A SWMM real-time simulation method coupled with short-term rainfall forecast

Abstract

The present invention discloses a SWMM real-time simulation method coupled with short-term rainfall forecast. First, the basic content and rainfall input content in the inp file of SWMM are prepared by constructing the corresponding relationship between the short-term rainfall forecast grid and the SWMM sub-catchment area; secondly, the SWMM dynamic link library is called to perform simulation calculation, and the simulation results of the pipe fullness and node overflow in the next 2 hours are read and output; finally, the rainfall input content is modified regularly, the simulation calculation is driven, and the simulation results are output. The present invention realizes the regular rolling forecast of the pipe fullness and the node overflow, and accurately forecasts and locates the overflow position of the pipe network.

Description

Technical Field

[0001] The invention belongs to the technical field of municipal engineering, and is a SWMM real-time simulation method coupled with short-term rainfall forecast, which is used for efficiently and accurately forecasting the overflow of rainwater pipe network nodes for urban waterlogging disasters. Background Art

[0002] Since 2011, large-scale urban waterlogging has occurred in many cities in my country. For waterlogging disasters, it is necessary to determine in advance the overflow location and water accumulation location of the rainwater pipe network after rainfall, so as to effectively guide the emergency deployment and dispatching of personnel and materials in flood prevention work. Summary of the invention

[0003] The purpose of the present invention is to propose a SWMM real-time simulation method coupled with short-term rainfall forecast, input the short-term rainfall forecast product into SWMM and realize the real-time simulation of the model, forecast the overflow volume and overflow position of the pipeline node in the next 2 hours, which is helpful to guide the early and accurate deployment of flood control dispatch and emergency command work.

[0004] The purpose of the present invention is achieved through the following specific technical solutions:

[0005] (1) Establish the correspondence between the short-term rainfall forecast grid and the SWMM sub-catchment area. The short-term rainfall forecast is a grid-based rainfall forecast, and its forecast result is a 1km×1km grid distribution. Each grid has the rainfall process in the next 2 hours. It is necessary to establish a correspondence between the short-term rainfall forecast grid and the SWMM sub-catchment area so that the forecast rainfall can be accurately input into SWMM.

[0006] (2) According to the inp file format requirements of SWMM, the model basic file is prepared to form the basic model files "input_1.txt" and "input_2.txt". Specifically, it includes the following sub-steps:

[0007] (2.1) Write the attribute data of pipelines, nodes, subcatchments, rainfall grids, etc. into "input_1.txt" according to the format requirements of the inp file for [RAINGAGES], [SUBCATCHMENTS], [SUBAREAS], [INFILTRATION], [JUNCTIONS], [OUTFALLS], [STORAGE], [CONDUITS], [PUMPS], [XSECTIONS], and [CURVES];

[0008] (2.2) Write the spatial coordinate information of the model elements. Based on the vector shp files of the pipe network, subcatchment area, rainfall grid, etc., and in accordance with the format requirements of the inp file for the [COORDINATES], [VERTICES], [SYMBOLS], and [Polygons] parts, write the spatial coordinate information of the model elements to generate "input_2.txt";

[0009] (3) According to the inp file format requirements of SWMM, the rainfall input part is prepared to form the rainfall file "input_3.txt" and the model setting file "input_4.txt". The specific steps include the following:

[0010] (3.1) According to the correspondence between the short-term rainfall forecast grid and the SWMM subcatchment number in step (1), obtain the short-term rainfall forecast grid number corresponding to each subcatchment;

[0011] (3.2) According to the short-term rainfall forecast grid number, call the http interface provided by the short-term rainfall forecast product to obtain the next 2-hour rainfall process of the grid. That is, each SWMM sub-catchment area can correspond to a next 2-hour rainfall process time series.

[0012] (3.3) Write the next 2 hours rainfall process of the grid into the "input_3.txt" file according to the requirements of the [TIMESERIES] part of the inp file;

[0013] (3.4) Follow steps (3.1) to (3.3) to traverse each SWMM subcatchment until all are completed.

