HEC-HMS model multi-session flood parameter calibration method based on MATLAB framework

Abstract

The invention belongs to the field of hydrological forecasting, and particularly provides an HEC-HMS model multi-session flood parameter calibration method based on an MATLAB framework, and the method comprises the steps: obtaining digital elevation data and land utilization data of a research basin, and rainfall runoff data of session flood, and constructing a data storage system database of an HEC-DSS model; preparing necessary files for the operation of the HEC-HMS model; the method comprises the following steps: establishing an interface program of an MATLAB platform, an HEC-HMS model and an HEC-DSSVue data storage system, constructing a super-multi-objective function for simulating multi-session flood at the same time, and optimizing the super-multi-objective function at the same time by adopting a super-multi-objective large-scale optimization algorithm LMOCSO based on a competitive group optimizer. And obtaining the optimal parameters of the HEC-HMS model suitable for researching watershed session flood simulation. According to the method, coupling of the MATLAB platform, the HEC-HMS model and the HEC-DSSVue data storage system is achieved, and the optimal parameters of the HEC-HMS model suitable for watershed session flood simulation can be obtained on the MATLAB framework through a super-multi-target large-scale optimization algorithm.

Description

Technical Field

[0001] The invention belongs to the field of hydrological forecasting, and in particular relates to a HEC-HMS model multi-flood parameter calibration method based on a MATLAB framework. Background Art

[0002] At present, in order to study the problems of reservoir operation and flood disaster prevention, the parameter calibration of the basin hydrological model is one of the essential steps. The HEC-HMS model is a semi-distributed basin hydrological model developed by the U.S. Army Corps of Engineers. The model provides a friendly graphical interface, is easy to operate, and has high simulation accuracy. It has been widely used in hydrological simulation and water quality simulation at home and abroad. In terms of parameter calibration, the model provides 2 parameter optimization methods and 14 objective functions for users to choose from, which can calibrate the objective function of flood events very efficiently. However, the parameter optimization method provided by the model is a single-objective optimization method. The parameter calibration function is only for a single objective function of a single flood event. The obtained model parameters are only applicable to the current calibrated flood event, and the simulation effect of other flood events is poor. In order to obtain model parameters that can correctly reflect the flood characteristics of the basin and are applicable to multiple flood events, it is often necessary to use sensitivity analysis and manual parameter adjustment methods. This method is very time-consuming and requires high operator experience. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a multi-flood parameter calibration method for the HEC-HMS model based on the MATLAB framework, and at the same time optimize the objective function of a large number of floods, so as to obtain flood model parameters that can reflect the characteristics of watershed runoff.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is: a multi-flood parameter calibration method of the HEC-HMS model based on the MATLAB framework, comprising the following steps: S1. Collection and compilation of data; S2. Preparation of necessary documents for running the HEC-HMS model; Creation of the interface between S3, MATLAB platform and HEC-HMS model; S4, establish the interface between MATLAB platform and HEC-DSSVue data storage system; S5. Establishment of multi-objective large-scale optimization function; S6. Optimize the multi-objective large-scale optimization function and determine the Pareto optimal solution of the multi-objective function; S7. Selection of the optimal solution of the HEC-HMS model: Using the Euclidean distance method, a solution with the minimum distance to the ideal solution is selected from the Pareto optimal solution obtained in step S6 as the optimal solution of the HEC-HMS model.

[0005] In the preferred scheme, in step S1, digital elevation data and land use data of the study basin are collected, a basin model of the study basin is generated through a geographic information system tool, and the impermeability of each sub-basin of the basin model is calculated; precipitation data excerpt tables of each rain gauge and flood element excerpt tables of each hydrological station are collected, rainfall runoff data of floods are extracted, and the data are sorted into hourly data and written into the HEC-DSSVue data storage system to form a database of the HEC-HMS model, and the database of the HEC-HMS model is a database in .dss format.

