A method for predicting the reduction of accumulated rainwater in a rainwater well by a sponge facility based on SWMM

Abstract

This invention relates to a prediction method for reducing the cumulative rainwater volume of storm drains using sponge city infrastructure based on SWMM (Sponge Modeling). The method includes the following steps: constructing a hydraulic model of the stormwater pipe network for the target area using SWMM software, and generalizing the target area according to topographical features; selecting an infiltration model and a calculation model, simulating the model using a Chicago rain gauge, and verifying the results using local rainfall data; analyzing pipe flow rate and node water depth to obtain the relationship curve between storm drain node water depth and time; obtaining the cumulative rainwater volume of the storm drain over a period of time based on the relationship curve; then, using the same method, simulating and predicting the cumulative rainwater volume of the storm drain after the installation of sponge city infrastructure over a period of time; finally, calculating the difference in cumulative rainwater volume between the two scenarios to characterize the amount of rainwater reduced by the sponge city infrastructure. This prediction method effectively solves the problems of complex calculation processes, low accuracy, and inaccurate calculation results of rainwater retention by sponge city infrastructure in existing methods for calculating cumulative rainwater volume of storm drains.

Description

Technical Field

[0001] This invention relates to the field of rainfall forecasting technology, specifically to a forecasting method for reducing the amount of accumulated rainwater in storm drains using a sponge city system based on Swimming Swimming Model (SWMM). Background Technology

[0002] The Rainwater Management Model (SWMM) is a dynamic precipitation-runoff simulation model jointly developed by the U.S. Environmental Protection Agency and the Water Resources Center. It is mainly used for single-event or long-term (continuous) simulation of urban runoff volume and water quality.

[0003] Currently, the known method for calculating the accumulated rainwater volume in storm drains involves combining the upstream catchment area with a local storm intensity formula to obtain the flow rate of the stormwater pipe section, and then calculating the maximum water depth using the ultimate strength theory. This method is complex and lacks accuracy. For rainwater retained by sponge city infrastructure, the volumetric method is mostly used, but this method inherently contains errors in the selection of reduction factors, resulting in inaccurate calculations. Therefore, a new technical solution is urgently needed to comprehensively address the problems existing in current technologies. Summary of the Invention

[0004] The purpose of this invention is to provide a prediction method for reducing the amount of accumulated rainwater in rainwater wells based on SWMM (Sponge City Model), which can effectively solve the problems of complex calculation process, low accuracy and inaccurate calculation results of rainwater retention in sponge facilities.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0006] A prediction method for reducing the amount of accumulated rainwater in storm drains using a sponge city system based on Swimming Swim Models (SWMM) includes the following steps:

[0007] S1. Use SWMM software to construct a hydraulic model of the stormwater pipe network in the target area, and generalize the target area according to the terrain trend, dividing it into catchment area, stormwater well, stormwater pipe and discharge outlet;

[0008] S2. Select the infiltration model and calculation model, simulate according to the Chicago rain pattern, and verify using local rainfall data;

[0009] S3. Analyze the flow rate and water depth at the nodes of the pipe section to obtain the relationship curve between the water depth at the nodes of the rainwater well and time;

[0010] S4. Based on the relationship curve, the cumulative rainwater volume in the rainwater well during the time interval t1 to t2 is:

[0011]

[0012] In the formula: A is the bottom area of ​​the rainwater well, and H is the water depth of the rainwater well.

[0013] It also includes step S5: using the same method, simulate and predict the cumulative rainwater volume of the rainwater well after the addition of the sponge facility in the time period t1 to t2, and then calculate the difference in the cumulative rainwater volume in the two cases to characterize the amount of rainwater reduced by the sponge facility.

[0014] Additionally, in the simulation options of SWMM, Horton is selected as the infiltration model, and kinematic wave is selected as the calculation model.

[0015] The prediction method for reducing the accumulated rainwater volume of storm drains based on SWMM provided in the above technical solution can analyze the maximum water depth and accumulated rainwater volume of each storm drain more quickly and accurately than traditional calculation methods. It can calculate the amount of rainwater reduced after adding the sponge facility, providing more convincing data support for improving the drainage capacity of the stormwater pipe network, so as to improve the effect of urban flooding and provide effective decision-making reference for the renovation plan. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the study area in this embodiment;

[0017] Figure 2 This is a generalized map of the study area in this embodiment;

[0018] Figure 3 This is a graph showing the water depth variation over time at key points during the 20-year recurrence period of the non-sponge facility after renovation.

[0019] Figure 4 This is a graph showing the water depth variation over time at key nodes during the 20-year recurrence period after the renovation of the sponge city facilities. Detailed Implementation

[0020] To make the objectives and advantages of this invention clearer, the invention will be specifically described below with reference to embodiments. It should be understood that the following text is merely used to describe one or more specific embodiments of the invention and does not strictly limit the scope of protection specifically claimed by the invention.

