{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T09:23:33Z","timestamp":1763457813086,"version":"build-2065373602"},"reference-count":95,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2019,4,6]],"date-time":"2019-04-06T00:00:00Z","timestamp":1554508800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Tropical reservoirs are critical infrastructure for managing drinking and irrigation water and generating hydroelectric power. However, long-term spaceborne monitoring of reservoir storage is challenged by data scarcity from near-persistent cloud cover and drought, which may reduce volumes below those in the observational record. In evaluating our ability to accurately monitor long-term reservoir volume dynamics using spaceborne data and overcome such observational challenges, we integrated optical, lidar, and radar time series to estimate reservoir volume dynamics across 13 reservoirs in eastern Brazil over a 12-year (2003\u20132014) period affected by historic drought. We (i) used 1560 Landsat images to measure reservoir surface area; (ii) built reservoir-specific regression models relating surface area and elevation from ICESat GLAS and Envisat RA-2 data; (iii) modeled volume changes for each reservoir; and (iv) compared modeled and in situ reservoir volume changes. Regression models had high goodness-of-fit (median RMSE = 0.89 m and r = 0.88) across reservoirs. Even though 88% of an average reservoir\u2019s volume time series was based on modeled area\u2013elevation relationships, we found exceptional agreement (RMSE = 0.31 km3 and r = 0.95) with in situ volume time series, and accurately captured seasonal recharge\/depletion dynamics and the drought\u2019s prolonged drawdown. Disagreements in volume dynamics were neither driven by wet\/dry season conditions nor reservoir capacity, indicating analytical efficacy across a range of monitoring scenarios.<\/jats:p>","DOI":"10.3390\/rs11070827","type":"journal-article","created":{"date-parts":[[2019,4,8]],"date-time":"2019-04-08T11:54:52Z","timestamp":1554724492000},"page":"827","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Monitoring Reservoir Drought Dynamics with Landsat and Radar\/Lidar Altimetry Time Series in Persistently Cloudy Eastern Brazil"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8074-0022","authenticated-orcid":false,"given":"Jamon","family":"Van Den Hoek","sequence":"first","affiliation":[{"name":"Geography Program, College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR 97331, USA"}]},{"given":"Augusto","family":"Getirana","sequence":"additional","affiliation":[{"name":"Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA"},{"name":"Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6330-1834","authenticated-orcid":false,"given":"Hahn Chul","family":"Jung","sequence":"additional","affiliation":[{"name":"Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA"},{"name":"Science Systems and Applications, Inc., Lanham, MD 20706, USA"}]},{"given":"Modurodoluwa A.","family":"Okeowo","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Houston, Houston, TX 77005, USA"}]},{"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 77005, USA"}]}],"member":"1968","published-online":{"date-parts":[[2019,4,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"13603","DOI":"10.1038\/ncomms13603","article-title":"Estimating the volume and age of water stored in global lakes using a geo-statistical approach","volume":"7","author":"Messager","year":"2016","journal-title":"Nat. Commun."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Garc\u00eda, L., Rodr\u00edguez, D., Wijnen, M., and Pakulski, I. (2016). Earth Observation for Water Resources Management: Current Use and Future Opportunities for the Water Sector, The World Bank.","DOI":"10.1596\/978-1-4648-0475-5"},{"key":"ref_3","first-page":"753","article-title":"Anthropogenic Disturbance of the Terrestrial Water Cycle","volume":"50","author":"Sahagian","year":"2006","journal-title":"Bioscience"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Zambon, R.C., Barros, M.T.L., and Yeh, W.W.G. (2016, January 22\u201326). Impacts of the 2012\u20132015 Drought on the Brazilian Hydropower System. Proceedings of the World Environmental and Water Resources Congress 2016, West Palm Beach, FL, USA.","DOI":"10.1061\/9780784479858.010"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Bastviken, D., Tranvik, L.J., Downing, J.A., Crill, P.M., and Enrich-Prast, A. (2011). Freshwater methane emissions offset the continental carbon sink. Science, 331.","DOI":"10.1126\/science.1196808"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1007\/s11027-005-7303-7","article-title":"Do hydroelectric dams mitigate global warming? The case of Brazil\u2019s Curu\u00e1-Una Dam","volume":"10","author":"Fearnside","year":"2005","journal-title":"Mitig. Adapt. Strateg. Glob. Chang."