Monthly runoff simulation method based on D-vine copula function

A simulation method and function fitting technology, applied in the field of monthly runoff simulation, to achieve the effect of overcoming linearity and steady state, and accurate and reliable simulation results

Active Publication Date: 2018-11-27
HOHAI UNIV
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Problems solved by technology

However, most of the existing research is limited to two-dimensional copulas, and there are few studies on multivariate copulas with more flexible structures and more powerful functions.

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  • Monthly runoff simulation method based on D-vine copula function
  • Monthly runoff simulation method based on D-vine copula function
  • Monthly runoff simulation method based on D-vine copula function

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Embodiment Construction

[0053]The technical solutions of the present invention will be described in detail below, but the protection scope of the present invention is not limited to the embodiments.

[0054] A monthly runoff simulation method, such as figure 1 As shown, in this case, the monthly runoff at the Tangnaihai Station on the main stream of the Yellow River is selected for time series simulation. The Yellow River Basin Map and the geographic information of the station are figure 2 As shown, using the restored monthly runoff data of the station from 1956 to 2010:

[0055] (1) Construct a fitting model for the marginal distribution of monthly runoff

[0056] According to the distribution characteristics of monthly runoff historical data in Tang Naihai, the distribution of Weibull function, lognormal function and gamma function were selected as alternative functions, and the function fitting was performed on each monthly runoff sequence respectively, and the cumulative distribution function g...

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Abstract

The invention provides a monthly runoff simulation method based on a D-vine copula function. The method includes: adopting a graphical method to construct a monthly runoff density distribution function fitting model; using a mixed D-vine copula function to construct a monthly runoff dependent structure simulation model of each month; adopting the Kendall coefficient based correlation test method to determine the mixed D-vine copula dimension of each monthly runoff; using the order method based on the maximum likelihood method and the AIC method to derive D-vine copula parameters; and using a conditional function to construct a monthly runoff stimulation model based on a conditional mixed D-vine copula joint distribution function. The invention constructs the monthly runoff simulation modelbased on the mixed D-vine copula. The model constructs the relevant structure of each month according to Kendall's tau values; if the confidence value is more than 95%, correlation is determined; andthe mixed D-vine copula is used to calculate the relevant structure to overcome the problem of the linearity and a steady state of the conventional models, and the simulation result is more accurateand reliable.

Description

technical field [0001] The invention relates to a runoff time series simulation method, in particular to a monthly runoff simulation method. Background technique [0002] The simulation of runoff time series is the basis for the formulation of water resources management plans. It not only reflects some internal laws of the hydrological system, but also can be used for flood and drought analysis, hydrology and water resources simulation, etc., which is crucial to the formulation of water resources management plans. Support work. At the same time, as the input data of the water resources system, especially as the inflow data of the reservoir group, the randomness of the runoff simulation is also the main source of the risk of the water resources system. More accurate runoff simulation and prediction have great practical significance for the planning and management of water resources, especially for the joint operation of reservoir groups. [0003] The key to time series simu...

Claims

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Application Information

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IPC IPC(8): G06Q10/04
CPCG06Q10/04
Inventor 董增川王文卓胡启玲
Owner HOHAI UNIV
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