{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T10:29:41Z","timestamp":1772620181060,"version":"3.50.1"},"reference-count":76,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T00:00:00Z","timestamp":1597881600000},"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>Despite increasing interest in monitoring the global water cycle, the availability of in situ gauging and discharge time series is decreasing. However, this lack of ground data can partly be compensated for by using remote sensing techniques to observe river stages and discharge. In this paper, a new approach for estimating discharge by combining water levels from multi-mission satellite altimetry and surface area extents from optical imagery with physical flow equations at a single cross-section is presented and tested at the Lower Mississippi River. The datasets are combined by fitting a hypsometric curve, which is then used to derive the water level for each acquisition epoch of the long-term multi-spectral remote sensing missions. In this way, the chance of detecting water level extremes is increased and a bathymetry can be estimated from water surface extent observations. Below the minimum hypsometric water level, the river bed elevation is estimated using an empirical width-to-depth relationship in order to determine the final cross-sectional geometry. The required flow gradient is derived from the differences between virtual station elevations, which are computed in a least square adjustment from the height differences of all multi-mission satellite altimetry data that are close in time. Using the virtual station elevations, satellite altimetry data from multiple virtual stations and missions are combined to one long-term water level time series. All required parameters are estimated purely based on remote sensing data, without using any ground data or calibration. The validation at three gauging stations of the Lower Mississippi River shows large deviations primarily caused by the below average width of the predefined cross-sections. At 13 additional cross-sections situated in wide, uniform, and straight river sections nearby the gauges the Normalized Root Mean Square Error (NRMSE) varies between 10.95% and 28.43%. The Nash-Sutcliffe Efficiency (NSE) for these targets is in a range from 0.658 to 0.946.<\/jats:p>","DOI":"10.3390\/rs12172693","type":"journal-article","created":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T09:35:31Z","timestamp":1597916131000},"page":"2693","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Long-Term Discharge Estimation for the Lower Mississippi River Using Satellite Altimetry and Remote Sensing Images"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6210-5869","authenticated-orcid":false,"given":"Daniel","family":"Scherer","sequence":"first","affiliation":[{"name":"Deutsches Geod\u00e4tisches Forschungsinsitut der Technischen Universit\u00e4t M\u00fcnchen (DGFI-TUM), Arcisstra\u00dfe 21, 80333 M\u00fcnchen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4741-3449","authenticated-orcid":false,"given":"Christian","family":"Schwatke","sequence":"additional","affiliation":[{"name":"Deutsches Geod\u00e4tisches Forschungsinsitut der Technischen Universit\u00e4t M\u00fcnchen (DGFI-TUM), Arcisstra\u00dfe 21, 80333 M\u00fcnchen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8940-4639","authenticated-orcid":false,"given":"Denise","family":"Dettmering","sequence":"additional","affiliation":[{"name":"Deutsches Geod\u00e4tisches Forschungsinsitut der Technischen Universit\u00e4t M\u00fcnchen (DGFI-TUM), Arcisstra\u00dfe 21, 80333 M\u00fcnchen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0718-6069","authenticated-orcid":false,"given":"Florian","family":"Seitz","sequence":"additional","affiliation":[{"name":"Deutsches Geod\u00e4tisches Forschungsinsitut der Technischen Universit\u00e4t M\u00fcnchen (DGFI-TUM), Arcisstra\u00dfe 21, 80333 M\u00fcnchen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,20]]},"reference":[{"key":"ref_1","first-page":"817","article-title":"Water resources","volume":"Volume 2","author":"Schneider","year":"2012","journal-title":"Encyclopedia of Climate and Weather"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/S0955-5986(02)00056-0","article-title":"Capitalising on river flow data to meet changing national needs\u2014A UK perspective","volume":"13","author":"Marsh","year":"2002","journal-title":"Flow Meas. Instrum."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"841","DOI":"10.5194\/hess-12-841-2008","article-title":"Value of river discharge data for global-scale hydrological modeling","volume":"12","author":"Hunger","year":"2008","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1038\/359373a0","article-title":"The hydrological cycle and its influence on climate","volume":"359","author":"Chahine","year":"1992","journal-title":"Nature"},{"key":"ref_5","unstructured":"Chow, V.T. (1964). Streamflow Measurement. Handbook of Applied Hydrology, McGraw-Hill. Chapter 15."},{"key":"ref_6","unstructured":"Singh, V.P. (2016). Streamflow Rating. Handbook of Applied Hydrology, McGraw-Hill. [2nd ed.]. Chapter 6."},{"key":"ref_7","unstructured":"Singh, V.P. (2016). Streamflow Data. Handbook of Applied Hydrology, McGraw-Hill. [2nd ed.]