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1080\/20442041.2018.1483126","article-title":"Extreme drought boosts CO2 and CH4 emissions from reservoir drawdown areas","volume":"8","author":"Kosten","year":"2018","journal-title":"Inland Waters"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"838","DOI":"10.1038\/ngeo1653","article-title":"Hydroelectric carbon sequestration","volume":"5","author":"Kosten","year":"2012","journal-title":"Nat. Geosci."},{"key":"ref_9","first-page":"246","article-title":"Are hydroelectric reservoirs significant sources of greenhouse gases","volume":"22","author":"Rudd","year":"1993","journal-title":"Ambio"},{"key":"ref_10","first-page":"766","article-title":"Reservoir Surfaces as Sources of Greenhouse Gases to the Atmosphere: A Global Estimate","volume":"50","author":"Duchemin","year":"2006","journal-title":"Bioscience"},{"key":"ref_11","first-page":"2298","article-title":"Lakes and reservoirs as regulators of carbon cycling and climate","volume":"54","author":"Knoll","year":"2011","journal-title":"Limnol. Oceanogr."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1890\/100125","article-title":"High-resolution mapping of the world\u2019s reservoirs and dams for sustainable river-flow management","volume":"9","author":"Lehner","year":"2011","journal-title":"Front. Ecol. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1038\/ngeo1211","article-title":"Carbon emission from hydroelectric reservoirs linked to reservoir age and latitude","volume":"4","author":"Barros","year":"2011","journal-title":"Nat. Geosci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4251","DOI":"10.5194\/bg-11-4251-2014","article-title":"Physical controls on CH4 emissions from a newly flooded subtropical freshwater hydroelectric reservoir: Nam Theun 2","volume":"11","author":"Deshmukh","year":"2014","journal-title":"Biogeosciences"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1023\/A:1012971715668","article-title":"Greenhouse gas emissions from a hydroelectric reservoir (Brazil\u2019s Tucuru\u00eddam) and the energy policy implications","volume":"133","author":"Fearnside","year":"2002","journal-title":"Water Air Soil Pollut."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1029\/1998GB900015","article-title":"Long-term greenhouse gas emissions from hydroelectric reservoirs in tropical forest regions","volume":"13","author":"Delmas","year":"1999","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1007\/s11027-007-9086-5","article-title":"Methane emissions from large dams as renewable energy resources: A developing nation perspective","volume":"13","author":"Lima","year":"2008","journal-title":"Mitig. Adapt. Strateg. Glob. Chang."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"949","DOI":"10.1093\/biosci\/biw117","article-title":"Greenhouse Gas Emissions from Reservoir Water Surfaces: A New Global Synthesis","volume":"66","author":"Deemer","year":"2016","journal-title":"Bioscience"},{"key":"ref_19","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_20","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":"Jelinski","year":"2011","journal-title":"Adv. Space Res."},{"key":"ref_21","first-page":"894","article-title":"Monitoring of the water-area variations of Lake Dongting in China with ENVISAT ASAR images","volume":"13","author":"Ding","year":"2011","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_22","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_23","doi-asserted-by":"crossref","unstructured":"Gao, H., Birkett, C., and Lettenmaier, D.P. (2012). Global monitoring of large reservoir storage from satellite remote sensing. Water Resour. Res., 48.","DOI":"10.1029\/2012WR012063"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.rse.2017.08.015","article-title":"CryoSat-2 radar altimetry for monitoring freshwater resources of China","volume":"200","author":"Jiang","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1353","DOI":"10.1002\/esp.1822","article-title":"Remote sensing of volumetric storage changes in lakes","volume":"34","author":"Smith","year":"2009","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1696","DOI":"10.1109\/JSTARS.2015.2500599","article-title":"Integrating Landsat Imageries and Digital Elevation Models to Infer Water Level Change in Hoover Dam","volume":"9","author":"Tseng","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1007\/s10661-006-5233-9","article-title":"Measuring Water Storage Fluctuations in Lake Dongting, China, by Topex\/Poseidon Satellite Altimetry","volume":"115","author":"Zhang","year":"2006","journal-title":"Environ. Monit. Assess."