{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T19:30:40Z","timestamp":1774553440996,"version":"3.50.1"},"reference-count":93,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2020,3,26]],"date-time":"2020-03-26T00:00:00Z","timestamp":1585180800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["91747201, 41571033"],"award-info":[{"award-number":["91747201, 41571033"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["XDA20060202 and XDA19070301"],"award-info":[{"award-number":["XDA20060202 and XDA19070301"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Reliable information about river discharge plays a key role in sustainably managing water resources and better understanding of hydrological systems. Therefore, river discharge estimation using remote sensing techniques is an ongoing research goal, especially in small, headwater catchments which are mostly ungauged due to environmental or financial limitations. Here, a novel method for river discharge estimation based entirely on remote sensing-derived parameters is presented. The model inputs include average river width, estimated from Landsat imagery by using the modified normalized difference water index (MNDWI) approach; average depth and velocity, based on empirical equations with inputs from remote sensing; channel slope from a high resolution shuttle radar topography mission digital elevation model (SRTM DEM); and channel roughness coefficient via further analysis and classification of Landsat images with support of previously published values. The discharge of the Lhasa River was then estimated based on these derived parameters and by using either the Manning equation (Model 1) or Bjerklie equation (Model 2). In general, both of the two models tend to overestimate discharge at moderate and high flows, and underestimate discharge at low flows. The overall performances of both models at the Lhasa gauge were satisfactory: comparisons with the observations yielded Nash\u2013Sutcliffe efficiency coefficient (NSE) and R2 values \u2265 0.886. Both models also performed well at the upper gauge (Tanggya) of the Lhasa River (NSE \u2265 0.950) indicating the transferability of the methodology to river cross-sections with different morphologies, thus demonstrating the potential to quantify streamflow entirely from remote sensing data in poorly-gauged or ungauged rivers on the Tibetan Plateau.<\/jats:p>","DOI":"10.3390\/rs12071064","type":"journal-article","created":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T03:44:13Z","timestamp":1585712653000},"page":"1064","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Discharge Estimates for Ungauged Rivers Flowing over Complex High-Mountainous Regions based Solely on Remote Sensing-Derived Datasets"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6871-0031","authenticated-orcid":false,"given":"Mulugeta Genanu","family":"Kebede","sequence":"first","affiliation":[{"name":"Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, and CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Arba Minch Water Technology Institute, Faculty of Meteorology and Hydrology, Arba Minch University, P.O. Box 21, Arba Minch, Ethiopia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7201-8715","authenticated-orcid":false,"given":"Lei","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, and CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kun","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Earth System Science, Tsinghua University, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0288-5618","authenticated-orcid":false,"given":"Deliang","family":"Chen","sequence":"additional","affiliation":[{"name":"Regional Climate Group, Department of Earth Sciences, University of Gothenburg, P.O. Box 460, S-405 30 Gothenburg, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiuping","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, and CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tian","family":"Zeng","sequence":"additional","affiliation":[{"name":"Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, and CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhidan","family":"Hu","sequence":"additional","affiliation":[{"name":"Information Center, Ministry of Water Resources, Beijing 100053, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4527","DOI":"10.1002\/2015WR018434","article-title":"An intercomparison of remote sensing river discharge estimation algorithms from measurements of river height, width, and slope","volume":"52","author":"Durand","year":"2016","journal-title":"Water Resour. Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1068","DOI":"10.1126\/science.1128845","article-title":"Global hydrological cycles and world water resources","volume":"313","author":"Oki","year":"2006","journal-title":"Science"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1175\/1525-7541(2002)003<0660:EOFDFC>2.0.CO;2","article-title":"Estimates of freshwater discharge from continents: Latitudinal and seasonal variations","volume":"3","author":"Dai","year":"2002","journal-title":"J. Hydrometeorol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1516","DOI":"10.1016\/j.jhydrol.2014.08.044","article-title":"Assessing the potential global extent of SWOT river discharge observation","volume":"519","author":"Pavelsky","year":"2014","journal-title":"J. Hydrol."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Elmi, O., Tourian, M.J., and Sneeuw, N. (2016). Dynamic River masks from multi-temporal satellite imagery: An automatic algorithm using graph cuts optimization. Remote Sens., 8.","DOI":"10.3390\/rs8121005"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3165","DOI":"10.1002\/wrcr.20176","article-title":"Estimation of river depth from remotely sensed hydraulic relationships","volume":"49","author":"Mersel","year":"2013","journal-title":"Water Resour. Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"RG2002","DOI":"10.1029\/2006RG000197","article-title":"Measuring surface water from space","volume":"45","author":"Alsdorf","year":"2007","journal-title":"Rev. Geophys."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1220","DOI":"10.1016\/j.scitotenv.2018.05.226","article-title":"Detection of hydrological variations and their impacts on vegetation from multiple satellite observations in the Three-River Source Region of the Tibetan Plateau","volume":"639","author":"Xu","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"4145","DOI":"10.3390\/rs5094145","article-title":"River discharge estimation by using altimetry data and simplified flood routing modeling","volume":"5","author":"Tarpanelli","year":"2013","journal-title":"Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.rse.2018.10.008","article-title":"Discharge estimation in high-mountain regions with improved methods using multisource remote sensing: A case study of the Upper Brahmaputra River","volume":"219","author":"Huang","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.rse.2016.03.019","article-title":"Estimating continental river basin discharges using multiple remote sensing data sets","volume":"179","author":"Sichangi","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2773","DOI":"10.1175\/2008JCLI2592.1","article-title":"Changes in continental freshwater discharge from 1948 to 2004","volume":"22","author":"Dai","year":"2009","journal-title":"J. Clim."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"L08402","DOI":"10.1029\/2007GL029447","article-title":"Spatial and temporal complexity of the Amazon flood measured from space","volume":"34","author":"Alsdorf","year":"2007","journal-title":"Geophys. Res. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1109\/JSTARS.2013.2283402","article-title":"Proof of concept of an altimeter-based river forecasting system for transboundary flow inside Bangladesh","volume":"7","author":"Hossain","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/S0022-1694(03)00129-X","article-title":"Evaluating the potential for measuring river discharge from space","volume":"278","author":"Bjerklie","year":"2003","journal-title":"J. Hydrol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3641","DOI":"10.1002\/hyp.7518","article-title":"A data assimilation approach to discharge estimation from space","volume":"23","author":"Neal","year":"2009","journal-title":"Hydrol. Process."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"133571","DOI":"10.1016\/j.scitotenv.2019.07.377","article-title":"Streamflow calculation for medium-to-small Rivers in data scarce inland areas","volume":"693","author":"Zhao","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3322","DOI":"10.1080\/01431161.2019.1701213","article-title":"Remote sensing-based river discharge estimation for a small river flowing over the high mountain regions of the Tibetan Plateau","volume":"41","author":"Genanu","year":"2020","journal-title":"Int. J. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1427","DOI":"10.1002\/(SICI)1099-1085(199708)11:10<1427::AID-HYP473>3.0.CO;2-S","article-title":"Satellite remote sensing of river inundation area, stage, and discharge: A review","volume":"11","author":"Smith","year":"1997","journal-title":"Hydrol. Process."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1109\/JSTARS.2009.2033453","article-title":"Estimating river depth from remote sensing swath interferometry measurements of river height, slope, and width","volume":"3","author":"Durand","year":"2010","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1016\/j.scib.2019.03.015","article-title":"New methods designed to estimate the daily discharges of rivers in the Tibetan Plateau","volume":"64","author":"Wang","year":"2019","journal-title":"Sci. Bull."