{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T10:07:38Z","timestamp":1768990058348,"version":"3.49.0"},"reference-count":82,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2022,8,18]],"date-time":"2022-08-18T00:00:00Z","timestamp":1660780800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100012046","name":"Vietnam Academy of Science and Technology (VAST)","doi-asserted-by":"publisher","award":["THTEXS.03\/22-24"],"award-info":[{"award-number":["THTEXS.03\/22-24"]}],"id":[{"id":"10.13039\/100012046","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012046","name":"Vietnam Academy of Science and Technology (VAST)","doi-asserted-by":"publisher","award":["SWHYM"],"award-info":[{"award-number":["SWHYM"]}],"id":[{"id":"10.13039\/100012046","id-type":"DOI","asserted-by":"publisher"}]},{"name":"French Space Agency (Centre National d\u2019Etudes Spatiales\u2013CNES)","award":["THTEXS.03\/22-24"],"award-info":[{"award-number":["THTEXS.03\/22-24"]}]},{"name":"French Space Agency (Centre National d\u2019Etudes Spatiales\u2013CNES)","award":["SWHYM"],"award-info":[{"award-number":["SWHYM"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study estimates monthly variation of surface water volume of Thac Mo hydroelectric reservoir (located in South Vietnam), during the 2016\u20132021 period. Variation of surface water volume is estimated based on variation of surface water extent, derived from Sentinel-1 observations, and variation of surface water level, derived from Jason-3 altimetry data. Except for drought years in 2019 and 2020, surface water extent of Thac Mo reservoir varies in the range 50\u2013100 km2, while its water level varies in the range 202\u2013217 m. Correlation between these two components is high (R = 0.948), as well as correlation between surface water maps derived from Sentinel-1 and free-cloud Sentinel-2 observations (R = 0.98), and correlation between surface water level derived from Jason-3 altimetry data and from in situ measurement (R = 0.99; RMSE = 0.86 m). We showed that water volume of Thac Mo reservoir varies between \u22120.3 and 0.4 km3 month\u22121, and it is in a very good agreement with in situ measurement (R = 0.95; RMSE = 0.0682 km3 month\u22121). This study highlights the advantages in using different types of satellite observations and data for monitoring variation of lakes\u2019 water storage, which is very important for regional hydrological models. Similar research can be applied to monitor lakes in remote areas where in situ measurements are not available, or cannot be accessed freely.<\/jats:p>","DOI":"10.3390\/rs14164023","type":"journal-article","created":{"date-parts":[[2022,8,18]],"date-time":"2022-08-18T23:28:41Z","timestamp":1660865321000},"page":"4023","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Monitoring Lake Volume Variation from Space Using Satellite Observations\u2014A Case Study in Thac Mo Reservoir (Vietnam)"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6533-6830","authenticated-orcid":false,"given":"Binh","family":"Pham-Duc","sequence":"first","affiliation":[{"name":"REMOSAT, University of Science and Technology of Hanoi, Vietnam Academy of Science and Technology, Hanoi 10000, Vietnam"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4661-8274","authenticated-orcid":false,"given":"Frederic","family":"Frappart","sequence":"additional","affiliation":[{"name":"INRAE, Bordeaux Sciences Agro, UMR 1391 ISPA, 33140 Villenave-d\u2019Ornon, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1201-0161","authenticated-orcid":false,"given":"Quan","family":"Tran-Anh","sequence":"additional","affiliation":[{"name":"Faculty of Environment, Hanoi University of Mining and Geology, Hanoi 10000, Vietnam"}]},{"given":"Son Tong","family":"Si","sequence":"additional","affiliation":[{"name":"REMOSAT, University of Science and Technology of Hanoi, Vietnam Academy of Science and Technology, Hanoi 10000, Vietnam"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4935-462X","authenticated-orcid":false,"given":"Hien","family":"Phan","sequence":"additional","affiliation":[{"name":"REMOSAT, University of Science and Technology of Hanoi, Vietnam Academy of Science and Technology, Hanoi 10000, Vietnam"}]},{"given":"Son