[0021] Example

[0022] (1) Overview of the study area

[0023] The overall slope of the study area is between 3% and 4%, with residential as the primary land use type. The total land area is approximately 3.88 hectares, and the total building area is 3.6 hectares. The outdoor stormwater and sewage drainage pipes of the study area were upgraded, with the original stormwater pipe diameter enlarged. A hydraulic model of the stormwater pipe network was constructed using SWMM software to evaluate the drainage capacity of the upgraded stormwater pipes. The study area is as follows: Figure 1 As shown.

[0024] (2) Rainfall data construction

[0025] By collecting nearly 40 years of heavy rainfall data from multiple rainwater stations in the area, and improving and deriving the traditional heavy rainfall intensity formula, the following heavy rainfall intensity formula for the area was finally derived:

[0026] In the formula, i represents the intensity of the rainstorm, in mm / min; t represents the duration of rainfall, in min; and P represents the return period, in years.

[0027] The above-mentioned rainstorm intensity formula was used to simulate rainfall data in the study area. The Chicago rain pattern was used to simulate rainfall conditions with return periods of 2 years, 5 years, 10 years, 20 years, and 50 years, respectively. The peak proportion r was set to 0.4, and the duration was 120 minutes.

[0028] (3) Model building

[0029] The study area was generalized, and based on the topographical features, 31 sub-catchments (ZMJ), 58 stormwater inspection wells (J), 59 stormwater pipes (GQ), and 2 outfalls (PFK) were established. Figure 2 The Horton infiltration model was selected, the kinematic wave was used as the calculation model, and the time calculation step was 10 seconds.

[0030] (4) Water depth analysis of important nodes

[0031] Rainfall data generated by a Chicago rain gauge was input into a computational model to simulate the water depth at nodes with added sponge city infrastructure before and after stormwater pipe renovation. The hydraulic model was then used in SWMM software with generalized data for calculation. Based on changes in stormwater well depth and pipe diameter, key nodes on the main pipeline were selected, numbered J5, J18, J21, J24, J25, and J33, and their maximum water depth under different return periods was analyzed.

[0032] Table 1. Summary data of some nodes

[0033]

[0034] like Figure 3 and Figure 4 As shown, Figure 3 This is a graph showing the water depth variation over time at key points during the 20-year return period for the remodeled sponge-free facility. Figure 4 This is a graph showing the water depth variation over time at key nodes during the 20-year recurrence period after the renovation of the sponge city facilities.

[0035] (5) Results Analysis and Calculation

[0036] After the renovation and the addition of sponge city facilities, with a return period of 20 years, the maximum water depth of each rainwater well decreased, and the integral area of ​​the curve showing the change in water depth of each rainwater well over time decreased compared to the case without sponge city facilities. This means that the accumulated rainwater volume in the rainwater wells decreased, with the reduction being [amount missing]. (A is normalized to 1.0).

[0037] This invention provides a prediction method for reducing the cumulative rainwater volume of rainwater wells based on the SWMM sponge system. It can accurately predict the water depth and cumulative rainwater volume of rainwater wells. It uses the SWMM model to simulate the relationship curve between the water depth and time of rainwater wells, and performs integral processing on the relationship curve to obtain the cumulative rainwater volume of the rainwater well node over a certain period of time.

[0038] The embodiments of the present invention have been described in detail above with reference to the examples. However, the present invention is not limited to the above embodiments. For those skilled in the art, after learning the contents described in the present invention, several equivalent changes and substitutions can be made without departing from the principle of the present invention. These equivalent changes and substitutions should also be considered to fall within the protection scope of the present invention.

Claims

1. A prediction method for reducing the cumulative rainwater volume of storm drains using sponge city infrastructure based on Swimming Swimming Model (SWMM), characterized in that, Includes the following steps: S1. Use SWMM software to construct a hydraulic model of the stormwater pipe network in the target area, and generalize the target area according to the terrain trend, dividing it into catchment area, stormwater well, stormwater pipe and discharge outlet; S2. Select the infiltration model and calculation model, simulate according to the Chicago rain pattern, and verify using local rainfall data; S3. Analyze the flow rate and water depth at the nodes of the pipe section to obtain the relationship curve between the water depth at the nodes of the rainwater well and time; S4. Obtained from the relationship curve t1 to t2 The cumulative rainwater volume in the rainwater wells within the specified time period is: In the formula: A The bottom area of ​​the rainwater well. H This refers to the depth of water accumulation in the rainwater well. S5. Using the same method, simulate and predict the rainwater wells after the addition of sponge city facilities. t1 to t2 The cumulative rainfall over a period of time is calculated, and then the difference between the cumulative rainfall in the two cases can be used to characterize the amount of rainwater reduced by the sponge city facility.

2. The prediction method for reducing the cumulative rainwater volume of rainwater wells based on SWMM for sponge city facilities according to claim 1, characterized in that: In the simulation options of SWMM, select Horton for the infiltration model and select motion wave for the calculation model.

Images