{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T07:07:29Z","timestamp":1773817649693,"version":"3.50.1"},"reference-count":69,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2021,3,5]],"date-time":"2021-03-05T00:00:00Z","timestamp":1614902400000},"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":["41974003, 41674007, 41374010"],"award-info":[{"award-number":["41974003, 41674007, 41374010"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Basin runoff is a quantity of river discharge per unit basin area monitored close to an estuary mouth, essential for providing information on the flooding and drought conditions of an entire river basin. Owing to a decreasing number of in situ monitoring stations since the late 1970s, basin runoff estimates using remote sensing have been advocated. Previous runoff estimates of the entire Mekong Basin calculated from the water balance equation were achieved through the hybrid use of remotely sensed and model-predicted data products. Nonetheless, these basin runoff estimates revealed a weak consistency with the in situ ones. To address this issue, we provide a newly improved estimate of the monthly Mekong Basin runoff by using the terrestrial water balance equation, purely based on remotely sensed water balance component data products. The remotely sensed water balance component data products used in this study included the satellite precipitation from the Tropical Rainfall Measuring Mission (TRMM), the satellite evapotranspiration from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the inferred terrestrial water storage from the Gravity Recovery and Climate Experiment (GRACE). A comparison of our new estimate and previously published result against the in situ runoff indicated a marked improvement in terms of the Pearson\u2019s correlation coefficient (PCC), reaching 0.836 (the new estimate) instead of 0.621 (the previously published result). When a three-month moving-average process was applied to each data product, our new estimate further reached a PCC of 0.932, along with the consistent improvement revealed from other evaluation metrics. Conducting an error analysis of the estimated mean monthly runoff for the entire data timespan, we found that the usage of different evapotranspiration data products had a substantial influence on the estimated runoff. This indicates that the choice of evapotranspiration data product is critical in the remotely sensed runoff estimation.<\/jats:p>","DOI":"10.3390\/rs13050996","type":"journal-article","created":{"date-parts":[[2021,3,5]],"date-time":"2021-03-05T11:46:09Z","timestamp":1614944769000},"page":"996","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Improved Mekong Basin Runoff Estimate and Its Error Characteristics Using Pure Remotely Sensed Data Products"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0535-5292","authenticated-orcid":false,"given":"Hok Sum","family":"Fok","sequence":"first","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"},{"name":"Key Laboratory of Geophysical Geodesy, Ministry of Natural Resources, Wuhan 430079, China"}]},{"given":"Yutong","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"},{"name":"Key Laboratory of Geophysical Geodesy, Ministry of Natural Resources, Wuhan 430079, China"}]},{"given":"Lei","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Civil, Environmental and Geodetic Engineering, Ohio State University, Columbus, OH 43210, USA"},{"name":"Core Faculty, Translational Data Analytics Institute, Ohio State University, Columbus, OH 43210, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9915-4960","authenticated-orcid":false,"given":"Robert","family":"Tenzer","sequence":"additional","affiliation":[{"name":"Department of Land Surveying and Geo-informatics, The Hong Kong Polytechnic University, Hong Kong, China"}]},{"given":"Qing","family":"He","sequence":"additional","affiliation":[{"name":"Department of Geography, Hong Kong Baptist University, Hong Kong, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,5]]},"reference":[{"key":"ref_1","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_2","doi-asserted-by":"crossref","first-page":"945","DOI":"10.1007\/s11269-014-0853-2","article-title":"Impact of intensive irrigation activities on river discharge under agricultural scenarios in the semi-arid Aksu river basin, northwest China","volume":"29","author":"Huang","year":"2015","journal-title":"Water Resour. Manag."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Zampieri, M., Carmona Garcia, G., Dentener, F., Gumma, M., Salamon, P., Seguini, L., and Toreti, A. (2018). Surface freshwater limitation explains worst rice production anomaly in India in 2002. Remote Sens., 10.","DOI":"10.3390\/rs10020244"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1333","DOI":"10.1007\/s10712-014-9300-4","article-title":"Estimating runoff using hydro-geodetic approaches","volume":"35","author":"Sneeuw","year":"2014","journal-title":"Surv. Geophys."