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Yang, S., Wang, J., Wang, P., Gong, T., and Liu, H. (2019). Low Altitude Unmanned Aerial Vehicles (UAVs) and Satellite Remote Sensing Are Used to Calculated River Discharge Attenuation Coefficients of Ungauged Catchments in Arid Desert. Water, 11.","DOI":"10.3390\/w11122633"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Koutalakis, P., Tzoraki, O., and Zaimes, G. (2019). UAVs for hydrologic scopes: Application of a low-cost UAV to estimate surface water velocity by using three different image-based methods. Drones, 3.","DOI":"10.3390\/drones3010014"},{"key":"ref_24","unstructured":"Gentile, V., Mr\u00f3z, M., and Spitoni, M. (2016, January 10). Bathymetric mapping of shallow rivers with UAV hyperspectral data. Proceedings of the 5th International Conference on Telecommunications and Remote Sensing, Milan, Italy."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"C12013","DOI":"10.1029\/2009JC006075","article-title":"Satellite altimeter-derived monthly discharge of the Ganga-Brahmaputra River and its seasonal to interannual variations from 1993 to 2008","volume":"115","author":"Papa","year":"2010","journal-title":"J. Geophys. Res."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"W03427","DOI":"10.1029\/2007WR006133","article-title":"Estimation of river discharge, propagation speed, and hydraulic geometry from space: Lena River, Siberia","volume":"44","author":"Smith","year":"2008","journal-title":"Water Resour. Res."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.rse.2012.11.013","article-title":"Upstream satellite remote sensing for river discharge forecasting: Application to major rivers in South Asia","volume":"131","author":"Hirpa","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.marpolbul.2012.01.043","article-title":"Fine sediment and nutrient dynamics related to particle size and floc formation in a Burdekin river flood plume, Australia","volume":"65","author":"Bainbridge","year":"2012","journal-title":"Mar. Pollut. Bull."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1325","DOI":"10.1029\/95WR00145","article-title":"Estimation of discharge from braided glacial Rivers using ERS 1 synthetic aperture radar: First results","volume":"31","author":"Smith","year":"1995","journal-title":"Water Resour. Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2021","DOI":"10.1029\/96WR00752","article-title":"Estimation of discharge from three braided rivers using synthetic aperture radar satellite imagery: Potential application to ungaged basins","volume":"32","author":"Smith","year":"1996","journal-title":"Water Resour. Res."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"4631","DOI":"10.1029\/2001GL013263","article-title":"Remote sensing of global wetland dynamics with multiple satellite data sets","volume":"28","author":"Prigent","year":"2001","journal-title":"Geophys. Res. Lett."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1029\/2005EO190001","article-title":"Space-based measurement of river runoff","volume":"86","author":"Brakenridge","year":"2005","journal-title":"Eos Trans. Am. Geophys. Union"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Papa, F., Prigent, C., Durand, F., and Rossow, W.B. (2006). Wetland dynamics using a suite of satellite observations: A case study of application and evaluation for the Indian Subcontinent. Geophys. Res. Lett., 33.","DOI":"10.1029\/2006GL025767"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1109\/TGRS.2010.2057513","article-title":"Satellite Remote Sensing and Hydrologic Modeling for Flood Inundation Mapping in Lake Victoria Basin: Implications for Hydrologic Prediction in Ungauged Basins","volume":"49","author":"Khan","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/j.jhydrol.2004.11.022","article-title":"Estimating discharge in rivers using remotely sensed hydraulic information","volume":"309","author":"Bjerklie","year":"2005","journal-title":"J. Hydrol."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Brakenridge, G.R., Nghiem, S.V., Anderson, E., and Mic, R. (2007). Orbital microwave measurement of river discharge and ice status. Water Resour. Res., 43.","DOI":"10.1029\/2006WR005238"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1029\/2012EO450006","article-title":"Developing new algorithms for estimating river discharge from space","volume":"93","author":"Pavelsky","year":"2012","journal-title":"Eos Trans. Am. Geophys. Union"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1593","DOI":"10.1080\/02626667.2013.852278","article-title":"Remotely sensed estimation of water discharge in to the rapidly dwindling Dead Sea","volume":"59","author":"Vachtman","year":"2014","journal-title":"Hydrol. Sci. J."