{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T14:49:58Z","timestamp":1780498198639,"version":"3.54.1"},"reference-count":53,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2019,11,17]],"date-time":"2019-11-17T00:00:00Z","timestamp":1573948800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000104","name":"National Aeronautics and Space Administration","doi-asserted-by":"publisher","award":["NNX16AQ33G"],"award-info":[{"award-number":["NNX16AQ33G"]}],"id":[{"id":"10.13039\/100000104","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000104","name":"National Aeronautics and Space Administration","doi-asserted-by":"publisher","award":["80NSSC18K0423"],"award-info":[{"award-number":["80NSSC18K0423"]}],"id":[{"id":"10.13039\/100000104","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000104","name":"National Aeronautics and Space Administration","doi-asserted-by":"publisher","award":["TBD"],"award-info":[{"award-number":["TBD"]}],"id":[{"id":"10.13039\/100000104","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Korea Ministry of Environment","award":["79622"],"award-info":[{"award-number":["79622"]}]},{"name":"Vingroup Innovation Foundation (VINIF)","award":["VINIF.2019.DA17"],"award-info":[{"award-number":["VINIF.2019.DA17"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Estimating river discharge (Q) is critical for ecosystems and water resource management. Traditionally, estimating Q has depended on a single rating curve or the Manning equation. In contrast to the single rating curve, several rating curves at different locations have been linearly combined in an ensemble learning regression method to estimate Q (ELQ) at the Brazzaville gauge station in the central Congo River in a previous study. In this study, we further tested the proposed ELQ and apply it to the Lower Mekong River Basin (LMRB) with three locations: Stung Treng, Kratie, and Tan Chau. Two major advancements for estimating Q with ELQ are presented. First, ELQ successfully estimated Q at Tan Chau, downstream of Kratie, where hydrodynamic complexities exist. Since the hydrologic characteristics downstream of Kratie are extremely diverse and complex in time and space, most previous studies have estimated Q only upstream from Kratie with hydrologic models and statistical methods. Second, we estimated Q over the LMRB using ELQ with water levels (H) obtained from two radar altimetry missions, Envisat and Jason-2, which made it possible to estimate Q seamlessly from 2003 to 2016. Owing to ELQ with multi-mission radar altimetry data, we have overcome the problems of a single rating curve: Locations for estimating Q have to be close to virtual stations, e.g., a few tens of kilometers, because the performance of the single rating curve degrades as the distance between the location of Q estimation and a virtual station increases. Therefore, most previous studies had not used Jason-2 data whose cross-track interval is about 315 km at the equator. On the contrary, several H obtained from Jason-2 altimetry were used in this study regardless of distances from in-situ Q stations since the ELQ method compensates for degradation in the performance for Q estimation due to the poor rating curve with virtual stations away from in-situ Q stations. In general, the ELQ-estimated Q (      Q ^   E L Q      ) showed more accurate results compared to those obtained from a single rating curve. In the case of Tan Chau, the root mean square error (RMSE) of       Q ^   E L Q       decreased by 1504\/1338 m3\/s using Envisat-derived H for the training\/validation datasets. We successfully applied ELQ to the LMRB, which is one of the most complex basins to estimate Q with multi-mission radar altimetry data. Furthermore, our method can be used to obtain finer temporal resolution and enhance the performance of Q estimation with the current altimetry missions, such as Sentinel-3A\/B and Jason-3.<\/jats:p>","DOI":"10.3390\/rs11222684","type":"journal-article","created":{"date-parts":[[2019,11,18]],"date-time":"2019-11-18T04:31:10Z","timestamp":1574051470000},"page":"2684","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Daily River Discharge Estimation Using Multi-Mission Radar Altimetry Data and Ensemble Learning Regression in the Lower Mekong River Basin"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9373-0680","authenticated-orcid":false,"given":"Donghwan","family":"Kim","sequence":"first","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Houston, Houston, TX 77204, USA"},{"name":"National Center for Airborne Laser Mapping, University of Houston, Houston, TX 77204, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6478-7533","authenticated-orcid":false,"given":"Hyongki","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Houston, Houston, TX 77204, USA"},{"name":"National Center for Airborne Laser Mapping, University of Houston, Houston, TX 77204, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chi-Hung","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Houston, Houston, TX 77204, USA"},{"name":"National Center for Airborne Laser Mapping, University of Houston, Houston, TX 77204, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Duong Du","family":"Bui","sequence":"additional","affiliation":[{"name":"National Centre for Water Resources Planning and Investigation, Ministry of Natural Resources and Environment, Hanoi, Vietnam"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Susantha","family":"Jayasinghe","sequence":"additional","affiliation":[{"name":"Asian Disaster Preparedness Centre, Bangkok 10400, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Senaka","family":"Basnayake","sequence":"additional","affiliation":[{"name":"Asian Disaster Preparedness Centre, Bangkok 10400, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6392-6084","authenticated-orcid":false,"given":"Farrukh","family":"Chishtie","sequence":"additional","affiliation":[{"name":"Asian Disaster Preparedness Centre, Bangkok 10400, Thailand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Euiho","family":"Hwang","sequence":"additional","affiliation":[{"name":"Water Resources Research Center, K-Water Institute, K-Water, Daejeon 34350, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1126\/science.289.5477.284","article-title":"Global water resources: Vulnerability from climate change and population growth","volume":"289","author":"Green","year":"2000","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2006RG000197","article-title":"Measuring surface water from space","volume":"45","author":"Alsdorf","year":"2007","journal-title":"Rev. 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