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1491","DOI":"10.1126\/science.1089802","article-title":"Tracking fresh water from space","volume":"301","author":"Alsdorf","year":"2003","journal-title":"Science"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Gleason, C.J., and Durand, M.T. (2020). Remote sensing of river discharge: A review and framing for the discipline. Remote Sens., 12.","DOI":"10.3390\/rs12071107"},{"key":"ref_7","first-page":"376","article-title":"Calibration and validation of a distributed energy\u2013water balance model using satellite data of land surface temperature and ground discharge measurements","volume":"15","author":"Chiara","year":"2012","journal-title":"J. Hydrometeorol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.rse.2013.04.010","article-title":"Toward the estimation of river discharge variations using MODIS data in ungauged basins","volume":"136","author":"Tarpanelli","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1080\/07038992.2000.10855273","article-title":"NDVI and its relationships with hydrological regimes in the upper Yangtze","volume":"26","author":"Lu","year":"2000","journal-title":"Can. J. Remote Sens."},{"key":"ref_10","first-page":"753","article-title":"Spatio-temporal changes of NDVI and their relations with precipitation and runoff in the Yellow River Basin","volume":"23","author":"Li","year":"2004","journal-title":"Geogr. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1080\/07038992.2016.1171135","article-title":"Correlation analysis of Mackenzie river discharge and NDVI relationship","volume":"42","author":"Xu","year":"2016","journal-title":"Can. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1175\/1520-0426(1998)015<0809:TTRMMT>2.0.CO;2","article-title":"The tropical rainfall measuring mission (TRMM) sensor package","volume":"15","author":"Kummerow","year":"1998","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Rodell, M., Famiglietti, J.S., Chen, J., Seneviratne, S.I., Viterbo, P., Holl, S., and Wilson, C.R. (2004). Basin scale estimates of evapotranspiration using GRACE and other observations. Geophys. Res. Lett., 31.","DOI":"10.1029\/2004GL020873"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"L11501","DOI":"10.1029\/2004GL019779","article-title":"Time-variable gravity from GRACE: First results","volume":"31","author":"Wahr","year":"2004","journal-title":"Geophys Res Lett."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Fok, H.S., and He, Q. (2018). Water Level Reconstruction Based on Satellite Gravimetry in the Yangtze River Basin. ISPRS Int. J. Geo Inf., 7.","DOI":"10.3390\/ijgi7070286"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Zhou, L., Fok, H.S., Ma, Z., and Chen, Q. (2019). Upstream Remotely-Sensed Hydrological Variables and Their Standardization for Surface Runoff Reconstruction and Estimation of the Entire Mekong River Basin. Remote Sens., 11.","DOI":"10.3390\/rs11091064"},{"key":"ref_17","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_18","doi-asserted-by":"crossref","first-page":"L17404","DOI":"10.1029\/2005GL023836","article-title":"Water slope and discharge in the Amazon river estimated using the shuttle radar topography mission digital elevation model","volume":"32","author":"LeFavour","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_19","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":"2010","journal-title":"Hydrol. Process."},{"key":"ref_20","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 observations","volume":"519","author":"Pavelsky","year":"2014","journal-title":"J. Hydrol."},{"key":"ref_21","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 datasets","volume":"179","author":"Sichangi","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"116","DOI":"10.13031\/2013.33488","article-title":"Seasonal variations of Manning\u2019s roughness coefficient in a subtropical marsh","volume":"25","author":"Shih","year":"1982","journal-title":"Trans. ASABE"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1061\/(ASCE)0733-9437(2008)134:2(185)","article-title":"Spatial and temporal variation of Manning\u2019s roughness coefficient in furrow irrigation","volume":"134","author":"Mailapalli","year":"2008","journal-title":"J. Irrig. Drain. Eng."},{"key":"ref_24","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. Envrion."},{"key":"ref_25","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_26","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.rse.2004.07.007","article-title":"Ob\u2019 river discharge from TOPEX\/Poseidon satellite altimetry (1992\u20132002)","volume":"93","author":"Kouraev","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_27","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_28","doi-asserted-by":"crossref","unstructured":"Kim, D., Lee, H., Chang, C.H., Bui, D.D., Jayasinghe, S., Basnayake, S., Chishtie, F., and Hwang, E. (2019). Daily river discharge estimation using multi-mission radar altimetry data and ensemble learning regression in the lower mekong river basin. Remote Sens., 11.","DOI":"10.3390\/rs11222684"},{"key":"ref_29","first-page":"12","article-title":"ICESat derived elevation changes of Tibetan lakes between 2003 and 2009","volume":"17","author":"Phan","year":"2012","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_30","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 Sc."