Nguyen","family":"Quoc","sequence":"additional","affiliation":[{"name":"REMOSAT, University of Science and Technology of Hanoi, Vietnam Academy of Science and Technology, Hanoi 10000, Vietnam"}]},{"given":"Anh Pham","family":"Le","sequence":"additional","affiliation":[{"name":"REMOSAT, University of Science and Technology of Hanoi, Vietnam Academy of Science and Technology, Hanoi 10000, Vietnam"}]},{"given":"Bach Do","family":"Viet","sequence":"additional","affiliation":[{"name":"Son La Hydro Power Plant, Son La 34000, Vietnam"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Huth, J., Gessner, U., Klein, I., Yesou, H., Lai, X., Oppelt, N., and Kuenzer, C. (2020). Analyzing Water Dynamics Based on Sentinel-1 Time Series\u2014A Study for Dongting Lake Wetlands in China. Remote Sens., 12.","DOI":"10.3390\/rs12111761"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1007\/s10712-016-9362-6","article-title":"Lake Volume Monitoring from Space","volume":"37","author":"Arsen","year":"2016","journal-title":"Surv. Geophys."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1007\/s00027-014-0377-0","article-title":"A global boom in hydropower dam construction","volume":"77","author":"Zarfl","year":"2015","journal-title":"Aquat. Sci."},{"key":"ref_4","first-page":"1","article-title":"Monitoring spatial-temporal dynamics of small lakes based on SAR Sentinel-1 observations: A case study over Nui Coc Lake (Vietnam)","volume":"44","year":"2021","journal-title":"Vietnam J. Earth Sci."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Pham-Duc, B., Prigent, C., and Aires, F. (2017). Surface Water Monitoring within Cambodia and the Vietnamese Mekong Delta over a Year, with Sentinel-1 SAR Observations. Water, 9.","DOI":"10.3390\/w9060366"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2273","DOI":"10.4319\/lo.2009.54.6_part_2.2273","article-title":"Lakes and Reservoirs as Sentinels, Integrators, and Regulators of Climate Change","volume":"54","author":"Williamson","year":"2009","journal-title":"Limnol. Oceanogr."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2388","DOI":"10.4319\/lo.2006.51.5.2388","article-title":"The global abundance and size distribution of lakes, ponds, and impoundments","volume":"51","author":"Downing","year":"2006","journal-title":"Limnol. Oceanogr."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jhydrol.2004.03.028","article-title":"Development and validation of a global database of lakes, reservoirs and wetlands","volume":"296","author":"Lehner","year":"2004","journal-title":"J. Hydrol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"597","DOI":"10.4319\/lo.2012.57.2.0597","article-title":"The regional abundance and size distribution of lakes and reservoirs in the United States and implications for estimates of global lake extent","volume":"57","author":"McDonald","year":"2012","journal-title":"Limnol. Oceanogr."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"814","DOI":"10.1111\/j.1365-2427.2007.01730.x","article-title":"Small lakes dominate a random sample of regional lake characteristics","volume":"52","author":"Hanson","year":"2007","journal-title":"Freshw. Biol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"350","DOI":"10.4319\/lo.2011.56.1.0350","article-title":"Does the Pareto distribution adequately describe the size-distribution of lakes?","volume":"56","author":"Seekell","year":"2011","journal-title":"Limnol. Oceanogr."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1002\/grl.50139","article-title":"A fractal-based approach to lake size-distributions","volume":"40","author":"Seekell","year":"2013","journal-title":"Geophys. Res. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"6396","DOI":"10.1002\/2014GL060641","article-title":"A global inventory of lakes based on high-resolution satellite imagery","volume":"41","author":"Verpoorter","year":"2014","journal-title":"Geophys. Res. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1038\/nature20584","article-title":"High-resolution mapping of global surface water and its long-term changes","volume":"540","author":"Pekel","year":"2016","journal-title":"Nature"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1080\/17538940701782577","article-title":"Water resource applications with Radarsat-2\u2014A preview","volume":"1","author":"Brisco","year":"2008","journal-title":"Int. J. Digit. Earth"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1109\/MGRS.2013.2248301","article-title":"A tutorial on synthetic aperture radar","volume":"1","author":"Moreira","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3519","DOI":"10.1080\/01431161.2015.1060647","article-title":"Comparing four operational SAR-based water and flood detection approaches","volume":"36","author":"Martinis","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.actaastro.2012.10.034","article-title":"Observing floods from space: Experience gained from COSMO-SkyMed observations","volume":"84","author":"Pierdicca","year":"2013","journal-title":"Acta Astronaut."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"562","DOI":"10.1109\/JSTARS.2013.2283340","article-title":"Flood Mapping with TerraSAR-X in Forested Regions in Estonia","volume":"7","author":"Voormansik","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"89","DOI":"10.2166\/nh.2008.041","article-title":"Detection of permanent open water surfaces in central Siberia with ENVISAT ASAR wide swath data with special emphasis on the estimation of methane fluxes from tundra wetlands","volume":"39","author":"Bartsch","year":"2008","journal-title":"Hydrol. Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"336","DOI":"10.5589\/m09-025","article-title":"A semi-automated tool for surface water mapping with RADARSAT-1","volume":"35","author":"Brisco","year":"2009","journal-title":"Can. J. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Reschke, J., Bartsch, A., Schlaffer, S., and Schepaschenko, D. (2012). Capability of C-Band SAR for Operational Wetland Monitoring at High Latitudes. Remote Sens., 4.","DOI":"10.3390\/rs4102923"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.rse.2015.10.031","article-title":"Strengths and weaknesses of multi-year Envisat ASAR backscatter measurements to map permanent open water bodies at global scale","volume":"171","author":"Santoro","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Vignudelli, S., Kostianoy, A.G., Cipollini, P., and Benveniste, J. (2011). Radar Altimetry: Past, Present and Future. Coastal Altimetry, Springer.","DOI":"10.1007\/978-3-642-12796-0"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Vignudelli, S., Kostianoy, A.G., Cipollini, P., and Benveniste, J. (2011). From Research to Operations: The USDA Global Reservoir and Lake Monitor BT. Coastal Altimetry, Springer.","DOI":"10.1007\/978-3-642-12796-0"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Cr\u00e9taux, J.-F., Biancamaria, S., Arsen, A., Berg\u00e9-Nguyen, M., and Becker, M. (2015). Global surveys of reservoirs and lakes from satellites and regional application to the Syrdarya river basin. Environ. Res. Lett., 10.","DOI":"10.1088\/1748-9326\/10\/1\/015002"},{"key":"ref_27","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_28","doi-asserted-by":"crossref","first-page":"570","DOI":"10.1111\/j.1365-246X.2006.03184.x","article-title":"Water volume change in the lower Mekong from satellite altimetry and imagery data","volume":"167","author":"Frappart","year":"2006","journal-title":"Geophys. J. Int."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Papa, F., Durand, F., Rossow, W.B., Rahman, A., and Bala, S.K. (2010). Satellite altimeter-derived monthly discharge of the Ganga-Brahmaputra River and its seasonal to interannual variations from 1993 to 2008. J. Geophys. Res. Ocean., 115.","DOI":"10.1029\/2009JC006075"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Pham-Duc, B., Sylvestre, F., Papa, F., Frappart, F., Bouchez, C., and Cr\u00e9taux, J.-F. (2020). The Lake Chad hydrology under current climate change. Sci. Rep., 10.","DOI":"10.1038\/s41598-020-62417-w"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Pham-Duc, B., Papa, F., Prigent, C., Aires, F., Biancamaria, S., and Frappart, F. (2019). Variations of Surface and Subsurface Water Storage in the Lower Mekong Basin (Vietnam and Cambodia) from Multisatellite Observations. Water, 11.","DOI":"10.3390\/w11010075"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2007","DOI":"10.5194\/hess-18-2007-2014","article-title":"Combining high-resolution satellite images and altimetry to estimate the volume of small lakes","volume":"18","author":"Baup","year":"2014","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1497","DOI":"10.1016\/j.asr.2011.01.004","article-title":"SOLS: A lake database to monitor in the Near Real Time water level and storage variations from remote sensing data","volume":"47","author":"Arsen","year":"2011","journal-title":"Adv. Sp. Res."