Inversion of Yellow River Runoff Based on Multi-source Radar Remote Sensing Technology

被引：1

作者：

Min Lin ^{[1
,2
,3
]}

Wang Ning ^{[1
,2
,4
]}

Wu Lin ^{[1
,2
,4
]}

Li Ning ^{[1
,2
,4
]}

Zhao Jianhui ^{[1
,2
,4
]}

机构：

[1] Henan Univ, Henan Engn Res Ctr Intelligent Technol & Applicat, Kaifeng 475004, Peoples R China

[2] Henan Univ, Henan Key Lab Big Data Anal & Proc, Kaifeng 475004, Peoples R China

[3] Henan Univ, Network Informat Ctr Off, Kaifeng 475004, Peoples R China

[4] Henan Univ, Coll Comp & Informat Engn, Kaifeng 475004, Peoples R China

来源：

JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY | 2020年 / 42卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Synthetic Aperture Radar (SAR); Runoff calculation model; Radar Altimetry (RA); Relationship fitting; Yellow River; VALIDATION; BASIN; LAKE;

D O I：

10.11999/JEIT190494

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The Yellow River is an important water resource in China. Using radar remote sensing to monitor the runoff of the Yellow River can conveniently reflect the changing trend of drought and flood, which has important practical significance. At present, Radar Altimeter (RA) commonly is used to construct a water depth-runoff model in runoff inversion. This method ignores the influence of river surface change on runoff fluctuation and has certain limitations. A Multi-source Radar Remote Sensing Runoff Calculation Model (MRRS-RCM) is proposed. In this study, RA technology and Synthetic Aperture Radar (SAR) technology are used to construct MRRS-RCM model on the basis of the Manning's equation to realize runoff inversion. Three stations are selected for experiments in the lower reaches of the Yellow River. The results show that the Relative Root Mean Square Error (RRMSE) of MRRS-RCM runoff inversion reaches 13.969%, which is better than the accuracy requirement of traditional runoff monitoring of 15%similar to 20%.

引用

页码：1590 / 1598

页数：9

共 20 条

[1] [Anonymous], 2017, THESIS
[2] [Anonymous], 2005, THESIS
[3] Validation of Jason-3 tracking modes over French rivers
Biancamaria, Sylvain
Schaedele, Thomas
Blumstein, Denis
Frappart, Frederic
Boy, Francois
Desjonqueres, Jean-Damien
Pottier, Claire
Blarel, Fabien
Nino, Fernando
[J]. REMOTE SENSING OF ENVIRONMENT, 2018, 209 : 77 - 89
[4] Brakenridge GR., 1994, Eos Trans. Am. Geophys. Union, V75, P521, DOI [DOI 10.1029/EO075I045P00521, 10.1029/EO075I045P00521.481]
[5] Chen H, 2017, J ELECTRON INF TECHN, V39, P2232, DOI 10.11999/JEIT161363
[6] Lake studies from satellite radar altimetry
Cretaux, Jean-Francois
Birkett, Charon
[J]. COMPTES RENDUS GEOSCIENCE, 2006, 338 (14-15) : 1098 - 1112
[7] Preliminary results of ENVISAT RA-2-derived water levels validation over the Amazon basin
Frappart, F
Calmant, S
Cauhopé, M
Seyler, F
Cazenave, A
[J]. REMOTE SENSING OF ENVIRONMENT, 2006, 100 (02) : 252 - 264
[8] [郭拯危 Guo Zhengwei], 2018, [国土资源遥感, Remote Sensing for Land & Resources], V30, P62
[9] Modeling of the effect of land use changes on the runoff generation of a river basin through parameter regionalization of a watershed model
Hundecha, Y
Bárdossy, A
[J]. JOURNAL OF HYDROLOGY, 2004, 292 (1-4) : 281 - 295
[10] Leng Y, 2017, J ELECTRON INF TECHN, V39, P1064, DOI 10.11999/JEIT160870

← 1 2 →