Rainfall-runoff simulation method based on random forest algorithm
A technology of random forest algorithm and random forest model, which is applied in the field of small watershed runoff simulation research, can solve the problem of lack of historical rainfall runoff process data in small watersheds, and achieve the effect of improving simulation accuracy
Pending Publication Date: 2020-06-16
TAIYUAN UNIV OF TECH
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The rainfall-runoff model has achieved good results in the application of runoff simulation, but the lack of historical rainfall-runoff process data in small watersheds limits the models and methods used in runoff simulation research, and the data-driven rainfall-runoff model is simple and efficient , the characteristics of low data requirements have been widely used. At the same time, with the rise of the field of machine learning, the combination of machine learning algorithms and runoff simulation has gradually become a research hotspot.
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[0034] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.
[0035] Such as figure 1 As shown, the present invention is based on the rainfall-runoff simulation method flow process of the random forest algorithm and is introduced as follows:
[0036] The method is divided into three main parts: (1) Obtain the rainfall-runoff observation data of each event, and analyze and sort out a regionally representative M-dimensional rainfall feature set D. The M-dimensional rainfall features include rainfall amount, rainfall duration, and average rainfall Intensity, 30-minute rainfall intensity, and early impact rainfall that characterize the soil moisture in the watershed, etc.; (2) Use gray correlation analysis to extract dominant rainfall features from the rainfall features, and construct a rainfall attribute set D' composed of N-dimensional dominant rainfall features , D′∈D, N≤M; (3) Build a random forest model...
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The invention discloses a rainfall-runoff simulation method based on a random forest algorithm. The method mainly comprises steps that a random forest algorithm is used for carrying out runoff simulation on session rainfall with different rainfall characteristics, a rainfall-runoff model integrating the rainfall characteristics is provided in combination with the random forest algorithm, the characteristics of the session rainfall are used as model input by means of a machine learning algorithm, the runoff volume is used as model output, and therefore the runoff simulation process is achieved.Parameter calibration work of a traditional rainfall-runoff model is avoided, the calculation process is simple, a good simulation effect can be obtained, meanwhile, the method can be used for runoffsimulation research work of different areas, and a new method is provided for runoff simulation.
Description
technical field [0001] The invention relates to the research field of runoff simulation in small watersheds, in particular to a rainfall-runoff simulation method based on a random forest algorithm. Background technique [0002] At present, the development of runoff simulation methods has become increasingly mature, and the selection of hydrological models for runoff simulation is the main research direction in the field of hydrology. Rainfall is an important hydrometeorological element, and runoff, soil moisture content and other hydrological processes are all affected by rainfall. The rainfall-runoff model has achieved good results in the application of runoff simulation, but the lack of historical rainfall and runoff process data in small watersheds limits the models and methods used in runoff simulation research, and the data-driven rainfall-runoff model is simple and efficient , and low data requirements have been widely used. At the same time, with the rise of the fiel...
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IPC IPC(8): G06F30/20G06N20/00G06F111/10
CPCG06N20/00
Inventor 赵雪花张丽娟王畅裴源博祝雪萍蔡文君
Owner TAIYUAN UNIV OF TECH