| 邵银龙,李晓晨,廖美廷,马景胜,白音包力皋,周小日.动态径流系数法和基于城市功能区的SWMM参数率定方法研究[J].中国水利水电科学研究院学报,2024,22(4):342-352 |
| 动态径流系数法和基于城市功能区的SWMM参数率定方法研究 |
| Calibration method of the Storm Water Management Model based on dynamic runoff coefficients and urban functional areas |
| 投稿时间：2023-04-25 |
| DOI：10.13244/j.cnki.jiwhr.20230194 |
| 中文关键词: 径流系数 SWMM模型 城市功能区 不确定性参数 Horton方程 |
| 英文关键词:runoff coefficient SWMM model urban functional area uncertain parameters Horton equation |
| 基金项目:水利部重大科技项目(SKR-2022056);华东院科技项目(ZXY2021-FJ-02-08) |
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| 中文摘要: |
| 城市雨洪模型是研究城市内涝形成规律及演进过程的重要手段，但在我国城市化进程加速、雨水内涝监测能力不足的背景下，模型参数率定和应用面临挑战。为解决缺乏实测雨洪数据条件下城市雨洪模型参数校准的难题，本文提出了根据地理和气候特征计算雨水径流量的动态径流系数法和基于城市功能区的Storm Water Management Model (SWMM)参数率定方法。在福建省三明市的应用表明：动态径流系数法与规范和经验公式结果一致，与传统方法相比则能反映降雨产流随雨强、下渗等因素变化的规律，更符合城市降雨产流的实际过程。基于城市功能区的参数率定方法结果与研究区城市化水平和下垫面特征相符。率定后雨水径流过程NSE值达到0.80，雨水总径流量误差处于6%以内，洪峰时间误差小于3分钟。本文提出的方法可为缺乏实测雨洪数据地区的城市雨洪模拟提供参考。 |
| 英文摘要: |
| Urban stormwater models are essential in analyzing the patterns and dynamics of urban flooding.However，calibrating and applying these models presents challenges amid China's rapid urbanization and limited stormwater monitoring infrastructure.To overcome the challenges of parameter calibration in urban stormwater models without empirical stormwater data，this study employs a dynamic runoff coefficient method for estimating stormwater runoff volumes，with Sanming city of China’s Fujian Province as a case study.Moreover，we introduce a SWMM(Storm Water Management Model) parameter calibration strategy based on urban functional areas to enhance the model accuracy and reliability.The application reveals that the dynamic runoff coefficient method corresponds closely with conventional and empirically derived formulas，effectively capturing the variability of runoff coefficients in response to rainfall intensity and infiltration changes.This tailored parameter calibration method for urban functional areas produces results in agreement with the area's level of urbanization and surface characteristics.The optimized model successfully achieves an NSE value of 0.80，keeping the total runoff volume error within 6% and the peak flow timing error under three minutes.The methodologies proposed herein offer valuable insights for simulating urban stormwater in regions without comprehensive stormwater data. |
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