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River discharge estimation based on remote sensing |
LI Hemou1,2,3( ), BAI Juan3, GAN Fuping3(), LI Xianqing1,2, WANG Zekun1,2,3 |
1. State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology(Beijing), Beijing 100083, China
2. College of Geoscience and Surveying Engineering, China University of Mining and Technology(Beijing), Beijing 100083, China
3. China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China |
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Abstract Since the availability of global runoff data decrease year by year, the inversion algorithms, as substitutes for the river discharge measured at hydrological stations, have become increasingly important. With the continuous development of satellite remote sensing technology, the methods for estimating river discharge have increased in number. This study systematically summarized the remote sensing-based inversion methods for river discharge, as well as the inversion methods for hydraulic remote sensing elements that are closely related to the estimation of river discharge and the progress made in them. Moreover, this study reviewed the methods, principles, and application status of two types of algorithms based on hydrological models and empirical regression equations and summarized the applicable conditions and shortcomings of different methods. Finally, this study predicted the worldwide development trends of the river discharge inversion based on the satellite remote sensing technology, including ① actively developing the advanced data assimilation technology for satellite remote sensing data; ② integrating new sensor products; ③ optimizing and innovating algorithms.
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| Keywords
river discharge
remote sensing
water level
river width
hydraulic characteristics
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Issue Date: 07 July 2023
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| [1] |
Ramanathan V, Crutzen P J, Kiehl J T, et al. Aerosols,climate, and the hydrological cycle[J]. Science, 2001, 294(5549):2119-2124.
doi: 10.1126/science.1064034
pmid: 11739947
|
| [2] |
Deangelis A M, Qu X, Zelinka M, et al. An observational radiative constraint on hydrologic cycle intensification[J]. Nature, 2015, 528(7581):249-253.
doi: 10.1038/nature15770
|
| [3] |
Li Y, Piao S, Li L Z, et al. Divergent hydrological response to large-scale afforestation and vegetation greening in China[J]. Science Advances, 2018, 4(5):eaar4182.
doi: 10.1126/sciadv.aar4182
url: https://www.science.org/doi/10.1126/sciadv.aar4182
|
| [4] |
Yang S, Wang P, Lou H, et al. Estimating river discharges in ungauged catchments using the slope-area method and unmanned aerial vehicle[J]. Water, 2019, 11(11):2361.
doi: 10.3390/w11112361
url: https://www.mdpi.com/2073-4441/11/11/2361
|
| [5] |
Fekete B M, Vrsmarty C J. The current status of global river discharge monitoring and potential new technologies complementing traditional discharge measurements[C]// Proceeding of Predictions in Ungauged Basins. 2007, 309(20):129-136.
|
| [6] |
Gleason C J, Durand M T. Remote sensing of river discharge:A review and a framing for the discipline[J]. Remote Sensing, 2020, 12(7):1107.
doi: 10.3390/rs12071107
url: https://www.mdpi.com/2072-4292/12/7/1107
|
| [7] |
Smith L C, Yang K, Pitcher L H, et al. Direct measurements of meltwater runoff on the Greenland ice sheet surface[C]// Proceedings of the National Academy of Sciences of the United States of America, 2017, 114(50):e10622-e10631.
|
| [8] |
陈晓宏, 钟睿达, 王兆礼, 等. 新一代GPM IMERG卫星遥感降水数据在中国南方地区的精度及水文效用评估[J]. 水利学报, 2017, 48(10):1147-1156.
|
| [8] |
Chen X H, Zhong R D, Wang Z L, et al. Evaluation on the accuracy and hydrological performance of the latest-generation GPM IMERG product over South China[J]. Journal of Hydraulic Engineering, 2017, 48(10):1147-1156.
|
| [9] |
王兆礼, 钟睿达, 赖成光, 等. TRMM卫星降水反演数据在珠江流域的适用性研究——以东江和北江为例[J]. 水科学进展, 2017, 28(2):174-182.
|
| [9] |
Wang Z L, Zhong R D, Lai C G, et al. Evaluation of TRMM 3B42-V7 satellite-based precipitation data product in the Pearl River basin,China:Dongjiang River and Beijiang River basin as examples[J]. Advances in Water Science, 2017, 28(2):174-182.
|
| [10] |
Sheffield J, Wood E F, Pan M, et al. Satellite remote sensing for water resources management:Potential for supporting sustainable development in data-poor regions[J]. Water Resources Research, 2018, 54(12):9724-9758.
