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平原地下水水质评价方法探讨 总被引：6，自引：0，他引：6
本文从平原地下水水质评价标准的确定、评价指标的选择、单项和综合评价方法等方面建立了平原地下水水质评价的完整体系,它既考虑了地下水水体污染的随机性和模糊性,又能保证平原地下水水质评价结果的区域可比性,同时简便明了,适用于平原地下水资源评价面广点多的特点。 相似文献
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Bellie Sivakumar 《地球表面变化过程与地形》2007,32(7):969-979
Whether or not river flow exhibits nonlinear determinism remains an unresolved question. While studies on the use of nonlinear deterministic methods for modeling and prediction of river flow series are on the rise and the outcomes are encouraging, suspicions and criticisms of such studies continue to exist as well. An important reason for this situation is that the correlation dimension method, used as a nonlinear determinism identification tool in most of those studies, may possess certain limitations when applied to real river flow series, which are always finite and often short and also contaminated with noise (e.g. measurement error). In view of this, the present study addresses the issue of nonlinear determinism in river flow series using prediction as a possible indicator. This is done by (1) reviewing studies that have employed nonlinear deterministic methods (coupling phase‐space reconstruction and local approximation techniques) for river flow predictions and (2) identifying nonlinear determinism (or linear stochasticity) based on the level of prediction accuracy in general, and on the prediction accuracy against the phase‐space reconstruction parameters in particular (termed as the ‘inverse approach’). The results not only provide possible indications to the presence of nonlinear determinism in the river flow series studied, but also support, both qualitatively and quantitatively, the low correlation dimensions reported for such. Therefore, nonlinear deterministic methods are a viable complement to linear stochastic ones for studying river flow dynamics, if sufficient caution is exercised in their applications and in interpreting the outcomes. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
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This work examines the propagation of time harmonic, horizontally polarized shear waves through a naturally occurring heterogeneous medium that exhibits viscous behaviour as well as random fluctuations of its elastic modulus about a mean value. As a first step, the governing equation, which is a heterogeneous Helmholtz equation, is solved using algebraic transformations and the relevant Green's function is obtained for two sets of boundary conditions, one corresponding to a finite depth layer and the other to an infinite layer. Viscous material behaviour is introduced by considering the depth-dependent elastic modulus to be a complex quantity. Subsequently, material stochasticity in the medium is handled through the perturbation approach by assuming that the elastic modulus has a small random fluctuation about its mean value. The final results are closed-form expressions for the mean value and covariance matrix of both the wave speed profile in the medium and the corresponding Green's function. In Part II, (Soil Dynam. Earth. Engng, 1996,15, 129-39), two examples concerning seismic wave propagation in soft topsoil and in sandstone serve to illustrate the methodology and comparisons are made with Monte Carlo simulations. 相似文献
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Anastasios A. Tsonis 《水文科学杂志》2016,61(9):1591-1610
ABSTRACTThis article is a concept paper, which discusses the definition of randomness, and the sources of randomness in the mathematical system as well as in the physical system (the Universe). We document that randomness is an inherited property of mathematics and of the physical world, shaping all observed forms and structures, and we discuss its role.
Editor D. Koutsoyiannis; Guest editor E. Volpi 相似文献
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Abstract One of the world's largest irrigation networks, based on the Indus River system in Pakistan, faces serious scarcity of water in one season and disastrous floods in another. The system is dominated both by monsoon and by snow and glacier dynamics, which confer strong seasonal and inter-annual variability. In this paper two different forecasting methods are utilized to analyse the long-term seasonal behaviour of the Indus River. The study also assesses whether the strong seasonal behaviour is dominated by the presence of low-dimensional nonlinear dynamics, or whether the periodic behaviour is simply immersed in random fluctuations. Forecasts obtained by nonlinear prediction (NLP) and the seasonal autoregressive integrated moving average (SARIMA) methods show that the performance of NLP is relatively better than the SARIMA method. This, along with the low values of the correlation dimension, is indicative of low-dimensional nonlinear behaviour of the hydrological dynamics. A relatively better performance of NLP, using an inverse technique, may also be indicative of the low-dimensional behaviour. Moreover, the embedding dimension of the best NLP forecasts is in good agreement with the estimated correlation dimension. This provides evidence that the nonlinearity inherent in the monthly river flow due to the snowmelt and the monsoon variations dominate over the high-dimensional components and might be exploited for prediction and modelling of the complex hydrological system. Citation Hassan, S. A. & Ansari, M. R. K. (2010) Nonlinear analysis of seasonality and stochasticity of the Indus River. Hydrol. Sci. J. 55(2), 250–265. 相似文献
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Vadim V. Silberschmidt Vladimir G. Silberschmidt 《International Journal of Earth Sciences》1996,85(1):103-109
Development of defects in brittle rocks is analysed in terms of continuous damage mechanics with an emphasis on a shear damage evolution. Necessity to account for an effect of stochastic action leads to an introduction of kinetic relations for damage accumlation in a form of stochastic differential equations. Numerical algorithms for their solution for three types of noise are proposed. Results of simulation are compared with analytical solutions for a determiistic case (absence of stochastic action). Effect of various types of noise on damage accumulation and on time-to-fracture distributions is investigated. The study is limited to the case of temporal stochasticity; ways for unification of approach and schemes with spatial randomness are discussed. 相似文献
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Sinan Q. Salih Ahmad Sharafati Khabat Khosravi Hossam Faris Ozgur Kisi Hai Tao 《水文科学杂志》2020,65(4):624-637
ABSTRACTSuspended sediment load (SSL) is one of the essential hydrological processes that affects river engineering sustainability. Sediment has a major influence on the operation of dams and reservoir capacity. This investigation is aimed at exploring a new version of machine learning models (i.e. data mining), including M5P, attribute selected classifier (AS M5P), M5Rule (M5R), and K Star (KS) models for SSL prediction at the Trenton meteorological station on the Delaware River, USA. Different input scenarios were examined based on the river flow discharge and sediment load database. The performance of the applied data mining models was evaluated using various statistical metrics and graphical presentation. Among the applied data mining models, the M5P model gave a superior prediction result. The current and one-day lead time river flow and sediment load were the influential predictors for one-day-ahead SSL prediction. Overall, the applied data mining models achieved excellent predictions of the SSL process. 相似文献
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The interactions between the stream and the geomorphologic units that compose the stream channel result in an exchange of water, heat, and chemicals that is an important component of the flows of energy and nutrients in the river ecosystem. This exchange is characterized by complex spatial and temporal dynamics that depend on the characteristics of the stream flow and morphology. At present, many studies have addressed the development of spatial patterns of hyporheic exchange that are induced by many geomorphological factors at different scales. However, much less is known about the temporal evolution of the surface–subsurface exchange in response to the dynamics of the stream discharge. In order to investigate this problem, the present work analyzes the influence of streamflow variability on the hyporheic exchange induced by fluvial bedforms. A stochastic approach is employed to generate streamflow series whose statistical properties are representative of streams with different hydrological regimes. The resulting exchange fluxes and travel times are then computed, and the relationships between the streamflow regime and the dynamics of the exchange flux and travel times are investigated. The results show that the mean stream discharge can be used to estimate the average features of the temporal dynamics of hyporheic exchange. Moreover, exchange fluxes and residence times distributions exhibit significant fluctuations, which are tightly related to the coefficient of variation of the streamflow hydrograph. 相似文献
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Recruitment in randomly varying environments 总被引：1，自引：0，他引：1
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