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"448","DOI":"10.1016\/j.pce.2005.06.011","article-title":"Estimation of small reservoir storage capacities in a semi-arid environment","volume":"30","author":"Liebe","year":"2005","journal-title":"Phys. Chem. Earth"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Ogilvie, A., Belaud, G., Massuel, S., Mulligan, M., Le Goulven, P., Calvez, R., Ogilvie, A., Belaud, G., Massuel, S., and Mulligan, M. (2016). Assessing Floods and Droughts in Ungauged Small Reservoirs with Long-Term Landsat Imagery. Geosciences, 6.","DOI":"10.3390\/geosciences6040042"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"17113","DOI":"10.3390\/rs71215872","article-title":"Remote Sensing of Storage Fluctuations of Poorly Gauged Reservoirs and State Space Model (SSM)-Based Estimation","volume":"7","author":"Singh","year":"2015","journal-title":"Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Wang, L., and Dessler, A.E. (2006). Instantaneous cloud overlap statistics in the tropical area revealed by ICESat\/GLAS data. Geophys. Res. Lett., 33.","DOI":"10.1029\/2005GL024350"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"873","DOI":"10.1007\/s11269-011-9941-8","article-title":"Estimation of small reservoir storage capacities with remote sensing in the Brazilian Savannah region","volume":"26","author":"Rodrigues","year":"2012","journal-title":"Water Resour. Manag."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2739","DOI":"10.1080\/01431160600981517","article-title":"Spatial and temporal probabilities of obtaining cloud-free Landsat images over the Brazilian tropical savanna","volume":"28","author":"Sano","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_34","unstructured":"Vermote, E., and Wolfe, R. (2015). MOD09GA MODIS\/Terra Surface Reflectance Daily L2G Global 1kmand 500m SIN Grid V006 [Data set]."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"8927","DOI":"10.1002\/2014WR015829","article-title":"Monitoring reservoir storage in South Asia from multisatellite remote sensing","volume":"50","author":"Zhang","year":"2014","journal-title":"Water Resour. Res."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Chipman, J.W. (2019). A Multisensor Approach to Satellite Monitoring of Trends in Lake Area, Water Level, and Volume. Remote Sens., 11.","DOI":"10.3390\/rs11020158"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2103","DOI":"10.1002\/hyp.5559","article-title":"Seasonal inundation patterns in two large savanna floodplains of South America: The Llanos de Moxos (Bolivia) and the Llanos del Orinoco (Venezuela and Colombia)","volume":"18","author":"Hamilton","year":"2004","journal-title":"Hydrol. Proc."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Kang, S., and Hong, S.Y. (2016). Assessing Seasonal and Inter-Annual Variations of Lake Surface Areas in Mongolia during 2000-2011 Using Minimum Composite MODIS NDVI. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0151395"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"810","DOI":"10.1038\/nclimate3111","article-title":"Earth\u2019s surface water change over the past 30 years","volume":"6","author":"Donchyts","year":"2016","journal-title":"Nat. Clim. Chang."