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1520","DOI":"10.1016\/j.scitotenv.2018.04.326","article-title":"Influence of recent climatic events on the surface water storage of the Tonle Sap Lake","volume":"636","author":"Frappart","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Chou, F.N.-F., Linh, N.T.T., and Wu, C.-W. (2020). Optimizing the Management Strategies of a Multi-Purpose Multi-Reservoir System in Vietnam. Water, 12.","DOI":"10.3390\/w12040938"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Fok, H.S., He, Q., Chun, K.P., Zhou, Z., and Chu, T. (2018). Application of ENSO and Drought Indices for Water Level Reconstruction and Prediction: A Case Study in the Lower Mekong River Estuary. Water, 10.","DOI":"10.3390\/w10010058"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"4073","DOI":"10.1175\/1520-0442(2001)014<4073:IVOTAS>2.0.CO;2","article-title":"Interannual Variability of the Asian Summer Monsoon: Contrasts between the Indian and the Western North Pacific\u2013East Asian Monsoons","volume":"14","author":"Wang","year":"2001","journal-title":"J. Clim."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1093","DOI":"10.1139\/cjce-2017-0707","article-title":"Classification of El Ni\u00f1o and La Ni\u00f1a years for water resources management in Alberta","volume":"45","author":"Islam","year":"2018","journal-title":"Can. J. Civ. Eng."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Hund, S.V., Grossmann, I., Steyn, D.G., Allen, D.M., and Johnson, M.S. (2021). Changing Water Resources Under El Ni\u00f1o, Climate Change, and Growing Water Demands in Seasonally Dry Tropical Watersheds. Water Resour. Res., 57.","DOI":"10.1029\/2020WR028535"},{"key":"ref_40","unstructured":"(2022, June 20). ESA Sentinel-1 Technical Guides 2015. Available online: https:\/\/sentinels.copernicus.eu\/web\/sentinel\/technical-guides\/sentinel-1-sar."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Li, Y., Niu, Z., Xu, Z., and Yan, X. (2020). Construction of High Spatial-Temporal Water Body Dataset in China Based on Sentinel-1 Archives and GEE. Remote Sens., 12.","DOI":"10.3390\/rs12152413"},{"key":"ref_42","unstructured":"(2022, June 20). Sentinel-1 Algorithms in Google Earth Engine; 2022. Available online: https:\/\/developers.google.com\/earth-engine\/guides\/sentinel1."},{"key":"ref_43","first-page":"1","article-title":"Supraglacial rivers on the northwest Greenland Ice Sheet, Devon Ice Cap, and Barnes Ice Cap mapped using Sentinel-2 imagery","volume":"78","author":"Yang","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_44","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_45","doi-asserted-by":"crossref","unstructured":"Vaze, P., Neeck, S., Bannoura, W., Green, J., Wade, A., Mignogno, M., Zaouche, G., Couderc, V., Thouvenot, E., and Parisot, F. (2010, January 20\u201323). The Jason-3 Mission: Completing the transition of ocean altimetry from research to operations. Proceedings of the Sensors, Systems, and Next-Generation Satellites XIV, SPIE, Toulouse, France.","DOI":"10.1117\/12.868543"},{"key":"ref_46","unstructured":"Wingham, D.J., Rapley, C.G., and Griffiths, H. (1986, January 8\u201311). New techniques in satellite altimeter tracking systems. Proceedings of the IGARSS\u2019 86 Symposium, Z\u00fcrich, Switzerland."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1016\/j.rse.2005.10.027","article-title":"Preliminary results of ENVISAT RA-2-derived water levels validation over the Amazon basin","volume":"100","author":"Frappart","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_48","unstructured":"CTOH (2022, June 20). Center for Topographic Studies of the Ocean and Hydrosphere. Available online: http:\/\/ctoh.legos.obs-mip.fr\/."},{"key":"ref_49","unstructured":"European Commission (2022, June 20). Global Surface Water Explorer. Available online: https:\/\/global-surface-water.appspot.com\/#."},{"key":"ref_50","unstructured":"ThacMo (2022, June 20). Thac Mo Hydropower Company. Available online: https:\/\/tmhpp.com.vn\/."