doi: 10.1029/2017WR022437
url: https://onlinelibrary.wiley.com/doi/abs/10.1029/2017WR022437
|
| [11] |
周启鸣, 李剑锋, 崔爱红, 等. 中亚干旱区陆地水资源评估方法与挑战[J]. 水文, 2021, 41(1):15-21,72.
|
| [11] |
Zhou Q M, Li J F, Cui A H, et al. The state-of-the-art and prospective of terrestrial water resource assessment in central Asia arid zone[J]. Journal of China Hydrology, 2021, 41(1):15-21,72.
|
| [12] |
Alsdorf D E. Tracking freshwater from space[J]. Science, 2003, 301(5639):1098-1112.
|
| [13] |
Bjerklie D M, Ayotte J D, Cahillane M J. Simulating hydrologic response to climate change scenarios in four selected watersheds of New Hampshire[R]. US Geological Survey Scientific Investigations Report: Reston, VA,USA, 2015.
|
| [14] |
杨胜天, 王鹏飞, 王娟, 等. 结合无人机航空摄影测量的河道流量估算[J]. 遥感学报, 2021, 25(6):1284-1293.
|
| [14] |
Yang S T, Wang P F, Wang J, et al. River flow estimation method based on UAV aerial photogrammetry[J]. Journal of Remote Sensing, 2021, 25(6):1284-1293.
|
| [15] |
Güntner A. Improvement of global hydrological models using GRACE data[J]. Surveys in Geophysics, 2008, 29(4):375-397.
doi: 10.1007/s10712-008-9038-y
url: http://link.springer.com/10.1007/s10712-008-9038-y
|
| [16] |
Li Q, Zhong B, Luo Z, et al. GRACE-based estimates of water discharge over the Yellow River basin[J]. Geodesy and Geodynamics, 2016, 7(3):187-193.
doi: 10.1016/j.geog.2016.04.007
url: https://linkinghub.elsevier.com/retrieve/pii/S1674984716300271
|
| [17] |
Simons G, Bastiaanssen W, Ngo L A, et al. Integrating global satellite-derived data products as a pre-analysis for hydrological modelling studies:A case study for the Red River basin[J]. Remote Sensing, 2016, 8(4):279.
doi: 10.3390/rs8040279
url: http://www.mdpi.com/2072-4292/8/4/279
|
| [18] |
Laiolo P, Gabellani S, Campo L, et al. Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model[J]. International Journal of Applied Earth Observation and Geoinformation, 2016, 48:131-145.
doi: 10.1016/j.jag.2015.06.002
url: https://linkinghub.elsevier.com/retrieve/pii/S0303243415001312
|
| [19] |
Zhang D, Liu X, Bai P, et al. Suitability of satellite-based precipitation products for water balance simulations using multiple observations in a humid catchment[J]. Remote Sensing, 2019, 11(2):151.
doi: 10.3390/rs11020151
url: http://www.mdpi.com/2072-4292/11/2/151
|
| [20] |
Kittel C M, Arildsen A L, Dybkjae S, et al. Informing hydrological models of poorly gauged river catchments:A parameter regionalization and calibration approach[J]. Journal of Hydrology, 2020, 587:124999.
doi: 10.1016/j.jhydrol.2020.124999
url: https://linkinghub.elsevier.com/retrieve/pii/S0022169420304595
|
| [21] |
Getirana A C V, Boone A, Yamazaki D, et al. Automatic parameterization of a flow routing scheme driven by Radar altimetry data:Evaluation in the Amazon basin[J]. Water Resources Research, 2013, 49(1):614-629.
doi: 10.1002/wrcr.20077
url: http://doi.wiley.com/10.1002/wrcr.20077
|
| [22] |
Liu G, Schwartz F W, Tseng K H, et al. Discharge and water-depth estimates for ungauged rivers:Combining hydrologic,hydraulic,and inverse modeling with stage and water-area measurements from satellites[J]. Water Resources Research, 2015, 51(8):6017-6035.
doi: 10.1002/2015WR016971
url: http://doi.wiley.com/10.1002/2015WR016971
|
| [23] |
Sun W, Fan J, Wang G, et al. Calibrating a hydrological model in a regional river of the Qinghai-Tibet Plateau using river water width determined from high spatial resolution satellite images[J]. Remote Sensing of Environment, 2018, 214:100-114.
