Data area hydrological parameter calibration method based on adversarial neural network

Abstract

The invention discloses a data area hydrological parameter calibration method based on an adversarial neural network. The method comprises the following steps: collecting soil texture, vegetation coverage, land utilization rate, topographic data, runoff coefficient, annual total evaporation amount, gradient and gradient data; dividing the calibration region into calculation units within 30 squarekilometers or less; determining the underlying surface and meteorological correlation factors of each parameter of each calculation unit; adopting an adversarial neural network GAN to automatically calibrate the hydrological parameters of the watershed with the data to obtain the optimal hydrological parameters of each unit; training a unified parameter generator based on an adversarial neural network (GAN) by adopting the optimal hydrological parameters of all computing units in the area with data; determining hydrological parameters of the data-free region through the trained parameter generator. The technical problems that in the prior art, work repeatability and efficiency are low, complexity is extremely high, and application and popularization of a hydrological model are not utilizedare solved.

Description

technical field [0001] The invention belongs to hydrological parameter calibration technology, in particular to a method for calibrating hydrological parameters in areas with data based on an adversarial neural network. Background technique [0002] Hydrological models play an important role in the study of hydrological laws and solving practical production problems. With the rapid development of modern science and technology, information technology with computers and communications as the core is widely used in the fields of hydrology, water resources and hydraulic engineering. The study of hydrological models has been developed rapidly and widely used in the study of basic laws of hydrology, flood and drought disaster prevention, water resource evaluation and development and utilization, water environment and ecosystem protection, climate change and analysis of the impact of human activities on water resources and water environment and other fields. Therefore, it is of gr...

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Problems solved by technology

[0014] The technical problem to be solved by the present invention is to provide a method for calibrating hydrological parameters in areas with data based on an adversarial neural network to solve the problem that the prior art adopts the traditional trial-and-error method for determining the parameters of a watershed hydrological model without data, that is, by Manually adjust the parameter values ​​of the hydrological model to meet the simulation accuracy requirements. This method has problems such as low calibration accuracy and seriously affecting the accuracy of hydrological forecasting.

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