[0006] In a preferred solution, in step S2, the necessary files for running the HEC-HMS model include engineering files, watershed model files, meteorological files, site files, control files and operation files.

[0007] In the preferred solution, in step S3, the method for creating the interface between the MATLAB platform and the HEC-HMS model is: create a script for running the HEC-HMS model on the MATLAB platform, first import all functions and classes from the Jython module of HEC-HMS, then open the specified HEC-HMS project, the MATLAB platform provides the necessary files for running the HEC-HMS model, run a certain flood, and finally exit the HEC-HMS model.

[0008] In the preferred scheme, in step S4, the method for establishing the interface between the MATLAB platform and the HEC-DSSVue software is: first, create an operation script of the HEC-DSSVue software to read the operation results of the HEC-HMS model, and output the measured flow series, simulated flow series and corresponding time series of the basin outlet section in the operation results to an EXCEL table; automatically run the HEC-DSSVue data storage system in MATLAB, execute the operation script of the HEC-DSSVue software, and enable MATLAB to automatically read the calculation results of the HEC-HMS model in step S3.

[0009] In a preferred solution, in step S5, the method for establishing the super multi-objective large-scale optimization function is: Set the i The objective function of flood optimization is: ,The objective function is selected according to the optimization effect of a single flood, and the residual sum of squares function, the peak weighted root mean square error function, the flood volume error percentage function, or the comprehensive function that comprehensively considers the impact of the flood peak and volume are selected. Several objective functions are designed according to the number of floods in each group; Construct a multi-objective large-scale optimization function, the expression is: (1); In formula (1), For the constructed multi-objective large-scale optimization function, represents the first optimization objective, Represents the nth optimization objective.

[0010] In a preferred solution, the peak weighted root mean square error function is: (2); In formula (2), Indicates i Objective function of flooding; For the i The number of ordinates of the flow process line of the flood; The measured flood was j Traffic flow at the moment; The output calculated with the selected model parameters is given by i The flood in j Traffic flow at the moment; is the average value of the measured flood flow; The residual sum of squares function is: (3); The flood error percentage function is: (4); In formula (4), represents the runoff depth of the measured flood, It represents the runoff depth of flood simulated by the hydrological model; The comprehensive function that comprehensively considers the impact of flood peak and flood volume is: (5); In the formula, Indicates the weight corresponding to the jth flow sample point reflecting the flood distribution characteristics; in Calculated by formula (6): (6); In the formula is the runoff in the jth period of the flood; is the total runoff of the flood; in, is calculated by formula (7): (7); In the formula, The time interval for the runoff data with equal time intervals; Calculated by formula (8): (8).

[0011] In a preferred solution, in step S7, the Euclidean distance calculation method is as follows: (9); In formula (9), Indicates i The Euclidean distance of the Pareto solutions; The vector representing the point of the i-th Pareto solution; A vector representing a reference point; represents the dimension of the Pareto solution vector; Indicates i The first Pareto solution j The value of the dimension; Indicates the reference point j The value of a dimension.

[0012] The present invention provides a method for calibrating multiple flood parameters of a HEC-HMS model based on a MATLAB framework, which has the following beneficial effects: 1. When using the HEC-HMS model to calibrate flood parameters, the objective function of the flood is constructed on the MATLAB platform and used as a sub-objective function. The multi-objective function is further constructed from the sub-objective function. The constructed multi-objective function is calibrated using an algorithm suitable for large-scale optimization of multi-objectives to obtain the Pareto optimal solution. The Euclidean distance method is used to obtain the optimal parameters of the HEC-HMS flood model suitable for the study basin.