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1016\/j.scitotenv.2018.10.279","article-title":"Improved remotely sensed satellite products for studying Lake Victoria\u2019s water storage changes","volume":"652","author":"Khaki","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"4174","DOI":"10.1002\/wrcr.20348","article-title":"A quantile function approach to discharge estimation from satellite altimetry (ENVISAT)","volume":"49","author":"Tourian","year":"2013","journal-title":"Water Resour. Res."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"L20401","DOI":"10.1029\/2008GL034150","article-title":"Estimation of bathymetric depth and slope from data assimilation of swath altimetry into a hydrodynamic model","volume":"35","author":"Durand","year":"2008","journal-title":"Geophys. Res. Lett."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1109\/LGRS.2007.908305","article-title":"RivWidth: A software tool for the calculation of river widths from remotely sensed imagery","volume":"5","author":"Pavelsky","year":"2008","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.jhydrol.2009.09.049","article-title":"Hydrological monitoring of poorly gauged basins based on rainfall-runoff modeling and spatial altimetry","volume":"379","author":"Getirana","year":"2009","journal-title":"J. Hydrol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/j.jhydrol.2010.04.013","article-title":"Integrating spatial altimetry data into the automatic calibration of hydrological models","volume":"387","author":"Getirana","year":"2010","journal-title":"J. Hydrol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2011","DOI":"10.5194\/hess-14-2011-2010","article-title":"Towards improving river discharge estimation in ungauged basins: Calibration of rainfall-runoff models based on satellite observations of river flow width at basin outlet","volume":"14","author":"Sun","year":"2010","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"872","DOI":"10.1002\/hyp.8301","article-title":"Prospects for calibrating rainfall-runoff models using satellite observations of river hydraulic variables as surrogates for in situ river discharge measurements","volume":"26","author":"Sun","year":"2012","journal-title":"Hydrol. Process."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"3524","DOI":"10.1002\/hyp.8429","article-title":"Calibration of hydrological models in ungauged basins based on satellite radar altimetry observations of river water level","volume":"26","author":"Sun","year":"2012","journal-title":"Hydrol. Process."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1729","DOI":"10.5194\/hess-15-1729-2011","article-title":"Combining satellite radar altimetry, SAR surface soil moisture and GRACE total storage changes for hydrological model calibration in a large poorly gauged catchment","volume":"15","author":"Milzow","year":"2011","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1029\/2018RG000598","article-title":"Detecting, extracting, and monitoring surface water from space using optical sensors: A review","volume":"56","author":"Huang","year":"2018","journal-title":"Rev. Geophys."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Acharya, T., Subedi, A., and Lee, D. (2018). Evaluation of water indices for surface water extraction in a Landsat 8 scene of Nepal. Sensors, 18.","DOI":"10.3390\/s18082580"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Du, Y., Zhang, Y., Ling, F., Wang, Q., Li, W., and Li, X. (2016). Water bodies\u2019 mapping from Sentinel-2 Imagery with Modified Normalized Difference Water Index at 10-m Spatial Resolution Produced by Sharpening the SWIR Band. Remote Sens., 8.","DOI":"10.3390\/rs8040354"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Donchyts, G., Schellekens, J., Winsemius, H., Eisemann, E., and van de Giesen, N. (2016). A 30 m resolution surface water mask including estimation of positional and thematic differences using Landsat 8, SRTM and OpenStreetMap: A case study in the Murray-Darling Basin, Australia. Remote Sens., 8.","DOI":"10.3390\/rs8050386"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"5067","DOI":"10.3390\/rs6065067","article-title":"An automated method for extracting Rivers and Lakes from Landsat imagery","volume":"6","author":"Jiang","year":"2014","journal-title":"Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/0034-4257(85)90102-6","article-title":"A TM Tasseled Cap equivalent transformation for reflectance factor data","volume":"17","author":"Crist","year":"1985","journal-title":"Remote Sens. Environ."