. Chapter 5."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.1002\/hyp.7794","article-title":"Large-scale river flow archives: Importance, current status and future needs","volume":"25","author":"Hannah","year":"2011","journal-title":"Hydrol. Process."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"4788","DOI":"10.1073\/pnas.1317606111","article-title":"Toward global mapping of river discharge using satellite images and at-many-stations hydraulic geometry","volume":"111","author":"Gleason","year":"2014","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_10","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_11","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1016\/j.rse.2017.06.045","article-title":"Global WaterPack\u2014A 250 m resolution dataset revealing the daily dynamics of global inland water bodies","volume":"198","author":"Klein","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Schwatke, C., Scherer, D., and Dettmering, D. (2019). Automated Extraction of Consistent Time-Variable Water Surfaces of Lakes and Reservoirs Based on Landsat and Sentinel-2. Remote Sens., 11.","DOI":"10.3390\/rs11091010"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1109\/LGRS.2007.908305","article-title":"RivWidth: A Software Tool for the Calculation of River Widths From Remotely Sensed Imagery","volume":"5","author":"Pavelsky","year":"2008","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1126\/science.aat0636","article-title":"Global extent of rivers and streams","volume":"361","author":"Allen","year":"2018","journal-title":"Science"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1109\/LGRS.2019.2920225","article-title":"RivWidthCloud: An Automated Google Earth Engine Algorithm for River Width Extraction From Remotely Sensed Imagery","volume":"17","author":"Yang","year":"2020","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"RG2002","DOI":"10.1029\/2006RG000197","article-title":"Measuring surface water from space","volume":"45","author":"Alsdorf","year":"2007","journal-title":"Rev. Geophys."},{"key":"ref_17","unstructured":"Singh, V.P. (2016). Remote Sensing Techniques and Data Assimilation for Hydrologic Modeling. Handbook of Applied Hydrology, McGraw-Hill. [2nd ed.]. Chapter 8."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Kugler, Z., Nghiem, S., and Brakenridge, G. (2019). L-Band Passive Microwave Data from SMOS for River Gauging Observations in Tropical Climates. Remote Sens., 11.","DOI":"10.3390\/rs11070835"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"25179","DOI":"10.1029\/95JC02125","article-title":"The contribution of TOPEX\/POSEIDON to the global monitoring of climatically sensitive lakes","volume":"100","author":"Birkett","year":"1995","journal-title":"J. Geophys. Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"L16401","DOI":"10.1029\/2005GL022814","article-title":"Global inland water monitoring from multi-mission altimetry","volume":"32","author":"Berry","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_21","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_22","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.asr.2016.10.008","article-title":"Satellite radar altimetry water elevations performance over a 200 m wide river: Evaluation over the Garonne River","volume":"59","author":"Biancamaria","year":"2017","journal-title":"Adv. Space Res."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1007\/s12665-018-7823-6","article-title":"Satellite altimetry for measuring river stages in remote regions","volume":"77","author":"Liu","year":"2018","journal-title":"Environ. Earth Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1007\/s00190-016-0980-z","article-title":"Combination of multi-mission altimetry data along the Mekong River with spatio-temporal kriging","volume":"91","author":"Boergens","year":"2017","journal-title":"J. Geod."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1016\/j.rse.2018.08.030","article-title":"Deriving three dimensional reservoir bathymetry from multi-satellite datasets","volume":"217","author":"Getirana","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Schwatke, C., Dettmering, D., and Seitz, F. (2020). Volume Variations of Small Inland Water Bodies from a Combination of Satellite Altimetry and Optical Imagery. Remote Sens., 12.","DOI":"10.3390\/rs12101606"},{"key":"ref_27","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_28","doi-asserted-by":"crossref","first-page":"4174","DOI":"10.1002\/wrcr.20348","article-title":"A quantile function approach to discharge estimation from satellite altimetry (ENVISAT)","volume":"49","author":"Tourian","year":"2013","journal-title":"Water Resour. Res."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/j.jhydrol.2017.01.009","article-title":"River discharge estimation at daily resolution from satellite altimetry over an entire river basin","volume":"546","author":"Tourian","year":"2017","journal-title":"J. Hydrol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-018-20032-w","article-title":"Mapping Monthly Water Scarcity in Global Transboundary Basins at Country-Basin Mesh Based Spatial Resolution","volume":"8","author":"Degefu","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1080\/07900627.2019.1698413","article-title":"Economically challenged and water scarce: Identification of global populations most vulnerable to water crises","volume":"36","author":"Oki","year":"2020","journal-title":"Int. J. Water Resour. Dev."