},{"key":"ref_40","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_41","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1080\/17538947.2015.1026420","article-title":"A global, high-resolution (30-m) inland water body dataset for 2000: First results of a topographic\u2013spectral classification algorithm","volume":"9","author":"Feng","year":"2016","journal-title":"Int. J. Digit. Earth"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1016\/j.rse.2015.11.003","article-title":"Water observations from space: Mapping surface water from 25years of Landsat imagery across Australia","volume":"174","author":"Mueller","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_43","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_44","doi-asserted-by":"crossref","unstructured":"Alsdorf, D.E., Rodr\u00edguez, E., and Lettenmaier, D.P. (2007). Measuring surface water from space. Rev. Geophys., 45.","DOI":"10.1029\/2006RG000197"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"6445","DOI":"10.5194\/hess-21-6445-2017","article-title":"Monitoring small reservoirs\u2019 storage with satellite remote sensing in inaccessible areas","volume":"21","author":"Avisse","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"2211","DOI":"10.1109\/TGRS.2014.2357893","article-title":"Waveform retracking for improving level estimations from TOPEX\/Poseidon, Jason-1, and Jason-2 altimetry observations over African lakes","volume":"53","author":"Uebbing","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Jiang, L., Schneider, R., Andersen, O.B., and Bauer-Gottwein, P. (2017). CryoSat-2 altimetry applications over rivers and lakes. Water, 9.","DOI":"10.3390\/w9030211"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"3042","DOI":"10.1080\/01431161.2016.1192702","article-title":"Selection of a network of large lakes and reservoirs suitable for global environmental change analysis using Earth Observation","volume":"37","author":"Politi","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"669","DOI":"10.5194\/hess-23-669-2019","article-title":"A global lake and reservoir volume analysis using a surface water dataset and satellite altimetry","volume":"23","author":"Busker","year":"2019","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1080\/01431160612331392815","article-title":"Cover: Clouds over land in Envisat ASAR C-band image","volume":"27","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Pipitone, C., Maltese, A., Dardanelli, G., Brutto, M.L., and Loggia, G.L. (2018). Monitoring water surface and level of a reservoir using different remote sensing approaches and comparison with dam displacements evaluated via GNSS. Remote Sens., 10.","DOI":"10.3390\/rs10010071"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Ye, Z., Liu, H., Chen, Y., Shu, S., Wu, Q., and Wang, S. (2017). Analysis of water level variation of lakes and reservoirs in Xinjiang, China using ICESat laser altimetry data (2003\u20132009). PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0183800"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1175\/JHM-D-15-0096.1","article-title":"Extreme Water Deficit in Brazil Detected from Space","volume":"17","author":"Getirana","year":"2016","journal-title":"J. Hydrometeorol."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"252","DOI":"10.4236\/jwarp.2016.82022","article-title":"Some Characteristics and Impacts of the Drought and Water Crisis in Southeastern Brazil during 2014 and 2015","volume":"08","author":"Nobre","year":"2016","journal-title":"J. Water Resour. Prot."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"9137","DOI":"10.1175\/JCLI-D-12-00642.1","article-title":"Two Contrasting Severe Seasonal Extremes in Tropical South America in 2012: Flood in Amazonia and Drought in Northeast Brazil","volume":"26","author":"Marengo","year":"2013","journal-title":"J. Clim."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1007\/s00704-016-1840-8","article-title":"Drought in Northeast Brazil\u2014Past, present, and future","volume":"129","author":"Marengo","year":"2017","journal-title":"Theor. Appl. Climatol."},{"key":"ref_57","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_58","doi-asserted-by":"crossref","first-page":"8837","DOI":"10.1080\/01431161.2010.547533","article-title":"Earth science applications of ICESat\/GLAS: A review","volume":"32","author":"Wang","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_59","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. Geoinf."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Birkett, C., Reynolds, C., Beckley, B., and Doorn, B. (2011). From research to operations: The USDA global reservoir and lake monitor. Coastal Altimetry, Springer-Verlag Berlin Heidelberg.","DOI":"10.1007\/978-3-642-12796-0_2"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"2160","DOI":"10.1016\/j.rse.2010.04.020","article-title":"Water levels in the Amazon basin derived from the ERS 2 and ENVISAT radar altimetry missions","volume":"114","author":"Calmant","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_62","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_63","doi-asserted-by":"crossref","first-page":"169","DOI":"10.3319\/TAO.2010.08.09.01(TibXS)","article-title":"Present-day lake level variation from envisat altimetry over the northeastern qinghai-tibetan plateau: Links with precipitation and temperature","volume":"22","author":"Lee","year":"2011","journal-title":"Terr. Atmos. Ocean. Sci."