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1425","DOI":"10.1080\/01431169608948714","article-title":"The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features","volume":"17","author":"McFeeters","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"3025","DOI":"10.1080\/01431160600589179","article-title":"Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery","volume":"27","author":"Xu","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.rse.2013.08.029","article-title":"Automated water extraction index: A new technique for surface water mapping using Landsat imagery","volume":"140","author":"Feyisa","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1307","DOI":"10.14358\/PERS.75.11.1307","article-title":"Analysis of dynamic thresholds for the normalized difference water index","volume":"75","author":"Ji","year":"2009","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1016\/j.rse.2013.03.010","article-title":"Estimating water volume variations in lakes and reservoirs from four operational satellite altimetry databases and satellite imagery data","volume":"134","author":"Duan","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"3596","DOI":"10.1002\/hyp.9469","article-title":"Remote sensing of river stage using the cross-sectional inundation area\u2014River stage relationship (IARSR) constructed from digital elevation model data","volume":"27","author":"Pan","year":"2013","journal-title":"Hydrol. Process."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"670","DOI":"10.1016\/j.jhydrol.2016.06.024","article-title":"Constructing river stage-discharge rating curves using remotely sensed river cross sectional inundation areas and river bathymetry","volume":"540","author":"Pan","year":"2016","journal-title":"J. Hydrol."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Sichangi, A.W., Wang, L., and Hu, Z. (2018). Estimation of River Discharge Solely from Remote-Sensing Derived Data: An Initial Study Over the Yangtze River. Remote Sens., 10.","DOI":"10.3390\/rs10091385"},{"key":"ref_63","unstructured":"Prasch, M. (2010). Distributed Process Oriented Modelling of the Future Impact of Glacier Melt Water on Runoff in the Lhasa River Basin in Tibet. [Ph.D. Thesis, Dissertation An Der Fakult\u00e4t F\u00fcr Geowissenschaften Der Ludwig-Maximilians-Universit\u00e4t]."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Wu, X., Li, Z., Gao, P., Huang, C., and Hu, T. (2018). Response of the downstream braided channel to Zhikong reservoir on Lhasa River. Water, 10.","DOI":"10.3390\/w10091144"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1007\/s11442-008-0095-4","article-title":"The trend on runoff variations in the Lhasa River Basin","volume":"18","author":"Lin","year":"2008","journal-title":"J. Geogr. Sci."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"889","DOI":"10.5194\/tc-7-889-2013","article-title":"Quantifying present and future glacier melt-water contribution to runoff in a central Himalayan river basin","volume":"7","author":"Prasch","year":"2013","journal-title":"Cryosphere"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Peng, D., and Du, Y. (2010, January 18\u201320). Comparative analysis of several Lhasa River basin flood forecast models in Yarlung Zangbo River. Proceedings of the 4th International Conference on Bioinformatics and Biomedical Engineering, Chengdu, China.","DOI":"10.1109\/ICBBE.2010.5515463"},{"key":"ref_68","first-page":"157","article-title":"Hydrological characteristics of Yarlungzangbo River","volume":"54","author":"Liu","year":"1999","journal-title":"Acta Geogr. Sin."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"782","DOI":"10.1016\/j.jhydrol.2016.10.050","article-title":"Quantitative drought monitoring in a typical cold river basin over Tibetan Plateau: An integration of meteorological, agricultural and hydrological droughts","volume":"543","author":"Makokha","year":"2016","journal-title":"J. Hydrol."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Li, Y., Zhang, Q., Liu, X., and Yao, J. (2019). Water balance and flashiness for a large floodplain system: A case study of Poyang Lake, China. Sci. Total Environ., 135499.","DOI":"10.1016\/j.scitotenv.2019.135499"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"5194","DOI":"10.1080\/01431161.2012.657370","article-title":"An automated scheme for glacial lake dynamics mapping using Landsat imagery and digital elevation models: A case study in the Himalayas","volume":"33","author":"Li","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","article-title":"A Threshold Selection Method from Gray-Level Histograms","volume":"9","author":"Otsu","year":"1979","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_73","first-page":"5070","article-title":"Hydraulic characterization of the middle reach of the Congo River","volume":"49","author":"Trigg","year":"2013","journal-title":"Water Resour. Res."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"3467","DOI":"10.1002\/2013WR014664","article-title":"Development of the global width database for large rivers","volume":"50","author":"Yamazaki","year":"2014","journal-title":"Water Resour. Res."