Scenario-driven free-formation strategy for hydrological models

Abstract

The invention discloses a scenario-driven hydrological model free building strategy method, the steps are: 1) forming the layer data, topological structure and rainfall evaporation data of the target watershed; 2) determining the runoff model and slope confluence of the target watershed 3) Flood extraction; 4) Parameter calibration; 5) Verification; 6) Runoff calculation, slope confluence calculation, and river confluence calculation in sequence until the calculation reaches the target section, and the flow process of the target basin is obtained. The invention solves the problem of singleness of the generation and confluence models on each calculation unit in the traditional model modeling mode, and integrates the geospatial data processing software, model software, and model parameter calibration tools needed to build the hydrological model, and performs the production and confluence of each calculation unit Free collocation and combination of models, users can choose according to the actual needs of simulation, and improve modeling efficiency.

Description

technical field [0001] The invention relates to the technical field of water conservancy information, in particular to a strategy and method for free formation of a situation-driven hydrological model. Background technique [0002] The watershed hydrological model is the product of the combination of hydrological science and computer science, and is a vigorous research field in the hydrological science created by the information revolution. For more than half a century, there have been a large number of hydrological models describing the water cycle process in the basin. At present, there are at least 70 basin hydrological models with certain use value in the world, and they have been used more and more widely. Analytical simulations also play an increasingly important role. In flood control and disaster mitigation, the basin hydrological model is the core of real-time flood forecasting, and is a key technology to improve the flood forecasting accuracy and growth forecast p...

AI Technical Summary

Problems solved by technology

[0005] 1) When selecting a flow generation and confluence model, because the existing hydrological models often exist in a single way, they cannot meet the hydrological calculation requirements under different climates and underlying surface conditions at the same time;

[0006] 2) In the process of model building, since the process involves data transfer and processing between multiple software (such as ArcGIS, Excel, etc.) Restricted by external tool factors, the versatility of the model and the correctness of the data cannot be effectively guaranteed;

[0007] 3) In the process of model building, the flow generation and confluence models on each calculation unit of the same watershed can only be set uniformly, and it is difficult for users to freely match and combine the flow generation and confluence models of each calculation unit according to the actual needs of the simulation;

[0008] 4) There are many intermediate steps in the model building process, and the steps of different models are different. The lack of mature and perfect intelligent guidance technology solutions may easily affect the rationality and accuracy of model building

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