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"3604","DOI":"10.1016\/j.rse.2008.05.001","article-title":"Water level fluctuations derived from ENVISAT Radar Altimeter (RA-2) and in-situ measurements in a subtropical waterbody: Lake Izabal (Guatemala)","volume":"112","author":"Medina","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.jhydrol.2009.12.016","article-title":"Water volume variations in Lake Izabal (Guatemala) from in situ measurements and ENVISAT Radar Altimeter (RA-2) and Advanced Synthetic Aperture Radar (ASAR) data products","volume":"382","author":"Medina","year":"2010","journal-title":"J. Hydrol."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"4345","DOI":"10.5194\/hess-19-4345-2015","article-title":"DAHITI\u2014An innovative approach for estimating water level time series over inland waters using multi-mission satellite altimetry","volume":"19","author":"Schwatke","year":"2015","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1522","DOI":"10.1016\/j.rse.2011.02.011","article-title":"Inter-comparison study of water level estimates derived from hydrodynamic-hydrologic model and satellite altimetry for a complex deltaic environment","volume":"115","author":"Hossain","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Abshire, J.B., Sun, X., Riris, H., Sirota, J.M., McGarry, J.F., Liiva, P., Palm, S., and Yi, D. (2005). Geoscience Laser Altimeter System (GLAS) on the ICESat Mission: On-orbit measurement performance. Geophys. Res. Lett., 32.","DOI":"10.1029\/2005GL024028"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Hall, A.C., Schumann, G.J.P., Bamber, J.L., Bates, P.D., and Trigg, M.A. (2012). Geodetic corrections to Amazon River water level gauges using ICESat altimetry. Water Resour. Res., 48.","DOI":"10.1029\/2011WR010895"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"3276","DOI":"10.1002\/2015WR018237","article-title":"ICESat-derived inland water surface spot heights","volume":"52","author":"Neal","year":"2016","journal-title":"Water Resour. Res."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.jhydrol.2009.03.008","article-title":"Monitoring the water balance of Lake Victoria, East Africa, from space","volume":"370","author":"Swenson","year":"2009","journal-title":"J. Hydrol."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1109\/LGRS.2011.2167495","article-title":"Lake water footprint identification from time-series ICESat\/GLAS data","volume":"9","author":"Wang","year":"2012","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"3815","DOI":"10.1007\/s11434-013-5818-y","article-title":"Water balance estimates of ten greatest lakes in China using ICESat and Landsat data","volume":"58","author":"Zhang","year":"2013","journal-title":"Chin. Sci. Bull."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"3465","DOI":"10.1109\/JSTARS.2017.2684081","article-title":"Automated Generation of Lakes and Reservoirs Water Elevation Changes from Satellite Radar Altimetry","volume":"10","author":"Okeowo","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_75","unstructured":"Zwally, H.J., Schutz, R., Bentley, C., Bufton, J., Herring, T., Minster, J., Spinhirne, J., and Thomas, R. (2014). GLAS\/ICESat L2 Global Land Surface Altimetry Data, Version 34. [GLA14]."},{"key":"ref_76","unstructured":"(2018, May 18). Frequently Asked Questions. Available online: https:\/\/nsidc.org\/data\/icesat\/faq.html#alt7."},{"key":"ref_77","unstructured":"Schneider, J.C. (2000). Three Methods for Computing the Volume of a Lake, Manual of Fisheries Survey Methods II: With Periodic Updates."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.aqpro.2016.06.013","article-title":"Water for Development and Development for Water: Realizing the Sustainable Development Goals (SDGs) Vision","volume":"6","year":"2016","journal-title":"Aquat. Procedia"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1038\/nclimate2805","article-title":"Large rainfall changes consistently projected over substantial areas of tropical land","volume":"6","author":"Chadwick","year":"2016","journal-title":"Nat. Clim. Chang."