[1]周倩倩,冯军满,覃钊,等.基于GIS和SWMM的精细化水文表征方法[J].中国给水排水,2023,39(7):126-132.
　ZHOUQian-qian,FENGJun-man,QINZhao,et al.Refined Hydrological Characterization Method Based on GIS and SWMM[J].China Water & Wastewater,2023,39(7):126-132.
点击复制

基于GIS和SWMM的精细化水文表征方法

中国给水排水[ISSN:1000-4062/CN:12-1073/TU] 卷: 第39卷 期数: 2023年第7期 页码: 126-132 栏目: 出版日期: 2023-04-01
Title:
Refined Hydrological Characterization Method Based on GIS and SWMM
作者:
周倩倩1， 冯军满1， 覃钊1， 廖晓婷1， 张建良2， 葛晓光2， 陆宗雷3
（1.广东工业大学 土木与交通工程学院，广东 广州 510006；2.广东省交通规划设计研究院集团股份有限公司，广东 广州 510507；3.格兰富水泵<上海>有限公司，上海 201106）
Author(s):
ZHOU　Qian-qian1， FENG　Jun-man1， QIN　Zhao1， LIAO　Xiao-ting1， ZHANG　Jian-liang2， GE　Xiao-guang2， LU　Zong-lei3
（1. School of Civil and Transportation Engineering， Guangdong University of Technology， Guangzhou 510006， China； 2. Guangdong Communication Planning & Design Institute Group Co. Ltd.， Guangzhou 510507， China； 3. Grundfos Pump Co. Ltd.， Shanghai 201106， China）
关键词:
暴雨洪水管理模型（SWMM）;  地理信息系统（GIS）;  土地利用;  汇水区
Keywords:
SWMM;  GIS;  land use;  catchment area
摘要:
SWMM是模拟城市降雨径流响应的动态模型，其汇水区的空间元素细分方式和水文表征直接影响模拟结果。为此，提出了基于GIS对汇水区的土地利用进行精细化分类的方法，并将下垫面信息通过物理水文定义，反馈、模拟到SWMM的汇水区水文表征和低影响开发（LID）模块描述中，直接影响水文汇流过程。与常规水文构建方法相比，精细化模型中增加的缓冲渗透区可以接收来自间接不透水区的径流，更符合实际径流走向，提高了模型精度。在相同降雨重现期下，精细化模型模拟得到的径流总量、径流峰值和溢流总量均比常规模型要小。同时，该方法可以更合理地模拟LID措施的水文作用，可为LID措施提供因地制宜的布设空间和比例。
Abstract:
SWMM is a dynamic model to simulate urban rainfall runoff response, and its spatial element subdivision and hydrological characterization of catchment area directly affects the simulation results. Therefore, this paper proposed a method for refined land use classification in catchment area based on GIS, and fed back and simulated the underlying surface information into the catchment area hydrological characterization and low impact development (LID) module description of SWMM through physical hydrological definition, so as to directly affect the hydrological confluence process. Compared with the conventional hydrological modeling method, the buffer infiltration area added in the refined model received runoff from the indirect impervious area, which was more consistent with the actual runoff trend and improved the model accuracy. Under the same rainfall return period, the total runoff, peak runoff and overflow of the refined model were all smaller than those of the conventional model. In addition, this method can more reasonably simulate the hydrological performance of LID measures, and provide layout space and proportion for LID measures according to local conditions.

相似文献/References:

[1]袁绍春,李迪,陈垚,等.基于BP神经网络算法的SWMM参数自动率定方法[J].中国给水排水,2021,37(21):125.
　YUAN Shao-chun,LI Di,CHEN Yao,et al.Automatic Calibration Procedure of Storm Water Management Model Parameters Based on Back Propagation Neural Network Algorithm[J].China Water & Wastewater,2021,37(7):125.
[2]周领,陆燕清.排水管道瞬变流的SWMM模拟能力研究[J].中国给水排水,2022,38(5):108.
　ZHOULing,LUYan-qing.SWMM Simulation Capability for Transient Flow in Drainage Pipe[J].China Water & Wastewater,2022,38(7):108.
[3]康得军,温儒杰,邱福杰,等.基于SWMM和GIS的城市内涝4D可视化研究[J].中国给水排水,2023,39(13):133.
　KANGDe-jun,WENRu-jie,QIUFu-jie,et al.4D Visualization of Urban Waterlogging Based on SWMM and GIS[J].China Water & Wastewater,2023,39(7):133.

更新日期/Last Update: 2023-04-01