摘要
针对传统水库库容监测方法成本高、周期长的问题,本文提出了一种高效、低成本的动态监测技术,为中小型水库管理提供了新方案。以句容水库为研究对象,集成Sentinel-2与实测数据,采用随机森林算法构建水深反演模型,结合水位数据建立水下地形,进而生成库容曲线。结果表明,水深反演精度良好(R^(2)=0.90,RMSE=0.43 m),反演库容与官方数据趋势一致,并建立了面积-库容增量线性关系。相比传统方法,本文方法缩短了库容曲线更新周期,降低了成本。因此,卫星反演测深法能实现库容动态监测,具有快速、经济、便捷等优势,适用于中小型水库的常态化管理,为水利部门提供了切实可行的技术手段。
To address the issues of high cost and long cycles associated with traditional reservoir storage monitoring methods,this study explores an efficient and low-cost dynamic monitoring technology,providing a novel solution for medium and small reservoir management.Taking Jurong reservoir as the study case,we integrated Sentinel-2 data with in-situ measurements and developed a satellite-derived bathymetry model using the random forest algorithm.By combining water level data,underwater topography was reconstructed to generate an updated storage capacity curve.The results demonstrate good accuracy in water depth inversion(R^(2)=0.90,RMSE=0.43 m),with the derived storage capacity showing strong consistency with official data trends.A linear relationship between surface area and storage increment was established.Compared to conventional methods,this approach significantly shortens the update cycle of storage capacity curves while reducing costs.Therefore,satellite-derived bathymetry method proves to be a reliable method for dynamic storage monitoring,offering advantages in speed,cost-effectiveness,and operational convenience.This technique is particularly suitable for routine management of medium and small reservoirs,providing water authorities with a practical and efficient technical solution.
作者
王青青
张中流
卢刚
WANG Qingqing;ZHANG Zhongliu;LU Gang(Jiangsu Province Surveying&Mapping Engineering Institute,Nanjing 210019,China;Nanjing Hydraulic Research Institute,Nanjing 210003,China)
出处
《测绘通报》
北大核心
2026年第2期7-11,共5页
Bulletin of Surveying and Mapping
基金
江苏省重点研发计划(SBE2023030221)。
关键词
句容水库
随机森林
卫星反演测深
水下地形
库容曲线
Jurong reservoir
random forest
satellite-derived bathymetry
underwater topography
reservoir capacity curve