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"5326","DOI":"10.1109\/JSTARS.2020.3021052","article-title":"Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review","volume":"13","author":"Amani","year":"2020","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.isprsjprs.2020.04.001","article-title":"Google Earth Engine for geo-big data applications: A meta-analysis and systematic review","volume":"164","author":"Tamiminia","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Zhao, Q., Yu, L., Li, X., Peng, D., Zhang, Y., and Gong, P. (2021). Progress and Trends in the Application of Google Earth and Google Earth Engine. Remote Sens., 13.","DOI":"10.3390\/rs13183778"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Xiong, J., Thenkabail, P.S., Tilton, J.C., Gumma, M.K., Teluguntla, P., Oliphant, A., Congalton, R.G., Yadav, K., and Gorelick, N. (2017). Nominal 30-m Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine. Remote Sens., 9.","DOI":"10.3390\/rs9101065"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Midekisa, A., Holl, F., Savory, D.J., Andrade-Pacheco, R., Gething, P.W., Bennett, A., and Sturrock, H.J.W. (2017). Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0184926"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Hao, B., Ma, M., Li, S., Li, Q., Hao, D., Huang, J., Ge, Z., Yang, H., and Han, X. (2019). Land Use Change and Climate Variation in the Three Gorges Reservoir Catchment from 2000 to 2015 Based on the Google Earth Engine. Sensors, 19.","DOI":"10.3390\/s19092118"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.isprsjprs.2017.07.011","article-title":"A mangrove forest map of China in 2015: Analysis of time series Landsat 7\/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform","volume":"131","author":"Chen","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Hird, J.N., DeLancey, E.R., McDermid, G.J., and Kariyeva, J. (2017). Google Earth Engine, Open-Access Satellite Data, and Machine Learning in Support of Large-Area Probabilistic Wetland Mapping. Remote Sens., 9.","DOI":"10.3390\/rs9121315"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1016\/j.scitotenv.2019.06.341","article-title":"Continuous monitoring of lake dynamics on the Mongolian Plateau using all available Landsat imagery and Google Earth Engine","volume":"689","author":"Zhou","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_61","unstructured":"Huffman, G.J., Stocker, E.F., Bolvin, D.T., Nelkin, E.J., and Tan, J. (2022, June 20). GPM IMERG Final Precipitation L3 1 Month 0.1 Degree \u00d7 0.1 Degree V06, Available online: https:\/\/disc.gsfc.nasa.gov\/datasets\/GPM_3IMERGM_06\/summary."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.atmosres.2019.03.025","article-title":"Evaluating the hydrological utility of latest IMERG products over the Upper Huaihe River Basin, China","volume":"225","author":"Su","year":"2019","journal-title":"Atmos. Res."},{"key":"ref_63","unstructured":"NASA (2022, June 20). Giovani Webpage, Available online: https:\/\/giovanni.gsfc.nasa.gov\/giovanni\/."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"453","DOI":"10.5194\/hess-15-453-2011","article-title":"Global land-surface evaporation estimated from satellite-based observations","volume":"15","author":"Miralles","year":"2011","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1903","DOI":"10.5194\/gmd-10-1903-2017","article-title":"GLEAM v3: Satellite-based land evaporation and root-zone soil moisture","volume":"10","author":"Martens","year":"2017","journal-title":"Geosci. Model Dev."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Frappart, F., Wigneron, J.-P., Li, X., Liu, X., Al-Yaari, A., Fan, L., Wang, M., Moisy, C., Le Masson, E., and Aoulad Lafkih, Z. (2020). Global Monitoring of the Vegetation Dynamics from the Vegetation Optical Depth (VOD): A Review. Remote Sens., 12.","DOI":"10.3390\/rs12182915"},{"key":"ref_67","unstructured":"GLEAM (2022, June 20). The Global Land Evaporation Amsterdam Model. Available online: https:\/\/www.gleam.eu\/."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"1999","DOI":"10.1002\/qj.3803","article-title":"The ERA5 global reanalysis","volume":"146","author":"Hersbach","year":"2020","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_69","unstructured":"(2022, June 20). European_Commission Copernicus Climate Data Store. Available online: https:\/\/cds.climate.copernicus.eu\/#!