Drainage basin hydrological model parameter dynamic estimation method based on digital twinborn technology

Abstract

The invention discloses a watershed hydrological model parameter dynamic estimation method based on a digital twinborn technology. Constructing digital twin bodies of the watershed based on the physical characteristic data of the watershed and observation data such as historical hydro meteorology; sensors are arranged in the drainage basin to achieve real-time monitoring of multiple feature elements of the drainage basin, and real-time tracking and information synchronization of digital twins of the drainage basin are achieved; according to historical and real-time synchronous drainage basin digital twins, state variables and parameters in the simulation model are estimated in a mode of synchronously combining a data assimilation method and an optimization algorithm, and finally dynamic estimation of parameters of the drainage basin hydrological model is achieved. According to the method, the real-time monitoring data of the drainage basin can be fully utilized, the dynamic change presented by the characteristic conditions of the drainage basin under the changing environment background can be accurately reflected, the targets of intelligent management, analogue simulation, automatic optimization, real-time updating and reasonable prediction are achieved, and the runoff simulation precision of the drainage basin under the changing environment can be improved.

Description

technical field [0001] The invention belongs to the field of watershed hydrological models, in particular to a method for dynamically estimating parameters of watershed hydrological models based on digital twin technology. Background technique [0002] Watershed hydrological model is an important tool for studying natural laws of hydrology and solving practical hydrological problems. Accurate estimation of its parameters plays a vital role in simulating and forecasting watershed runoff. The current watershed hydrological model parameter estimation method is generally calibrated based on the hydrological measured data in the historical period using an optimization algorithm. The assumption is that the model parameters are constant in the watershed, that is, the parameters calibrated based on the hydrological data in the historical period can be directly used Watershed runoff forecasts for present and future periods. The main implementation steps of the current method are: (1...

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Problems solved by technology

[0003] Therefore, there are problems in the existing hydrological model parameter estimation methods: (1) only use historical period data for hydrological model parameter calibration, and cannot make full use of real-time monitoring data to further reduce the uncertainty of parameter estimation; (2) cannot accurately (3) The goals of intelligent management, sensory analysis, simulation, automatic optimization, real-time update and reasonable prediction cannot be achieved

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