潘丽娟1，王冬梅2，任旭华1，石一凡2

　　(1.河海大学水利水电学院，江苏 南京 210098;

　　2.江苏省水利科学研究院，江苏 南京 210017)

　　摘 要：针对传统外业测量水库库容估算方法易受地形、气象条件影响，存在危险性高、效率低等问题，以仑山水库为研究对象，采用机载LiDAR技术估算水库面积及水量变化。通过实地数据采集，利用KD-树算法剔除点云中的粗差点，并采用渐进加密不规则三角网(PTIND)滤波分离出地面点，完成LiDAR点云数据的预处理;根据点云数据建立精细化数字高程模型(DEM)，提取不同水位的水库水面面积;最终利用积分和传统棱台体积估算方法对比分析不同水位水量差值变化。结果表明：与高程实测值相比，DEM高程反演值满足高程精度要求，基于机载LiDAR的水量估算受库底坡度变化的影响，估算值低于传统估算方法的估算值，估算结果更为精确，可为监测水库水量变化提供科学依据。

　　关键词： LiDAR 技术;水量变化;典型水库;估算;机载;无人机;DEM ;点云

　　Estimation of water storage variations in typical reservoirs based on airborne LiDAR technology

　　PAN Lijuan1，WANG Dongmei2，REN Xuhua1，SHI Yifan2

　　(1.College of Water Conservancy & Hydropower Engineering，Hohai University，Nanjing 210098，China;

　　2. Jiangsu Hydraulic Research Institute，Nanjing 210017，China)

　　Abstract：To overcome the deficiency of traditional reservoir monitoring methods due to terrain and climate, this paper applies airborne LiDAR technology to Lunshan reservoir and develops Digital Elevation Models (DEMs) to calculate the changes of reservoir area and water storage. Based on the collected data, the KD-Tree algorithm and Progressive Triangulated Irregular Network Densification (PTIND) are applied to eliminate laser data noise and isolate the ground points. A refined DEM is developed based on pre-processed point cloud data to extract water surface area at different water levels of the reservoir. The variations of water storage at different water levels are estimated and compared by using integral calculus and conventional algorithm. The results show that the inversion values of the DEM meet the accuracy requirements compared with the measured elevation. The estimation of water storage based on airborne LiDAR is impacted by the change of reservoir bottom slope. Compared to traditional observation method, the LiDAR-estimated value is much lower, thus the estimation result is more accurate. This research can provide scientific reference for monitoring the variation of reservoir storage.

　　Key words: LiDAR technology;water storage variations;typical reservoir;estimation;airborne;drone;DEM;point cloud