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"811","DOI":"10.1038\/nclimate1907","article-title":"Changes in rainfall seasonality in the tropics","volume":"3","author":"Feng","year":"2013","journal-title":"Nat. Clim. Chang."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1002\/wrcr.20067","article-title":"Large-scale hydrologic and hydrodynamic modeling of the Amazon River basin","volume":"49","author":"Collischonn","year":"2013","journal-title":"Water Resour. Res."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"1641","DOI":"10.1175\/JHM-D-12-021.1","article-title":"The Hydrological Modeling and Analysis Platform (HyMAP): Evaluation in the Amazon Basin","volume":"13","author":"Getirana","year":"2012","journal-title":"J. Hydrometeorol."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1016\/j.jhydrol.2015.02.049","article-title":"Satellite-derived Digital Elevation Model (DEM) selection, preparation and correction for hydrodynamic modelling in large, low-gradient and data-sparse catchments","volume":"524","author":"Jarihani","year":"2015","journal-title":"J. Hydrol."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"7962","DOI":"10.1080\/01431161.2013.827814","article-title":"Lake water volume calculation with time series remote-sensing images","volume":"34","author":"Lu","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1111\/j.1440-1770.2007.00344.x","article-title":"Three methods for determining the area-depth relationship of Lake Poop\u00f3, a large shallow lake in Bolivia","volume":"12","author":"Bengtsson","year":"2007","journal-title":"Lakes Reserv."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"2123","DOI":"10.1002\/2015WR017952","article-title":"How well will the Surface Water and Ocean Topography (SWOT) mission observe global reservoirs?","volume":"52","author":"Solander","year":"2016","journal-title":"Water Resour. Res."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"2413","DOI":"10.5194\/hess-13-2413-2009","article-title":"Global-scale analysis of river flow alterations due to water withdrawals and reservoirs","volume":"13","author":"Doll","year":"2009","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"Haddeland, I., Skaugen, T., and Lettenmaier, D.P. (2006). Anthropogenic impacts on continental surface water fluxes. Geophys. Res. Lett., 33.","DOI":"10.1029\/2006GL026047"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"7245","DOI":"10.1002\/2013WR014845","article-title":"Assessing the impacts of reservoir operation to floodplain inundation by combining hydrological, reservoir management, and hydrodynamic models","volume":"50","author":"Mateo","year":"2014","journal-title":"Water Resour. Res."},{"key":"ref_90","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":"2013","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"10676","DOI":"10.3390\/rs61110676","article-title":"Sentinel-1 for monitoring reservoirs: A performance analysis","volume":"6","author":"Amitrano","year":"2014","journal-title":"Remote Sens."},{"key":"ref_92","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_93","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.rse.2011.09.030","article-title":"Sentinel 1 SAR interferometry applications: The outlook for sub millimeter measurements","volume":"120","author":"Rucci","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.3390\/rs6021191","article-title":"Remotely sensed monitoring of small reservoir dynamics: A Bayesian approach","volume":"6","author":"Eilander","year":"2014","journal-title":"Remote Sens."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"3055","DOI":"10.1080\/014311698214181","article-title":"Passive microwave observations of inundation area and the area\/stage relation in the Amazon River floodplain","volume":"19","author":"Sippel","year":"1998","journal-title":"Int. J. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/7\/827\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:43:24Z","timestamp":1760186604000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/7\/827"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,6]]},"references-count":95,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2019,4]]}},"alternative-id":["rs11070827"],"URL":"https:\/\/doi.org\/10.3390\/rs11070827","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2019,4,6]]}}}