°C air temperature increments. The graph shows a nearly identical distribution of percentage occurrences of snowfall in the Andes to that on a 1600-m high site in the Swiss Alps. This result suggests that, for hydrological modelling purposes in the outer tropical Andes, the same rain/snow threshold temperature as in the compared Swiss site can be applied. 相似文献
17.
基于NCEP/NCAR提供的1958～1995年全球月平均海温距平场再分析资料,采用动力系统反演思想和遗传算法途径,进行了El Nino/La Nina指数的动力预报模型的参数优化和模型反演,从上述海温资料中重构了Nino3海温距平指数的非线性动力模型.模型预报试验结果表明,遗传算法具有的全局搜索和并行计算优势能够客观、有效地反演海温指数的动力预报模型,对Nino3海温指数和El Nino/La Nina事件进行较为客观准确的预测,为El Nino/La Nina预测提供有益的研究参考. 相似文献
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19.
By identifying changes in stiffness parameters, structural damage can be detected and monitored. Although considerable progress has been made in this research area, many challenges remain in achieving robust structural identification based on incomplete and noisy measurement signals. The identification task is made even more difficult if measurement of input force is to be eliminated. To this end, an output‐only structural identification strategy is proposed to identify unknown stiffness and damping parameters. A non‐classical approach based on genetic algorithms (GAs) is adopted. The proposed strategy makes use of the recently developed GA‐based method of search space reduction, which has shown to be able to accurately and reliably identify structural parameters from measured input and output signals. By modifying the numerical integration scheme, input can be computed as the parameter identification task is in progress, thereby eliminating the need to measure forces. Numerical and experimental results demonstrate the power of the strategy in accurate and efficient identification of structural parameters and damage using only incomplete acceleration measurements. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
20.
A combined simulation–genetic algorithm (GA) optimization model is developed to determine optimal reservoir operational rule curves of the Nam Oon Reservoir and Irrigation Project in Thailand. The GA and simulation models operate in parallel over time with interactions through their solution procedure. A GA is selected as an optimization model, instead of traditional techniques, owing to its powerful and robust performance and simplicity in combining with a simulation technique. A GA is different from conventional optimization techniques in the way that it uses objective function information and does not require its derivatives, whereas in real‐world optimization problems the search space may include discontinuities and may often include a number of sub‐optimum peaks. This may cause difficulties for calculus‐based and enumerative schemes, but not in a GA. The simulation model is run to determine the net system benefit associated with state and control variables. The combined simulation–GA model is applied to determine the optimal upper and lower rule curves on a monthly basis for the Nam Oon Reservoir, Thailand. The objective function is maximum net system benefit subject to given constraints for three scenarios of cultivated areas. The monthly release is calculated by the simulation model in accordance with the given release policy, which depends on water demand. The optimal upper and lower rule curves are compared with the results of the HEC‐3 model (Reservoir System Analysis for Conservation model) calculated by the Royal Irrigation Department, Thailand, and those obtained using the standard operating policy. It was found that the optimal rule curves yield the maximum benefit and minimum damages caused by floods and water shortages. The combined simulation–GA model shows an excellent performance in terms of its optimization results and efficient computation. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献