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1007\/s10712-015-9346-y","article-title":"The SWOT Mission and Its Capabilities for Land Hydrology","volume":"37","author":"Biancamaria","year":"2016","journal-title":"Surv. Geophys."},{"key":"ref_33","first-page":"161","article-title":"On the flow of water in open channels and pipes","volume":"20","author":"Manning","year":"1891","journal-title":"Trans. Inst. Civ. Eng. Irel."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"9604","DOI":"10.1002\/2014WR016109","article-title":"Retrieval of river discharge solely from satellite imagery and at-many-stations hydraulic geometry: Sensitivity to river form and optimization parameters","volume":"50","author":"Gleason","year":"2014","journal-title":"Water Resour. Res."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Julien, P.Y. (2018). River Mechanics, Cambridge University Press.","DOI":"10.1017\/9781316107072"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.jhydrol.2013.12.050","article-title":"Estimating reach-averaged discharge for the River Severn from measurements of river water surface elevation and slope","volume":"511","author":"Durand","year":"2014","journal-title":"J. Hydrol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1109\/JSTARS.2009.2033453","article-title":"Estimating River Depth From Remote Sensing Swath Interferometry Measurements of River Height, Slope, and Width","volume":"3","author":"Durand","year":"2010","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"124561","DOI":"10.1016\/j.jhydrol.2020.124561","article-title":"River discharge estimation from radar altimetry: Assessment of satellite performance, river scales and methods","volume":"583","author":"Zakharova","year":"2020","journal-title":"J. Hydrol."},{"key":"ref_39","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_40","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.advwatres.2015.02.007","article-title":"Inference of effective river properties from remotely sensed observations of water surface","volume":"79","author":"Garambois","year":"2015","journal-title":"Adv. Water Resour."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1000","DOI":"10.1016\/j.jhydrol.2018.04.005","article-title":"Satellite remote sensing estimation of river discharge: Application to the Yukon River Alaska","volume":"561","author":"Bjerklie","year":"2018","journal-title":"J. Hydrol."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1016\/j.jhydrol.2007.04.011","article-title":"Estimating the bankfull velocity and discharge for rivers using remotely sensed river morphology information","volume":"341","author":"Bjerklie","year":"2007","journal-title":"J. Hydrol."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Kebede, M.G., Wang, L., Yang, K., Chen, D., Li, X., Zeng, T., and Hu, Z. (2020). Discharge Estimates for Ungauged Rivers Flowing over Complex High-Mountainous Regions based Solely on Remote Sensing-Derived Datasets. Remote Sens., 12.","DOI":"10.3390\/rs12071064"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"4527","DOI":"10.1002\/2015WR018434","article-title":"An intercomparison of remote sensing river discharge estimation algorithms from measurements of river height, width, and slope","volume":"52","author":"Durand","year":"2016","journal-title":"Water Resour. Res."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.rse.2016.03.019","article-title":"Estimating continental river basin discharges using multiple remote sensing data sets","volume":"179","author":"Sichangi","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"6692","DOI":"10.1029\/2018WR024220","article-title":"River Bathymetry Estimate and Discharge Assessment from Remote Sensing","volume":"55","author":"Moramarco","year":"2019","journal-title":"Water Resour. Res."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Sichangi, A., Wang, L., and Hu, Z. (2018). Estimation of River Discharge Solely from Remote-Sensing Derived Data: An Initial Study Over the Yangtze River. Remote Sens., 10.","DOI":"10.3390\/rs10091385"},{"key":"ref_48","unstructured":"Gupta, A. (2007). The Mississippi River System. Large Rivers, John Wiley & Sons, Ltd."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Little, C.D., and Biedenharn, D.S. (2014). Mississippi River Hydrodynamic and Delta Management Study (MRHDM)\u2014Geomorphic Assessment, US Army Engineer Research and Development Center (ERDC). Technical Report 14-5.","DOI":"10.21236\/ADA606456"},{"key":"ref_50","unstructured":"Gupta, A. (2007). Hydrology and Discharge. Large Rivers, John Wiley & Sons, Ltd."},{"key":"ref_51","unstructured":"(2020, August 05). The Global Runoff Data Centre, 56068 Koblenz, Germany. GRDC Data Download Portal. Available online: https:\/\/portal.grdc.bafg.de\/."