[0013] 2. The bidirectional coupling between the MATLAB platform and the HEC-HMS model is realized, which improves the limitation of the HEC-HMS model that it can only optimize a single flood. Even if the operator does not have rich experience, the optimal parameters of the HEC-HMS flood model suitable for multi-flood simulation that reflects the basin's runoff characteristics can still be obtained through simple operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The present invention will be further described below in conjunction with the accompanying drawings and embodiments: Figure 1 A watershed model map constructed for GIS; Figure 2 It is the change diagram of imperviousness rate in each sub-basin in each year; Figure 3 It is the database interface of HEC-HMS model; Figure 4 The Pareto optimal solution obtained by optimizing the multi-objective large-scale optimization algorithm; Figure 5 are the optimal parameters of the HEC-HMS model; Figure 6 The flow process line comparison diagram of each flood obtained by the optimal parameters of the HEC-HMS model; Figure 7 Scripts for running HEC-HMS models on the MATLAB platform; Figure 8 This is the running script for the HEC-DSSVue software. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical scheme and game code of the present invention more clear, the present invention is further described in detail below with reference to the accompanying drawings. It should be understood that the specific facts and methods described here are only used to explain the present invention and are not used to limit the present invention.

[0016] Combination Figure 1 to Figure 8 The specific embodiments of the present invention are described in further detail.

[0017] This embodiment takes the parameter calibration of the HEC-HMS flood model in the basin above the Dapoling hydrological station in the upper reaches of the Huaihe River as an example to illustrate the effect achieved by the present invention.

[0018] Dapoling Station is the uppermost hydrological station of the Huaihe River mainstream, controlling a drainage area of ​​1,640 square kilometers. The river above Dapoling is 73 kilometers long, and the drainage area is mostly mountainous and hilly with good vegetation. The river is a mountain stream river with many tributaries, a large slope, fast confluence, rapid water flow, and easy to dry up during droughts. There are not many water conservancy projects in the basin, and rice is the main crop. There are 4 rain gauges in the basin above Dapoling. The embodiment is based on the rainfall excerpts of 4 rain gauges for 20 floods from 1987 to 2009, the flood element excerpts of Dapoling Station, digital elevation data and land use data, and the optimal parameter calibration of the HEC-HMS model suitable for super-multiple flood simulations is implemented on the MATLAB platform. The method steps of the HEC-HMS flood model parameter calibration method based on the MATLAB framework in this embodiment are as follows: Step 1: Collect digital elevation data and land use data of the watershed above the Dapoling hydrological station, and generate a watershed model of the study basin using geographic information system tools, as shown in the attached figure. Figure 1 As shown in the figure, the changes in the imperviousness of each sub-basin in the basin model in each year are calculated, see the attached Figure 2 As shown. All the rain falling on impermeable ground is converted into surface runoff without any loss, while part of the rain falling on permeable ground will be lost by infiltration, and the remaining part will form surface runoff.

[0019] The created HEC-HMS model database interface is as follows Figure 3 shown.

[0020] Step 2: Prepare the necessary engineering files, watershed model files, meteorological files, site files, control files, operation files, etc. for the operation of the HEC-HMS model, all of which are written and provided by the MATLAB platform.

[0021] Step 3: Creation of interface between MATLAB platform and HEC-HMS model: Create a script to run the HEC-HMS model on the MATLAB platform. First, import all functions and classes from the Jython module of HEC-HMS, then open the specified HEC-HMS project, and the MATLAB platform will provide the necessary files for running the HEC-HMS model. Run a flood event and finally exit the HEC-HMS model.

[0022] The created interface between MATLAB and HEC-HMS model can realize setting various parameters of HEC-HMS model by MATLAB and automatically running HEC-HMS model.

[0023] The script for running the HEC-HMS model on the MATLAB platform is as follows Figure 7 shown.

[0024] Step 4: Establish an interface between the MATLAB platform and the HEC-DSSVue data storage system: First, create a running script for the HEC-DSSVue software to read the running results of the HEC-HMS model, and output the measured flow series, simulated flow series and corresponding time series of the basin outlet section in the running results to an EXCEL table; automatically run the HEC-DSSVue data storage system in MATLAB, execute the running script of the HEC-DSSVue software, and enable MATLAB to automatically read the calculation results of the HEC-HMS model in step S3.