doi: 10.1016/j.rse.2018.05.020
url: https://linkinghub.elsevier.com/retrieve/pii/S0034425718302414
|
| [24] |
Wongchuig-Correa S, de Paiva R C D, Biancamaria S, et al. Assimilation of future SWOT-based river elevations,surface extent observations and discharge estimations into uncertain global hydrological models[J]. Journal of Hydrology, 2020, 590:125473.
doi: 10.1016/j.jhydrol.2020.125473
url: https://linkinghub.elsevier.com/retrieve/pii/S0022169420309331
|
| [25] |
Huang Q, Long D, Du M, et al. Daily continuous river discharge estimation for ungauged basins using a hydrologic model calibrated by satellite altimetry:Implications for the SWOT mission[J]. Water Resources Research, 2020, 56(7):e2020WR027309.
|
| [26] |
Leopold L B, Maddock T. The hydraulic geometry of stream channels and some physiographic implications[M]. Washington D C: US Government Printing Office, 1953.
|
| [27] |
Kouraev A V, Zakharova E A, Samain O, et al. Ob’river discharge from TOPEX/Poseidon satellite altimetry (1992—2002)[J]. Remote Sensing of Environment, 2004, 93(1-2):238-245.
doi: 10.1016/j.rse.2004.07.007
url: https://linkinghub.elsevier.com/retrieve/pii/S0034425704002184
|
| [28] |
Zakharova E A, Kouraev A V, Cazenave A, et al. Amazon River discharge estimated from TOPEX/Poseidon altimetry[J]. Comptes Rendus Geoscience, 2006, 338(3):188-196.
doi: 10.1016/j.crte.2005.10.003
url: https://linkinghub.elsevier.com/retrieve/pii/S1631071305003226
|
| [29] |
Zakharova E A, Krylenko I N, Kouraev A V. Use of non-polar orbiting satellite Radar altimeters of the Jason series for estimation of river input to the Arctic Ocean[J]. Journal of Hydrology, 2019, 568:322-333.
doi: 10.1016/j.jhydrol.2018.10.068
|
| [30] |
Birkinshaw S J, O’Donnell G M, Moore P, et al. Using satellite altimetry data to augment flow estimation techniques on the Mekong River[J]. Hydrological Processes, 2010, 24(26):3811-3825.
doi: 10.1002/hyp.v24.26
url: http://doi.wiley.com/10.1002/hyp.v24.26
|
| [31] |
Papa F, Bala S K, Pandey R K, et al. Ganga-Brahmaputra River discharge from Jason-2 Radar altimetry:An update to the long-term satellite-derived estimates of continental freshwater forcing flux into the bay of Bengal[J]. Journal of Geophysical Research:Oceans, 2012, 117(c11):c11021.
|
| [32] |
Papa F, Durand F, Rossow W B, et al. Satellite altimeter-derived monthly discharge of the Ganga-Brahmaputra River and its seasonal to interannual variations from 1993 to 2008[J]. Journal of Geophysical Research, 2010, 115(c12):c12013.
|
| [33] |
Junqueira A M, Mao F, Mendes T S G, et al. Estimation of river flow using CubeSats remote sensing[J]. Science of the Total Environment, 2021, 788:147762.
doi: 10.1016/j.scitotenv.2021.147762
url: https://linkinghub.elsevier.com/retrieve/pii/S0048969721028333
|
| [34] |
Smith L C, Isacks B L, Bloom A L, et al. Estimation of discharge from three braided rivers using synthetic aperture Radar satellite imagery:Potential application to ungaged basins[J]. Water Resources Research, 1996, 32(7):2021-2034.
doi: 10.1029/96WR00752
url: http://doi.wiley.com/10.1029/96WR00752
|
| [35] |
Smith L C, Isacks B L, Forster R R, et al. Estimation of discharge from braided glacial rivers using ERS 1 synthetic aperture Radar:First results[J]. Water Resources Research, 1995, 31(5):1325-1329.
doi: 10.1029/95WR00145
url: http://doi.wiley.com/10.1029/95WR00145
|
| [36] |
Smith L C, Pavelsky T M. Estimation of river discharge,propagation speed,and hydraulic geometry from space:Lena River,Siberia[J]. Water Resources Research, 2008, 44(3):W03247.
|
| [37] |
Pavelsky T M. Using width-based rating curves from spatially discontinuous satellite imagery to monitor river discharge[J]. Hydrological Processes, 2014, 28(6):3035-3040.
|
| [38] |
Elmi O, Tourian M J, Sneeuw N. River discharge estimation using channel width from satellite imagery[C]// Proceedings of the Geoscience and Remote Sensing Symposium, 2015:727-730.