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3415","DOI":"10.3390\/rs5073415","article-title":"Estimating total discharge in the Yangtze River Basin using satellite-based observations","volume":"5","author":"Ferreira","year":"2013","journal-title":"Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"L24404","DOI":"10.1029\/2005GL024851","article-title":"Total basin discharge for the Amazon and Mississippi River basins from GRACE and a land-atmosphere water balance","volume":"32","author":"Syed","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1175\/2008JHM993.1","article-title":"GRACE-based estimates of terrestrial freshwater discharge from basin to continental scales","volume":"10","author":"Syed","year":"2009","journal-title":"J. Hydrometeorol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"532","DOI":"10.3390\/w9070532","article-title":"Total discharge estimation in the Korean Peninsula using multi-satellite products","volume":"9","author":"Seo","year":"2017","journal-title":"Water"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"L09607","DOI":"10.1029\/2004GL019920","article-title":"The gravity recovery and climate experiment: Mission overview and early results","volume":"31","author":"Tapley","year":"2004","journal-title":"Geophys. Res. Lett."},{"key":"ref_36","first-page":"415","article-title":"Physics of climate","volume":"173","author":"Peixoto","year":"1992","journal-title":"N. Y. Am. Inst. Phys."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1175\/1520-0477(1996)077<0437:TNYRP>2.0.CO;2","article-title":"The NCEP\/NCAR 40-year reanalysis project","volume":"77","author":"Kalnay","year":"1996","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_38","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_39","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1175\/BAMS-85-3-381","article-title":"The global land data assimilation system","volume":"3","author":"Rodell","year":"2004","journal-title":"Bull. Am. Meteorol Soc."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Chen, Y., Fok, H.S., Ma, Z., and Tenzer, R. (2019). Improved remote sensed total basin discharge and its seasonal error characterization in the Yangtze River Basin. Sensors, 19.","DOI":"10.3390\/s19153386"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/j.agrformet.2018.01.022","article-title":"Stand-alone uncertainty characterization of GLEAM, GLDAS and MOD16 evapotranspiration products using an extended triple collocation approach","volume":"252","author":"Khan","year":"2018","journal-title":"Agric. For. Meteorol."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1002\/esp.2036","article-title":"Changes in hydrology and sediment delivery of the Mekong River in the last 50 years: Connection to damming, monsoon, and ENSO","volume":"36","author":"Xue","year":"2011","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1175\/1520-0442(2002)015<0386:RSOTAP>2.0.CO;2","article-title":"Rainy Season of the Asian\u2013Pacific Summer Monsoon","volume":"15","author":"Wang","year":"2002","journal-title":"J. Clim."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.jhydrol.2012.10.028","article-title":"Spatiotemporal influences of ENSO on precipitation and flood pulse in the Mekong River Basin","volume":"476","author":"Kummu","year":"2013","journal-title":"J. Hydrol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.earscirev.2017.10.008","article-title":"Recent evolution of the Mekong Delta and the impacts of dams","volume":"175","author":"Li","year":"2017","journal-title":"Earth Sci. Rev."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1080\/19390459.2011.607962","article-title":"Reassessing water security in the Mekong: The Chinese rapprochement with Southeast Asia","volume":"3","author":"Onishi","year":"2011","journal-title":"J. Nat. Resour. Policy Res."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.quaint.2014.02.006","article-title":"Observed changes in the water flow at Chiang Saen in the lower Mekong: Impacts of Chinese dams?","volume":"336","author":"Lu","year":"2014","journal-title":"Quat. Int."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"4529","DOI":"10.5194\/hess-18-4529-2014","article-title":"Historical impact of water infrastructure on water levels of the Mekong River and the Tonle Sap system","volume":"18","author":"Cochrane","year":"2014","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_49","unstructured":"Lillesand, T., Kiefer, R.W., and Chipman, J. (2015). Remote Sensing and Image Interpretation, John Wiley & Sons."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Peng, H., Fok, H.S., Gong, J., and Wang, L. (2020). Improving Stage\u2013Discharge Relation in The Mekong River Estuary by Remotely Sensed Long-Period Ocean Tides. Remote Sens., 12.","DOI":"10.3390\/rs12213648"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1722","DOI":"10.1002\/hyp.9718","article-title":"Water balance analysis for the Tonle Sap Lake\u2013floodplain system","volume":"28","author":"Kummu","year":"2014","journal-title":"Hydrol Process."