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Lewis, J., Brown, G., and Ayers, S. (2017). Investigation of Discharge Measurements of the Lower Mississippi River below Natchez, MS, US Army Corps of Engineering. Technical Report 3.","DOI":"10.21079\/11681\/22738"},{"key":"ref_53","unstructured":"U.S. Geological Survey (2019, December 10). USGS Water Data for the Nation, Available online: https:\/\/waterdata.usgs.gov\/nwis."},{"key":"ref_54","unstructured":"US Army Corps of Engineers (2019, December 10). Rivergages.com. Available online: http:\/\/rivergages.mvr.usace.army.mil."},{"key":"ref_55","unstructured":"US Army Corps of Engineers (2019, December 10). USACE Hydrographic Surveys Powered by eHydro. Available online: https:\/\/geospatial-usace.opendata.arcgis.com\/datasets\/4b8f2ba307684cf597617bf1b6d2f85d."},{"key":"ref_56","unstructured":"US Army Corps of Engineers, N.O.D. (2019, December 10). Multibeam Bathymetric Data for the Lower Mississippi River. Available online: mvn.usace.army.mil\/Missions\/Engineering\/Channel-Improvement-and-Stabilization-Program\/2013MBMR\/."},{"key":"ref_57","unstructured":"Girardeau-Montaut, D. (2019, December 10). CloudCompare (version 2.9.1). Available online: http:\/\/www.cloudcompare.org\/."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"2255","DOI":"10.3390\/rs6032255","article-title":"Multi-Mission Cross-Calibration of Satellite Altimeters: Constructing a Long-Term Data Record for Global and Regional Sea Level Change Studies","volume":"6","author":"Bosch","year":"2014","journal-title":"Remote Sens."},{"key":"ref_59","first-page":"62","article-title":"The Trough-and-Ridge diagram","volume":"1","year":"1949","journal-title":"Tellus"},{"key":"ref_60","unstructured":"OpenStreetMap Contributors (2019, December 10). Planet Dump. Available online: https:\/\/planet.osm.org."},{"key":"ref_61","first-page":"89","article-title":"Der hydraulische oder Profil-Radius","volume":"103\/104","author":"Einstein","year":"1934","journal-title":"Schweiz. Bauztg."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Niemeier, W. (2008). Ausgleichungsrechnung, De Gruyter.","DOI":"10.1515\/9783110206784"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"441","DOI":"10.2307\/1422689","article-title":"The Proof and Measurement of Association between Two Things","volume":"100","author":"Spearman","year":"1987","journal-title":"Am. J. Psychol."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1251","DOI":"10.1002\/esp.403","article-title":"Characterization of the spatial variability of channel morphology","volume":"27","author":"Moody","year":"2002","journal-title":"Earth Surf. Process. Landforms"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1117","DOI":"10.1130\/0016-7606(1952)63[1117:HAAOET]2.0.CO;2","article-title":"Hypsometric (Area-Altitude) Analysis of Erosional Topography","volume":"63","author":"Strahler","year":"1952","journal-title":"GSA Bull."},{"key":"ref_66","first-page":"473","article-title":"Estimating hydraulic roughness coefficients","volume":"37","author":"Cowan","year":"1956","journal-title":"Agric. Eng."},{"key":"ref_67","unstructured":"Arcement, G.J., and Schneider, V.R. (1989). Guide for Selecting Manning\u2019s Roughness Coefficients for Natural Channels and Flood Plains, Technical Report."},{"key":"ref_68","unstructured":"Fitzpatrick, F.A., and Waite, I.R. (1998). Revised Methods for Characterizing Stream Habitat in the National Water-Quality Assessment Program, Technical Report."},{"key":"ref_69","unstructured":"Leopold, L.B., Wolman, M.G., and Miller, J.P. (1964). Fluvial Processes in Geomorphology, Dover Publications, Inc."},{"key":"ref_70","unstructured":"Gordon, N.D., McMahon, T.A., Finlayson, B.L., Gippel, C.J., and Nathan, R.J. (2004). Stream Hydrology: An Introduction for Ecologists, John Wiley & Sons, Ltd. [2nd ed.]."},{"key":"ref_71","unstructured":"Gaines, R.A., and Priestas, A.M. (2016). Particle Size Distribution of Bed Sediments along the Mississippi River, Grafton, Illinois, to Head of Passes, Louisiana, November 2013, US Army Corps of Engineers. Technical Report 7."},{"key":"ref_72","unstructured":"Lecher, K. (2012). Taschenbuch der Wasserwirtschaft, Springer-Vieweg. [9th ed.]."},{"key":"ref_73","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_74","unstructured":"Jones, B.E. (1916). A Method of Determining the Daily Discharge of Rivers if Variable Slope, Technical Report."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"870","DOI":"10.1061\/(ASCE)0733-9429(2004)130:9(870)","article-title":"Reproduction of Hysteresis in Rating Curves","volume":"130","author":"Perumal","year":"2004","journal-title":"J. Hydraul. Eng."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s13201-018-0745-3","article-title":"Spreadsheet-based modelling of hysteresis-affected curves","volume":"8","author":"Zakwan","year":"2018","journal-title":"Appl. Water Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/17\/2693\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:03:58Z","timestamp":1760177038000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/17\/2693"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,20]]},"references-count":76,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2020,9]]}},"alternative-id":["rs12172693"],"URL":"https:\/\/doi.org\/10.3390\/rs12172693","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,8,20]]}}}