|
| [39] |
Brakenridge G R, Nghiem S V, Anderson E, et al. Orbital microwave measurement of river discharge and ice status[J]. Water Resources Research, 2007, 43(4):W04405.
|
| [40] |
Tarpanelli A, Brocca L, Lacava T, et al. Toward the estimation of river discharge variations using MODIS data in ungauged basins[J]. Remote Sensing of Environment, 2013, 136:47-55.
doi: 10.1016/j.rse.2013.04.010
url: https://linkinghub.elsevier.com/retrieve/pii/S0034425713001375
|
| [41] |
Tarpanelli A, Amarnath G, Brocca L, et al. Discharge estimation and forecasting by MODIS and altimetry data in Niger-Benue River[J]. Remote Sensing of Environment, 2017, 195:96-106.
doi: 10.1016/j.rse.2017.04.015
url: https://linkinghub.elsevier.com/retrieve/pii/S0034425717301657
|
| [42] |
Revilla-Romero B, Thielen J, Salamon P, et al. Evaluation of the satellite-based global flood detection system for measuring river discharge:Influence of local factors[J]. Hydrology and Earth System Sciences, 2014, 18(11):4467-4484.
doi: 10.5194/hess-18-4467-2014
url: https://hess.copernicus.org/articles/18/4467/2014/
|
| [43] |
许继军, 屈星, 曾子悦, 等. 基于高精度遥感亮温的典型流域河道径流模拟分析[J]. 水科学进展, 2021, 32(6):877-889.
|
| [43] |
Xu J J, Qu X, Zeng Z Y, et al. River runoff simulation and analysis for typical basins based on high- resolution brightness temperature observations[J]. Advances in Water Science, 2021, 32(6):877-889.
|
| [44] |
Van Dijk A I, Brakenridge G R, Kettner A J, et al. River gauging at global scale using optical and passive microwave remote sensing[J]. Water Resources Research, 2016, 52(8):6404-6418.
doi: 10.1002/wrcr.v52.8
url: https://onlinelibrary.wiley.com/toc/19447973/52/8
|
| [45] |
Kim S, Sharma A. The role of floodplain topography in deriving basin discharge using passive microwave remote sensing[J]. Water Resources Research, 2019, 55(2):1707-1716.
doi: 10.1029/2018WR023627
url: https://onlinelibrary.wiley.com/doi/10.1029/2018WR023627
|
| [46] |
Li H, Li H, Wang J, et al. Extending the ability of near-infrared images to monitor small river discharge on the northeastern Tibetan Plateau[J]. Water Resources Research, 2019, 55(11):8404-8421.
doi: 10.1029/2018WR023808
url: https://onlinelibrary.wiley.com/doi/10.1029/2018WR023808
|
| [47] |
Gleason C J, Smith L C. Toward global mapping of river discharge using satellite images and at-many-stations hydraulic geometry[C]// Proceedings of the National Academy of Sciences of the United States of America, 2014, 111(13):4788.
|
| [48] |
Gleason C J, Smith L C, Lee J. Retrieval of river discharge solely from satellite imagery and at-many-stations hydraulic geometry:Sensitivity to river form and optimization parameters[J]. Water Resources Research, 2014, 50(12):9604-9619.
doi: 10.1002/wrcr.v50.12
url: https://onlinelibrary.wiley.com/toc/19447973/50/12
|
| [49] |
Rao K D, Shravya A, Dadhwal V. A novel method of satellite based river discharge estimation using river hydraulic geometry through genetic algorithm technique[J]. Journal of Hydrology, 2020, 589:125361.
doi: 10.1016/j.jhydrol.2020.125361
url: https://linkinghub.elsevier.com/retrieve/pii/S0022169420308210
|
| [50] |
Mengen D, Ottinger M, Leinenkugel P, et al. Modeling river discharge using automated river width measurements derived from Sentinel-1 time series[J]. Remote Sensing, 2020, 12(19):3236.
doi: 10.3390/rs12193236
url: https://www.mdpi.com/2072-4292/12/19/3236
|
| [51] |
Hagemann M W, Gleason C J, Durand M T. BAM:Bayesian AMHG-manning inference of discharge using remotely sensed stream width,slope,and height[J]. Water Resources Research, 2017, 53(11):9692-9707.