[0014] (3.5) Call the http interface provided by the short-term rainfall forecast product to read the start and end time of the forecast rainfall, and write "input_4.txt" according to the requirements of the [OPTIONS] section of the inp file to set the start and end time of the model calculation;

[0015] (4) Merge "input_4.txt", "input_3.txt", "input_1.txt" and "input_2.txt" into one text document in the above order, and change the document name and suffix to "model.inp";

[0016] (5) Call the swmm_open function in the SWMM dynamic link library to load the "model.inp" file; call the swmm_run function to drive the model simulation calculation; call the swmm_close function to close the model and generate the "model.rpt" and "model.out" files;

[0017] (6) Call the OpenSwmmOutFile function in the SWMM dynamic link library to open the "model.out" file; call the GetSwmmResult function to read the overflow flow results and pipe fullness results of each pipe network node, and output the results in the specified format; call the CloseSwmmOutFile function to close the "model.out" file;

[0018] Furthermore, first, execute step (1) and step (2) to produce the basic file of SWMM, wherein the results generated by step (1) and step (2) are the basic results of the SWMM model and are fixed during the real-time simulation process; secondly, execute step (3) to step (6) every hour to realize the online rolling real-time simulation of SWMM and continuously refresh the forecast results.

[0019] Furthermore, the method for establishing the correspondence between the short-term rainfall forecast grid and the SWMM sub-catchment in step (1) is as follows: first, obtain the geometric center coordinates of the SWMM sub-catchment; second, determine the short-term rainfall forecast grid number to which the center point of the SWMM sub-catchment belongs in terms of spatial position; finally, establish a correspondence table between the SWMM sub-catchment number and the short-term rainfall forecast grid number.

[0020] Furthermore, for the specific requirements of the inp file format in steps (2) and (3), please refer to the relevant provisions on file format in the SWMM user manual.

[0021] Furthermore, the attribute data of pipes, nodes, subcatchments, rainfall grids, etc. in step (2) are specifically the attributes of model elements specified in the SWMM user manual. The spatial coordinate information of the model elements in step (2) includes the coordinates of point elements, the starting and ending coordinates of line elements, and the coordinates of each vertex of surface elements.

[0022] Furthermore, the rainfall process of the grid in the next 2 hours in step (3) is a curve of the relationship between rainfall intensity (unit: mm / h) and time, and the curve data interval is 5 minutes.

[0023] Furthermore, the related functions in step (5) and step (6) are obtained by compiling the SWMM source code to generate a DLL file to obtain the function calling method.

[0024] As a mature hydraulic model, SWMM (Storm Water Management Model) can effectively simulate the flow generation and confluence process on the surface after rainfall, as well as the drainage process of rainwater in the pipe network, and analyze the node overflow water volume and location when the rainwater pipe network system encounters rainfall events.

[0025] The present invention couples the SWMM real-time simulation method of short-term rainfall forecast, couples the short-term rainfall forecast product with SWMM, takes the spatial rainfall process of the short-term rainfall forecast product in the next 2 hours as input and uses the SWMM model for simulation, can judge the overflow location of the rainwater pipe network in the next 2 hours, the overflow volume and the fullness of the pipe, and guide the relevant departments of flood control dispatch and emergency command to carry out key deployment in advance for areas where the pipe network overflow is more serious and the pipes are in full operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a flow chart of the present invention;

[0027] Figure 2 It is the basic data situation of the embodiment;

[0028] Figure 3a It is the [RAINGAGES] content in the input_1.txt file created in the embodiment;

[0029] Figure 3b It is the [SUBCATCHMENT] content in the input_1.txt file created in the embodiment;

[0030] Figure 3c It is the [INFILTRATION] content in the input_1.txt file created in the embodiment;

[0031] Figure 3d It is the [JUNCTIONS] content in the input_1.txt file created in the embodiment;

[0032] Figure 3e It is the [OUTFALLS] content in the input_1.txt file created in the embodiment;

[0033] Figure 3f It is the [STORAGE] content in the input_1.txt file created in the embodiment;

[0034] Figure 3g It is the [CONDUITS] content in the input_1.txt file created in the embodiment;

[0035] Figure 4 It is part of the content of the input_2.txt file created in the embodiment;

[0036] Figure 5 It is part of the content of the input_3.txt file created in the embodiment;

[0037] Figure 6It is part of the content of the input_4.txt file created in the embodiment;

[0038] Figure 7 The model.inp file created in the embodiment is loaded into the SWMM software for display;

[0039] Figure 8 is a pipeline fullness prediction result data table in the embodiment database;

[0040] Fig. 9 It is a node overflow forecast result data table in the embodiment database. DETAILED DESCRIPTION

[0041] The specific technical solution of the present invention is explained in conjunction with embodiments.