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.margeo.2010.01.013","article-title":"Impact of the east Asian monsoon rainfall changes on the erosion of the mekong river basin over the past 25,000 yr","volume":"271","author":"Colin","year":"2010","journal-title":"Mar. Geol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1317","DOI":"10.1175\/BAMS-D-11-00152.1","article-title":"Tropical Rainfall Measuring Mission (TRMM) precipitation data and services for research and applications","volume":"93","author":"Liu","year":"2012","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1175\/JHM560.1","article-title":"The TRMM Multi-satellite Precipitation Analysis: Quasi-Global, Multi-Year, Combined-Sensor Precipitation Estimates at Fine Scale","volume":"8","author":"Huffman","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_55","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_56","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.jog.2012.01.007","article-title":"Geocenter motion and its geodetic and geophysical implications","volume":"58","author":"Wu","year":"2012","journal-title":"J. Geodyn."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1007\/s00190-016-0995-5","article-title":"The unexpected signal in GRACE estimates of C20","volume":"91","author":"Cheng","year":"2017","journal-title":"J. Geod."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Swenson, S., and Wahr, J. (2006). Post-processing removal of correlated errors in GRACE data. Geophys. Res. Lett., 33.","DOI":"10.1029\/2005GL025285"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"30205","DOI":"10.1029\/98JB02844","article-title":"Time variability of the Earth\u2019s gravity field: Hydrological and oceanic effects and their possible detection using GRACE","volume":"103","author":"Wahr","year":"1998","journal-title":"J Geophys. Res. Solid Earth"},{"key":"ref_60","first-page":"2357","article-title":"Evaluation of Three Satellite-Based Precipitation Products Over the Lower Mekong River Basin Using Rain Gauge Observations and Hydrological Modeling","volume":"12","author":"Li","year":"2019","journal-title":"IEEE J-STARS"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"655","DOI":"10.1002\/hyp.3360090513","article-title":"Global atmospheric water balance and runoff from large river basins","volume":"9","author":"Oki","year":"1995","journal-title":"Hydrol. Process."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1016\/j.jhydrol.2009.06.019","article-title":"A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series","volume":"374","author":"Wang","year":"2009","journal-title":"J. Hydrol."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Fok, H.S., Zhou, L., Liu, Y., Ma, Z., and Chen, Y. (2020). Upstream GPS vertical displacement and its standardization for Mekong river basin surface runoff reconstruction and estimation. Remote Sens., 12.","DOI":"10.3390\/rs12010018"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/0022-1694(70)90255-6","article-title":"River flow forecasting through conceptual models part I\u2014A discussion of principles","volume":"10","author":"Nash","year":"1970","journal-title":"J. Hydrol."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Loc, H.H., Do, Q.H., Cokro, A.A., and Irvine, K.N. (2020). Deep neural network analyses of water quality time series associated with water sensitive urban design (WSUD) features. J. Appl. Water. Eng. Res., 1\u201320.","DOI":"10.1080\/23249676.2020.1831976"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"5609","DOI":"10.1073\/pnas.1201423109","article-title":"Trading-off fish biodiversity, food security, and hydropower in the Mekong River Basin","volume":"109","author":"Ziv","year":"2012","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"7183","DOI":"10.1029\/2000JD900719","article-title":"Summarizing multiple aspects of model performance in a single diagram","volume":"106","author":"Taylor","year":"2001","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"1131","DOI":"10.1002\/2013WR014581","article-title":"Uncertainty in evapotranspiration from land surface modeling, remote sensing, and GRACE satellites","volume":"50","author":"Long","year":"2014","journal-title":"Water Resour. Res."},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Wang, K., and Dickinson, R.E. (2012). A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability. Rev. Geophys., 50.","DOI":"10.1029\/2011RG000373"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/5\/996\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:33:33Z","timestamp":1760160813000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/5\/996"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,5]]},"references-count":69,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2021,3]]}},"alternative-id":["rs13050996"],"URL":"https:\/\/doi.org\/10.3390\/rs13050996","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,3,5]]}}}