[0025] The interface created between MATLAB and the HEC-DSSVue data storage system can automatically output the results of continuous and unlimited HEC-HMS model flood run times to an EXCEL file with the same specified file name. The results of each run are constantly refreshed without affecting each other.

[0026] The running script of the created HEC-DSSVue software is as follows Figure 8 shown.

[0027] Step 5: Establishment of super-multi-objective large-scale optimization function. The created super-multi-objective function is composed of the objective functions of each flood event, and its dimension is the same as the number of flood events to be rated.

[0028] Set the i The objective function of flood optimization is: The objective function is selected according to the optimization effect of a single flood. The residual sum of squares function, the peak weighted root mean square error function, the flood volume error percentage function, or the comprehensive function that comprehensively considers the impact of flood peak and volume can be selected. Different objective functions can be selected for each flood, and several objective functions are designed for each group according to the number of floods.

[0029] The variables in each objective function vary according to the number of sub-basins and river sections divided in the watershed model and the runoff generation and confluence method adopted.

[0030] Construct a multi-objective large-scale optimization function, the expression is: (1); In formula (1), For the constructed multi-objective large-scale optimization function, represents the first optimization objective, Represents the nth optimization objective.

[0031] In this embodiment, the objective function of each dimension in the super-multiple objective functions adopts the error square sum function.

[0032] Step 6: Optimize the large-scale optimization function with multiple objectives and determine the Pareto optimal solution of the multi-objective function.

[0033] In this embodiment, a large-scale multi-objective optimization algorithm (LMOCSO) based on a competitive swarm optimizer is used to optimize the multi-objective function established in step 5, and the Pareto optimal solution obtained is as follows: Figure 4 shown.

[0034] Step 7: Use the Euclidean distance method to select a solution with the minimum distance to the ideal solution from the Pareto optimal solution obtained in step S6 as the optimal solution of the HEC-HMS model. The algorithm based on super multi-objective large-scale optimization can be used to calibrate more than three floods at the same time, and there are more than 100 parameters in the HEC-HMS model of each flood.

[0035] The optimal parameters of the HEC-HMS model determined by the Euclidean distance method are as follows: Figure 5 shown.

[0036] The comparison of the flow process lines of each flood obtained by the optimal parameters of the HEC-HMS model is shown in the figure below: Figure 6 shown.

[0037] It can be seen from the above embodiments that the HEC-HMS model multi-flood parameter calibration method based on the MATLAB framework constructed by the present invention can obtain the Pareto solution of the hydrological model parameters that simultaneously makes the objective function of each flood at a relatively small value, and further determine the optimal parameters of the hydrological model from the Pareto optimal solution through the Euclidean distance method. The parameters can enable the hydrological model to achieve the optimal simulation effect for multiple floods at the same time. The method realizes the simultaneous automatic calibration of multiple objective functions of multiple floods of the HEC-HMS model, and significantly improves the accuracy and efficiency of the HEC-HMS model parameter calibration.

Claims

1. A multi-event flood parameter calibration method for HEC-HMS model based on MATLAB framework, characterized in that: The following steps are involved: S1. Collection and compilation of data; S2. Preparation of necessary documents for running the HEC-HMS model; Creation of the interface between S3, MATLAB platform and HEC-HMS model; S4, establish the interface between MATLAB platform and HEC-DSSVue data storage system; S5. Establishment of multi-objective large-scale optimization function; S6. Optimize the multi-objective large-scale optimization function and determine the Pareto optimal solution of the multi-objective function; S7. Selection of the optimal solution of the HEC-HMS model: Using the Euclidean distance method, a solution with the minimum distance to the ideal solution is selected from the Pareto optimal solution obtained in step S6 as the optimal solution of the HEC-HMS model.