},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"LeFavour, G., and Alsdorf, D. (2005). Water slope and discharge in the Amazon River estimated using the shuttle radar topography mission digital elevation model. Geophys. Res. Lett., 32.","DOI":"10.1029\/2005GL023836"},{"key":"ref_76","unstructured":"Coon, W.F. (1998). Estimation of Roughness Coefficients for Natural Stream Channels with Vegetated Banks."},{"key":"ref_77","unstructured":"Chow, V.T. (1959). Open Channel Hydraulics, McGraw-Hill."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1006\/jare.1997.0314","article-title":"Comparison of methods for measuring woody riparian vegetation density","volume":"38","author":"Dudley","year":"1998","journal-title":"J. Arid Environ."},{"key":"ref_79","first-page":"473","article-title":"Estimating hydraulic roughness coefficients","volume":"37","author":"Cowan","year":"1956","journal-title":"Agric. Eng."},{"key":"ref_80","unstructured":"Albertson, M.L., and Simons, D.B. (1964). Fluid Mechanics. Handbook of Applied Hydrology: A Compendium of Water-Resources Technology, McGraw-Hill."},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Bjerklie, D.M. (2007). Estimating the bankfull velocity and discharge for rivers using remotely sensed river morphology information. J. Hydrol., 144\u2013155.","DOI":"10.1016\/j.jhydrol.2007.04.011"},{"key":"ref_82","doi-asserted-by":"crossref","unstructured":"Tourian, M.J., Elmi, O., Mohammadnejad, A., and Sneeuw, N. (2017). Estimating river depth from SWOT-Type observables obtained by satellite altimetry and imagery. Water, 9.","DOI":"10.3390\/w9100753"},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"341","DOI":"10.5194\/hess-19-341-2015","article-title":"Satellite radar altimetry for monitoring small rivers and lakes in Indonesia","volume":"19","author":"Sulistioadi","year":"2015","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_84","first-page":"161","article-title":"On the flow of water in open channels and pipes","volume":"20","author":"Manning","year":"1891","journal-title":"Trans. Inst. Civ. Eng. Irel."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"1140","DOI":"10.1002\/2015WR017654","article-title":"Spatiotemporal densification of river water level time series by multimission satellite altimetry","volume":"52","author":"Tourian","year":"2016","journal-title":"Water Resour. Res."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1139\/l88-109","article-title":"Uncertainties in the single determination of river discharge: A literature review","volume":"15","author":"Pelletier","year":"1988","journal-title":"Can. J. Civ. Eng."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"739","DOI":"10.1080\/02626660009492374","article-title":"Rating curve modelling with Manning\u2019s equation to manage instability and improve extrapolation","volume":"45","author":"Leonard","year":"2000","journal-title":"Hydrol. Sci. J."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/S0955-5986(02)00047-X","article-title":"The uncertainty in a current meter measurement","volume":"13","author":"Herschy","year":"2002","journal-title":"Flow Meas. Instrum."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1002\/hyp.9567","article-title":"Uncertainty in streamflow rating curves: Methods, controls and consequences","volume":"28","author":"Tomkins","year":"2014","journal-title":"Hydrol. Process."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.envsoft.2014.09.011","article-title":"Streamflow rating uncertainty: Characterisation and impacts on model calibration and performance","volume":"63","author":"Zhang","year":"2015","journal-title":"Environ. Model. Softw."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"2049","DOI":"10.5194\/hess-15-2049-2011","article-title":"Estimating river discharge from earth observation measurements of river surface hydraulic variables","volume":"15","author":"Negrel","year":"2011","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"3811","DOI":"10.1002\/hyp.7811","article-title":"Using satellite altimetry data to augment flow estimation techniques on the Mekong River","volume":"24","author":"Birkinshaw","year":"2010","journal-title":"Hydrol. Process."},{"key":"ref_93","unstructured":"Abolfazl, M. (2017). Estimation of River Discharge from Spaceborne Observations: Assessment of Different Models. [Master\u2019s Thesis, University of Stuttgart]."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/7\/1064\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:11:47Z","timestamp":1760173907000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/7\/1064"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,26]]},"references-count":93,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2020,4]]}},"alternative-id":["rs12071064"],"URL":"https:\/\/doi.org\/10.3390\/rs12071064","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,26]]}}}