Method for forecasting monthly runoff through secondary coupling under condition of data shortage

A runoff and data technology, applied in the field of secondary coupled monthly runoff forecasting, can solve problems such as inability to effectively predict basin hydrological data

Inactive Publication Date: 2014-02-12
HOHAI UNIV
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[0007] Purpose of the invention: The present invention provides a method for forecasting secondary coupling monthly runoff in the case of data sh

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  • Method for forecasting monthly runoff through secondary coupling under condition of data shortage
  • Method for forecasting monthly runoff through secondary coupling under condition of data shortage
  • Method for forecasting monthly runoff through secondary coupling under condition of data shortage

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Embodiment

[0040] The Heihe River Basin is the second largest inland watershed in Northwest my country, located in the middle of the Hexi Corridor, roughly between 98°-101°30′E, 38°-42°N. The Heihe River is 821 kilometers long from its source to Juyan Sea, spanning three different natural environment units, with a drainage area of ​​about 142,900 square kilometers. The upper reaches of the Heigan River above Yingluo Gorge are 313 km long and the drainage area is 10,000 km 2 , is the main flow-producing area of ​​the Heihe River, with an annual average temperature of 1.5-2°C, an annual precipitation of more than 200 mm, with a maximum of 700 mm, a relative humidity of about 60%, and an evaporation of about 700 mm. It is a transition zone from agriculture to animal husbandry. The middle reaches from Yingluo Gorge to Zhengyi Gorge, the river course is 183km long and the drainage area is 23,400km 2 , the area is rich in light and heat resources, but it is severely arid, relying on the Heihe...

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Abstract

The invention discloses a method for forecasting monthly runoff through secondary coupling under the condition of data shortage. The number of structure parameters of a coupling model is small, the structure of the coupling model is simple, the computational process is not limited by the requirement for the accuracy of calculated length, topographic data and meteorological data of hydrologic data, the realness of a model system in simulating a real hydrologic process is guaranteed by carrying out model coupling on a GRNN model and other physical models, and errors caused by the adoption of a large number of empirical formulas and setup parameters are effectively avoided; a traditional time series ARMA model is modified, and a seasonal ARMA model is applied to an extension technology for hydrologic data series; data coupling is carried out on the coupling model and monthly runoff data extended through the seasonal ARMA model to determine the structure and the parameters of the coupling model so that a coupled GRNN model acquired after secondary coupling can still guarantee the accuracy in simulating the runoff of a drainage basin of which hydrologic data are relatively insufficient, and therefore the method has low dependency on the historical hydrologic data and can effectively guarantee the practicality and applicability of the coupling model system.

Description

technical field [0001] The invention belongs to the field of multiple coupling design methods for hydrological forecasting, and in particular relates to a secondary coupling monthly runoff forecasting method under the condition of data shortage. Background technique [0002] Hydrological forecasting is an important part of hydrology. It is a hydrological discipline based on the objective description of actual hydrological phenomena and using the measured data of hydrology and meteorology to predict the future changes of hydrological factors. Forecasting the inflow of water in the basin is a necessary work before the rational allocation of water resources in the basin and reservoirs. Reliable monthly runoff forecasting is particularly important for multi-functional scheduling of reservoirs. [0003] In the hydrological runoff forecasting model, according to different modeling methods, it can be divided into conceptual model, distributed model and black box model. The first t...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/02
CPCY02A90/10
Inventor 尹笋唐德善陈伟伟陆姗姗丁亿凡
Owner HOHAI UNIV
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