LAIZe-hui,PENGJin-shuang,BAOShi-tai,et al.Prediction of Urban Drainage Manhole Water Level Using Support Vector Machine Regression[J].China Water & Wastewater,2025,41(13):126-130.
基于支持向量机回归的城市排水窨井水位预测
- Title:
- Prediction of Urban Drainage Manhole Water Level Using Support Vector Machine Regression
- Keywords:
- urban drainage system; water level prediction; support vector machine regression; quality and efficiency improvement
- 摘要:
- 为实时掌握城市排水管网水位状态，减少水位监测设备长期运行的维护成本，通过获取排水窨井水位及降雨量短期监测数据，分析水位站点水文特征因子，制作样本数据集，并对支持向量机回归算法进行优化训练，构建城市排水窨井水位预测模型，最后利用典型天气数据对模型进行测试，模型预测结果精度良好。与长期布设窨井水位传感器开展长期监测相比，该方法通过获取短期水位数据即可对窨井实时水位进行预测，具有部署方便、运维成本低的特点，在城市排水日常提质增效运维、内涝应急调度等业务应用中具有较高的实用价值。
- Abstract:
- A model for predicting urban drainage manhole water level was constructed to monitor the water level status of the urban drainage network in real time and reduce the long-term operational maintenance costs of water level monitoring equipment. This involved collecting short-term monitoring data on manhole water levels and rainfall, analyzing hydrological characteristic factors of water level stations, creating a sample dataset, and optimizing and training a support vector machine regression algorithm. The model was subsequently tested using typical weather data, and the results demonstrated high prediction accuracy. Compared with the long-term installation of manhole water level sensors for continuous monitoring, this approach enabled the prediction of real-time manhole water levels by acquiring short-term water level data. It was characterized by ease of deployment and low operational and maintenance costs, making it highly practical for business applications such as daily quality and efficiency enhancement in urban drainage operations, and emergency dispatching during urban waterlogging events.
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