2. The method for calibrating multiple flood parameters of the HEC-HMS model based on MATLAB framework according to claim 1 is characterized in that: In the step S1, the digital elevation data and land use data of the study basin are collected, the basin model of the study basin is generated through the geographic information system tool, and the impermeability of each sub-basin of the basin model is calculated; the precipitation data excerpt table of each rain gauge and the flood element excerpt table of each hydrological station are collected, the rainfall runoff data of the flood are extracted, the data are sorted into hourly data, and written into the HEC-DSSVue data storage system to form the database of the HEC-HMS model.

3. The method for calibrating multiple flood parameters of the HEC-HMS model based on MATLAB framework according to claim 1 is characterized in that: In step S2, the necessary files for running the HEC-HMS model include engineering files, watershed model files, meteorological files, site files, control files and operation files.

4. The method for calibrating multiple flood parameters of the HEC-HMS model based on MATLAB framework according to claim 1 is characterized in that: In step S3, the method for creating the interface between the MATLAB platform and the HEC-HMS model is as follows: create a script for running the HEC-HMS model on the MATLAB platform, first import all functions and classes from the Jython module of the HEC-HMS, then open the specified HEC-HMS project, the MATLAB platform provides the necessary files for running the HEC-HMS model, run a flood of a certain time, and finally exit the HEC-HMS model.

5. The method for calibrating multiple flood parameters of the HEC-HMS model based on MATLAB framework according to claim 1 is characterized in that: In step S4, the method for establishing the interface between the MATLAB platform and the HEC-DSSVue software is as follows: first, a running script of the HEC-DSSVue software is created to read the running results of the HEC-HMS model, and the measured flow series, simulated flow series and corresponding time series of the basin outlet section in the running results are output to an EXCEL table; the HEC-DSSVue data storage system is automatically run in MATLAB, and the running script of the HEC-DSSVue software is executed, so that MATLAB can automatically read the calculation results of the HEC-HMS model in step S3.

6. The method for calibrating multiple flood parameters of the HEC-HMS model based on MATLAB framework according to claim 1 is characterized in that: In step S5, the method for establishing the multi-objective large-scale optimization function is: Set the i The objective function of flood optimization is: ,The objective function is selected according to the optimization effect of a single flood, and the residual sum of squares function or the peak weighted root mean square error function or the flood volume error percentage function or the comprehensive function that comprehensively considers the impact of the flood peak and volume is selected. Several objective functions are designed according to the number of floods in each group; Construct a multi-objective large-scale optimization function, the expression is: (1)； In formula (1), To construct a large-scale optimization function with multiple objectives, represents the first optimization objective, Represents the nth optimization objective.

7. The method for calibrating multiple flood parameters of the HEC-HMS model based on MATLAB framework according to claim 6 is characterized in that: The peak weighted root mean square error function is: (2)； In formula (2), represents the objective function of the ith flood; is the ordinate number of the flow process line of the i-th flood; The measured flood was j Traffic flow at the moment; The output calculated with the selected model parameters is given by i The flood in j Traffic flow at the moment; is the average value of the measured flood flow; The residual sum of squares function is: (3)； The flood error percentage function is: (4)； In formula (4), represents the runoff depth of the measured flood, It represents the runoff depth of flood simulated by the hydrological model; The comprehensive function that comprehensively considers the impact of flood peak and flood volume is: (5)； In the formula, Indicates the weight corresponding to the jth flow sample point reflecting the flood distribution characteristics; in Calculated by formula (6): (6)； In the formula, is the runoff in the jth period of the flood; is the total runoff of the flood; in, Calculated by formula (7): (7)； In the formula, The time interval for the runoff data with equal time intervals; Calculated by formula (8): (8)。 8. The method for calibrating multiple flood parameters of the HEC-HMS model based on MATLAB framework according to claim 1 is characterized in that: In step S7, the Euclidean distance calculation method is as follows: (9)； In formula (9), Indicates i The Euclidean distance of the Pareto solutions; The vector representing the point of the i-th Pareto solution; A vector representing a reference point; represents the dimension of the Pareto solution vector; Indicates i The first Pareto solution j The value of the dimension; Indicates the reference point j The value of a dimension.

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