[0042] This embodiment follows Figure 1 Proceed as shown in the flowchart.

[0043] Taking Huoju District in Zhongshan City as an example, the area is about 10 square kilometers, the total length of the rainwater pipe network is about 186 kilometers, and the number of rainwater inspection wells is 12,265. We now have a short-term rainfall forecast product for this area, with a forecast grid size of 1 km × 1 km and a total of 30 grids. The basic data of the study area and the short-term rainfall forecast grid are as follows: Figure 2 shown.

[0044] According to the spatial position of the short-term rainfall forecast grid and the geometric center of the sub-catchment, the corresponding relationship between the two numbers is extracted, as shown in Table 1, of which there are 12183 sub-catchments in total.

[0045] Table 1

[0046]

[0047] According to the attribute data of pipelines, nodes, subcatchments, rainfall grids, etc., write the contents of [RAINGAGES], [SUBCATCHMENTS], [SUBAREAS], [INFILTRATION], [JUNCTIONS], [OUTFALLS], [STORAGE], [CONDUITS], [PUMPS], [XSECTIONS], and [CURVES] to create "input_1.txt", such as Figure 3a to Figure 3g shown.

[0048] Write [COORDINATES], [VERTICES], [SYMBOLS], [POLYGONS] according to the vector shp files of pipe network, subcatchment area, rainfall grid, etc. to make "input_2.txt" file, such as Figure 4 shown.

[0049] According to the short-term rainfall forecast grid number corresponding to each sub-catchment area, call the http interface to read the grid rainfall forecast data for the next 2 hours, and write it into the [TIMESERIES] part to create the "input_3.txt" file, such as Figure 5 Call the http interface to read the start and end time of the forecast rainfall, write to the [OPTIONS] section and set the model-related operating parameters in the [OPTIONS] section to create the "input_4.txt" file, as shown in the following figure. Figure 6 shown.

[0050] Merge the four files into one text document in the order of "input_4.txt", "input_3.txt", "input_1.txt", and "input_2.txt" and rename it to "model.inp". The merged "model.inp" file is loaded into the model view of SWMM as shown below: Figure 7 shown.

[0051] The swmm_open, swmm_run, and swmm_close functions in the SWMM dynamic link library are called to drive the model calculation, and the OpenSwmmOutFile, GetSwmmResult, and CloseSwmmOutFile functions are called to read the pipe fullness and node overflow results and store them in the database. The database table structure is shown in Tables 2 and 3. After the model results are output to the database, Figure 8 and Fig. 9 shown.

[0052] Table 2 Pipe segment fullness results

[0053] Field Name Field Type illustrate id string Pipe segment number step1 float The corresponding fullness value in the next 5 minutes step2 float The corresponding fullness value for the next 10 minutes ··· float ··· Step 24 float The corresponding fullness value for the next 120 minutes

[0054] Table 3 Node overflow results

[0055] Field Name Field Type illustrate ID string Inspection well number Step 1 float <![CDATA[Overflow value of the node corresponding to the moment 5 minutes in the future (unit: m 3 / s)]]> Step 2 float <![CDATA[Overflow value of the node corresponding to the moment 10 minutes in the future (unit: m 3 / s)]]> ··· float ··· Step 24 float <![CDATA[Overflow value corresponding to the node at the moment 120 minutes in the future (unit: m 3 / s)]]>

[0056] According to the above steps, the simulation results of the pipe segment fullness result table and the node overflow result table in the database are refreshed every hour. By retrieving the pipe segment and node numbers with larger pipe fullness and node overflow in the data table, the pipe segment and node positions are located through GIS vector data, and the areas with severe waterlogging in the next 2 hours are locked.