\/home."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"19569","DOI":"10.1029\/1999JD900232","article-title":"A parameterization of snowpack and frozen ground intended for NCEP weather and climate models","volume":"104","author":"Koren","year":"1999","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1175\/BAMS-85-3-381","article-title":"The Global Land Data Assimilation System","volume":"85","author":"Rodell","year":"2004","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"McNally, A., Arsenault, K., Kumar, S., Shukla, S., Peterson, P., Wang, S., Funk, C., Peters-Lidard, C.D., and Verdin, J.P. (2017). A land data assimilation system for sub-Saharan Africa food and water security applications. Sci. Data, 4.","DOI":"10.1038\/sdata.2017.12"},{"key":"ref_73","unstructured":"Beaudoing, H., and Rodell, M. (2022, June 20). GLDAS Noah Land Surface Model L4 3 Hourly 0.25 \u00d7 0.25 Degree V2.1, Greenbelt, Maryland, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Available online: https:\/\/disc.gsfc.nasa.gov\/datasets\/GLDAS_NOAH025_3H_2.1\/summary."},{"key":"ref_74","unstructured":"McNally, A. (2022, June 20). FLDAS Noah Land Surface Model L4 Global Monthly 0.1 \u00d7 0.1 Degree (MERRA-2 and CHIRPS), Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center, Available online: https:\/\/disc.gsfc.nasa.gov\/datasets\/FLDAS_NOAH01_C_GL_M_001\/summary."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"1781","DOI":"10.1016\/j.rse.2011.02.019","article-title":"Improvements to a MODIS global terrestrial evapotranspiration algorithm","volume":"115","author":"Mu","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_76","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_77","doi-asserted-by":"crossref","unstructured":"Frappart, F., Blarel, F., Fayad, I., Berg\u00e9-Nguyen, M., Cr\u00e9taux, J.-F., Shu, S., Schregenberger, J., and Baghdadi, N. (2021). Evaluation of the Performances of Radar and Lidar Altimetry Missions for Water Level Retrievals in Mountainous Environment: The Case of the Swiss Lakes. Remote Sens., 13.","DOI":"10.3390\/rs13112196"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"285","DOI":"10.3319\/TAO.2005.16.2.285(A)","article-title":"A review on the western North Pacific monsoon: Synoptic-to-interannual variabilities","volume":"16","author":"Li","year":"2005","journal-title":"Terr. Atmos. Ocean. Sci."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1080\/16742834.2020.1806683","article-title":"Contrasting the Indian and western North Pacific summer monsoons in terms of their intensity of interannual variability and biennial relationship with ENSO","volume":"13","author":"CHEN","year":"2020","journal-title":"Atmos. Ocean. Sci. Lett."},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Yun, X., Tang, Q., Li, J., Lu, H., Zhang, L., and Chen, D. (2021). Can reservoir regulation mitigate future climate change induced hydrological extremes in the Lancang-Mekong River Basin?. Sci. Total Environ., 785.","DOI":"10.1016\/j.scitotenv.2021.147322"},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1080\/15387216.2020.1870516","article-title":"The politics of securitization: China\u2019s competing security agendas and their impacts on securitizing shared rivers","volume":"63","author":"Xie","year":"2022","journal-title":"Eurasian Geogr. Econ."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.envsci.2020.07.021","article-title":"Informal water diplomacy and power: A case of seeking water security in the Mekong River basin","volume":"114","author":"Mirumachi","year":"2020","journal-title":"Environ. Sci. Policy"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/16\/4023\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:11:39Z","timestamp":1760141499000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/16\/4023"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,18]]},"references-count":82,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2022,8]]}},"alternative-id":["rs14164023"],"URL":"https:\/\/doi.org\/10.3390\/rs14164023","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,18]]}}}