基于Sentinel-2数据与遥感技术的浅河川径流量估算模型  

Estimation on model of shallow river runoff based on Sentinel-2 Data and Remote Sensing Technology

作　　者：冯刘成 Feng Liucheng(Administration office of Xinjiang Uygur Autonomous Region Tarim River Basin,Alar843300,Xinjiang)

机构地区：[1]新疆维吾尔自治区塔里木河流域干流管理局,新疆阿拉尔843300

出　　处：《吉林水利》2022年第1期45-48,54,共5页Jilin Water Resources

摘　　要：针对西北浅川河流水文资料缺失问题,提出利用中高分辨率的Sentine-2遥感影像反演浅川径流量的方法。该文以塔里木河阿拉尔地区为例,利用2015—2020年夏、冬两季的Sentinel-2影像提取典型断面(SAL-1)处1km范围内水域像元数,结合观测获取的断面径流量数据,通过拟合“像元数-径流量”曲线得到浅川径流量估测模型。为测试该模型的移植性,将模型应用于SAL-2断面,结果表明该断面处的模拟结果与实测数据均具有较高一致性(R^(2)=0.72、MAE=2.21、RMSE=2.26m^(3)/s,P<0.05)。本文利用遥感数据为浅川地区径流资料快速补缺提供了新途径。In view of the lack of hydrological data of shallow rivers in Northwest China,a method of using medium and high resolution Sentinel-2 remote sensing images to retrieve shallow river funoff is proposed.Taking the Alar area of Tarim River as an example,this paper uses the Sentinel-2 images of summer and winter session since 2015 till 2020 to extract the number of water pixels in 1km range of the typical cross-section(SAL-1).Combined with the observed cross-section runoff data,the shallow river runoff estimation model is obtained by fitting the“pixel number-runoff”curve.In order to test the portability of the model,the model is applied to the SAL-2 section,and the results show that the simulation results at the section are in high agreement with the measured data(R^(2)=0.72,MAE=2.21,RMSE=2.26,P<0.05).This paper provides a new way by using remote sensing data to quickly fill the gap of runoff data of shallow river area.

关 键 词：浅川地区 径流量 Sentinel-2遥感影像 估算 

分 类 号：P333[天文地球—水文科学]