doi: 10.1002/wrcr.v53.11
url: https://onlinelibrary.wiley.com/toc/19447973/53/11
|
| [52] |
Bjerklie D M, Lawrence D S, Vorosmarty C J, et al. Evaluating the potential for measuring river discharge from space[J]. Journal of Hydrology, 2003, 278(1-4):17-38.
doi: 10.1016/S0022-1694(03)00129-X
url: https://linkinghub.elsevier.com/retrieve/pii/S002216940300129X
|
| [53] |
Birkinshaw S J, Moore P, Kilsby C G, et al. Daily discharge estimation at ungauged river sites using remote sensing[J]. Hydrological Processes, 2012, 28(3):1043-1054.
doi: 10.1002/hyp.v28.3
url: http://doi.wiley.com/10.1002/hyp.v28.3
|
| [54] |
Bjerklie D M, Birkett C M, Jones J W, et al. Satellite remote sensing estimation of river discharge:Application to the Yukon River Alaska[J]. Journal of Hydrology, 2018, 561:1000-1018.
doi: 10.1016/j.jhydrol.2018.04.005
url: https://linkinghub.elsevier.com/retrieve/pii/S0022169418302464
|
| [55] |
Sichangi A W, Wang L, Yang K, et al. Estimating continental river basin discharges using multiple remote sensing data sets[J]. Remote Sensing of Environment, 2016, 179:36-53.
doi: 10.1016/j.rse.2016.03.019
url: https://linkinghub.elsevier.com/retrieve/pii/S0034425716301110
|
| [56] |
Huang Q, Long D, Du M, et al. An improved approach to monitoring Brahmaputra River water levels using retracked altimetry data[J]. Remote Sensing of Environment, 2018, 211:112-128.
doi: 10.1016/j.rse.2018.04.018
url: https://linkinghub.elsevier.com/retrieve/pii/S0034425718301731
|
| [57] |
Kebede M G, Wang L, Yang K, et al. Discharge estimates for ungauged rivers flowing over complex high-mountainous regions based solely on remote sensing-derived datasets[J]. Remote Sensing, 2020, 12(7):1064.
doi: 10.3390/rs12071064
url: https://www.mdpi.com/2072-4292/12/7/1064
|
| [58] |
Garambois P A, Monnier J. Inferrence of effective river properties from remotely sensed observations of water surface[J]. Advances in Water Resources, 2015, 79:103-120.
doi: 10.1016/j.advwatres.2015.02.007
url: https://linkinghub.elsevier.com/retrieve/pii/S0309170815000330
|
| [59] |
Yang S, Li C, Lou H, et al. Performance of an unmanned aerial vehicle (UAV) in calculating the flood peak discharge of ephemeral rivers combined with the incipient motion of moving stones in arid ungauged regions[J]. Remote Sensing, 2020, 12(10):1610.
doi: 10.3390/rs12101610
url: https://www.mdpi.com/2072-4292/12/10/1610
|
| [60] |
Wufu A, Chen Y, Yang S, et al. Changes in glacial meltwater runoff and its response to climate change in the Tianshan region detected using unmanned aerial vehicles (UAVs) and satellite remote sensing[J]. Water, 2021, 13(13):1753.
doi: 10.3390/w13131753
url: https://www.mdpi.com/2073-4441/13/13/1753
|
| [61] |
Thakur P K, Nikam B R, Garg V, et al. Hydrological parameters estimation using remote sensing and GIS for Indian region:A review[C]// Proceedings of the National Academy of Sciences India Section A: Physical Sciences, 2017, 87(4):641-659.
|
| [62] |
Turnipseed D P, Sauer V B. Discharge measurements at gaging stations[R]. US Geological Survey, 2010.
|
| [63] |
Romeiser R, Runge H, Suchandt S, et al. Current measurements in rivers by spaceborne along-track InSAR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2007, 45(12):4019-4031.
doi: 10.1109/TGRS.2007.904837
url: http://ieeexplore.ieee.org/document/4378563/
|
| [64] |
Romeiser R, Suchandt S, Runge H, et al. First analysis of TerraSAR-X along-track InSAR-derived current fields[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(2):820-829.
doi: 10.1109/TGRS.2009.2030885
url: http://ieeexplore.ieee.org/document/5299033/
|
| [65] |
Kaab A, Leprince S. Motion detection using near-simultaneous satellite acquisitions[J]. Remote Sensing of Environment, 2014, 154:164-179.
doi: 10.1016/j.rse.2014.08.015
url: https://linkinghub.elsevier.com/retrieve/pii/S0034425714003125
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2023,
Vol. 35
