Small watershed flood forecasting and early warning method and terminal

Abstract

The invention discloses a small watershed flood forecasting and early warning method and a terminal, and the method comprises the steps: obtaining historical hydrological data and watershed basic data, building a hydrological-hydrodynamic coupling initial model based on MIKE series software and the watershed basic data, and calibrating the hydrological-hydrodynamic coupling initial model through the historical hydrological data, obtaining a calibrated hydrological-hydrodynamic coupling model; acquiring grid weather forecast data and evaporation capacity data in a research basin and preheating period rainfall data of each rainfall station, obtaining forecast period rainfall data according to the grid weather forecast data, and importing the preheating period rainfall data, the evaporation capacity data and the forecast period rainfall data into a hydrological-hydrodynamic coupling model, and generating and displaying flood forecasting and early warning information. According to the method, real-time, convenient, accurate and high-forecast-period small watershed flood forecasting and early warning can be realized.

Description

technical field [0001] The invention relates to the technical field of non-engineering measures for natural disaster defense, in particular to a small watershed flood forecasting and early warning method and terminal. Background technique [0002] Flood forecasting is based on the objective law of flood formation, using historical, real-time, or future hydrological and meteorological data, to predict the changes of flood elements in a control section for a period of time in the future (called the forecast period). The predicted flood elements include water level Or flow hydrograph, peak flow or water level, peak time, etc. Flood forecasting is one of the most important non-engineering measures in the flood control system. It can provide important technical means for flood control decision-making and command, and provide strong support for mountain torrent forecast analysis and flood disaster assessment. [0003] After decades of development, the application of flood forecas...

AI Technical Summary

Problems solved by technology

The traditional lumped hydrological model simulates the runoff production and confluence of the watershed as a whole, and can only predict the process of flooding at the outlet section of the watershed, without considering the underlying surface of the watershed, the heterogeneity of rainfall distribution, and the hydrodynamic laws of the river network. For disaster prevention and mitigation in small watersheds, we should not only pay attention to the flood process at the outlet section, but also know the changes of hydrological elements in the river channel control section and the dynamic evolution of flood in the river basin, so as to judge the flood risk of villages along the river

Moreover, the model only reflects the appearance of flow generation and confluence in the watershed without a clear description of its physical mechanism. Most of the parameters of the model lack clear physical meaning and cannot describe the internal mechanism of natural phenomena, which limits its application range.

[0005] Representative distributed hydrological models mainly include: HEC-HMS model, SHE model funded by the European Community in 1986, SHETRAN model, TOPKAPI, etc. Although the distributed hydrological model takes into account the spatial variability of watershed characteristics and has physical meaning, but in the actual application process, the distributed hydrological model has strict requirements on hydrology, topography, landform and other data, and involves a large number of differential equations to solve, the model is complex and the calculation efficiency is low

For small watersheds, the distributed hydrological model has a complex structure and many parameters, and needs to rely on a large amount of historical data. However, most small watersheds in China generally lack monitoring stations, which limits the application of this method in watersheds that lack historical data.

[0006] That is to say, in view of the characteristics of small watersheds such as heavy rainfall, strong spatial heterogeneity of the underlying surface, short flow generation and confluence time, strong suddenness, strong destructive power, and lack of hydrological data, the above-mentioned flood forecasting methods are not practical due to various limitations. Very suitable for fine simulation of flood forecasting in small watersheds

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