Claims

1. A SWMM real-time simulation method coupled with short-term rainfall forecast, characterized in that: By coupling the short-term forecast rainfall product into SWMM for simulation, the pipe filling degree and node overflow volume in the next 2 hours are predicted; The following steps are involved: (1) Construct the correspondence between the short-term rainfall forecast grid and the SWMM subcatchment area; (2) According to the inp file format requirements of SWMM, make the model basic file to form the basic model files "input_1.txt" and "input_2.txt"; Step (2) specifically includes the following sub-steps: (2.1) Write the pipe, node, subcatchment, and rainfall grid attribute data into "input_1.txt" according to the format requirements of the inp file for [RAINGAGES], [SUBCATCHMENTS], [SUBAREAS], [INFILTRATION], [JUNCTIONS], [OUTFALLS], [STORAGE], [CONDUITS], [PUMPS], [XSECTIONS], and [CURVES]; (2.2) Write the spatial coordinate information of the model elements; Based on the pipe network, subcatchment area, and rainfall grid vector shp files, and in accordance with the format requirements of the inp file for the [COORDINATES], [VERTICES], [SYMBOLS], and [Polygons] parts, write the spatial coordinate information of the model elements to generate "input_2.txt"; (3) According to the inp file format requirements of SWMM, prepare the rainfall input content to form the rainfall file "input_3.txt" and the model setting file "input_4.txt"; Step (3) specifically includes the following sub-steps: (3.1) According to the correspondence between the short-term rainfall forecast grid and the SWMM subcatchment number in step (1), obtain the short-term rainfall forecast grid number corresponding to each subcatchment; (3.2) According to the short-term rainfall forecast grid number, call the http interface provided by the short-term rainfall forecast product to obtain the next 2-hour rainfall process of the grid, that is, each SWMM sub-catchment area can correspond to a next 2-hour rainfall process time series; (3.3) Write the next 2 hours rainfall process of the grid into the "input_3.txt" file according to the requirements of the [TIMESERIES] part of the inp file; (3.4) Follow steps (3.1) to (3.3) to traverse each SWMM subcatchment until all are completed; (3.5) Call the http interface provided by the short-term rainfall forecast product to read the start and end time of the forecast rainfall, and write "input_4.txt" according to the requirements of the [OPTIONS] section in the inp file to set the start and end time of the model calculation; (4) Merge "input_4.txt", "input_3.txt", "input_1.txt" and "input_2.txt" into one text document in the above order, and change the document name and suffix to "model.inp"; (5) Call the swmm_open function in the SWMM dynamic link library to load the "model.inp" file; call the swmm_run function to drive the model simulation calculation; call the swmm_close function to close the model and generate the "model.rpt" and "model.out" files; (6) Call the OpenSwmmOutFile function in the SWMM dynamic link library to open the "model.out" file; call the GetSwmmResult function to read the overflow flow results and pipe fullness results of each pipe network node, and output the results in the specified format; call the CloseSwmmOutFile function to close the "model.out" file.

2. A SWMM real-time simulation method for coupled short-term rainfall forecast according to claim 1, characterized in that: First, execute steps (1) and (2) to create the basic file of SWMM. The results generated by steps (1) and (2) are the basic results of the SWMM model and are fixed during the real-time simulation process. Then, execute steps (3) to (6) every hour in a rolling cycle to complete the online rolling real-time simulation of SWMM and continuously refresh the model prediction results.

3. The SWMM real-time simulation method for coupled short-term rainfall forecast according to claim 1 is characterized in that: The method of step (1) is: First, obtain the geometric center coordinates of the SWMM subcatchment; Secondly, determine the short-term rainfall forecast grid number to which the SWMM subcatchment center point belongs in terms of spatial location; Finally, a correspondence table between SWMM subcatchment numbers and short-term rainfall forecast grid numbers is established.

4. The SWMM real-time simulation method for coupled short-term rainfall forecast according to claim 1 is characterized in that: The pipe, node, subcatchment, and rainfall grid attribute data in step (2) are specifically the attributes of the model elements specified in the SWMM User Manual; The spatial coordinate information of the model elements in step (2) includes the coordinates of the point elements, the coordinates of the starting point and the end point of the line elements, and the coordinates of each vertex of the surface elements.

5. The SWMM real-time simulation method for coupled short-term rainfall forecast according to claim 1 is characterized in that: The rainfall process of the grid in the next 2 hours in step (3) is a curve of the relationship between rainfall intensity and time, and the curve data interval is 5 minutes; the unit of rainfall intensity is: mm / h.

6. A SWMM real-time simulation method for coupled short-term rainfall forecast according to any one of claims 1 to 5, characterized in that: For specific requirements on the inp file format in steps (2) and (3), please refer to the relevant provisions on file format in the SWMM user manual.

7. A SWMM real-time simulation method for coupled short-term rainfall forecast according to claim 1, characterized in that: The related functions in step (5) and step (6) obtain the function calling method by compiling the SWMM source code to generate a DLL file.

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