{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T04:05:26Z","timestamp":1768881926558,"version":"3.49.0"},"reference-count":64,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T00:00:00Z","timestamp":1705881600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2018YFE0105900"],"award-info":[{"award-number":["2018YFE0105900"]}]},{"name":"National Key R&amp;D Program of China","award":["42271040"],"award-info":[{"award-number":["42271040"]}]},{"name":"National Key R&amp;D Program of China","award":["41901049"],"award-info":[{"award-number":["41901049"]}]},{"name":"National Key R&amp;D Program of China","award":["41961134003"],"award-info":[{"award-number":["41961134003"]}]},{"name":"National Key R&amp;D Program of China","award":["SAJC202106"],"award-info":[{"award-number":["SAJC202106"]}]},{"name":"National Key R&amp;D Program of China","award":["151542KYSB20200015"],"award-info":[{"award-number":["151542KYSB20200015"]}]},{"name":"National Natural Science Foundation of China","award":["2018YFE0105900"],"award-info":[{"award-number":["2018YFE0105900"]}]},{"name":"National Natural Science Foundation of China","award":["42271040"],"award-info":[{"award-number":["42271040"]}]},{"name":"National Natural Science Foundation of China","award":["41901049"],"award-info":[{"award-number":["41901049"]}]},{"name":"National Natural Science Foundation of China","award":["41961134003"],"award-info":[{"award-number":["41961134003"]}]},{"name":"National Natural Science Foundation of China","award":["SAJC202106"],"award-info":[{"award-number":["SAJC202106"]}]},{"name":"National Natural Science Foundation of China","award":["151542KYSB20200015"],"award-info":[{"award-number":["151542KYSB20200015"]}]},{"name":"Key Deployment Projects of Sino-Africa Joint Research Center, Chinese Academy of Sciences","award":["2018YFE0105900"],"award-info":[{"award-number":["2018YFE0105900"]}]},{"name":"Key Deployment Projects of Sino-Africa Joint Research Center, Chinese Academy of Sciences","award":["42271040"],"award-info":[{"award-number":["42271040"]}]},{"name":"Key Deployment Projects of Sino-Africa Joint Research Center, Chinese Academy of Sciences","award":["41901049"],"award-info":[{"award-number":["41901049"]}]},{"name":"Key Deployment Projects of Sino-Africa Joint Research Center, Chinese Academy of Sciences","award":["41961134003"],"award-info":[{"award-number":["41961134003"]}]},{"name":"Key Deployment Projects of Sino-Africa Joint Research Center, Chinese Academy of Sciences","award":["SAJC202106"],"award-info":[{"award-number":["SAJC202106"]}]},{"name":"Key Deployment Projects of Sino-Africa Joint Research Center, Chinese Academy of Sciences","award":["151542KYSB20200015"],"award-info":[{"award-number":["151542KYSB20200015"]}]},{"name":"International Collaboration Program of Chinese Academy of Science","award":["2018YFE0105900"],"award-info":[{"award-number":["2018YFE0105900"]}]},{"name":"International Collaboration Program of Chinese Academy of Science","award":["42271040"],"award-info":[{"award-number":["42271040"]}]},{"name":"International Collaboration Program of Chinese Academy of Science","award":["41901049"],"award-info":[{"award-number":["41901049"]}]},{"name":"International Collaboration Program of Chinese Academy of Science","award":["41961134003"],"award-info":[{"award-number":["41961134003"]}]},{"name":"International Collaboration Program of Chinese Academy of Science","award":["SAJC202106"],"award-info":[{"award-number":["SAJC202106"]}]},{"name":"International Collaboration Program of Chinese Academy of Science","award":["151542KYSB20200015"],"award-info":[{"award-number":["151542KYSB20200015"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The potential of satellite soil moisture (SM) in improving hydrological modeling has been addressed in synthetic experiments, but it is less explored in real data cases. Here, we investigate the added value of Soil Moisture and Passive (SMAP) and Advanced Scatterometer (ASCAT) SM data to distributed hydrological modeling with the soil and water assessment tool (SWAT) in a highly human disturbed catchment (126, 486 km2) featuring a network of SM and streamflow observations. The investigation is based on the ensemble Kalman filter (EnKF) considering SM errors from satellite data using the triple collocation. The assimilation of SMAP and ASCAT SM improved the surface (0\u201310 cm) and rootzone (10\u201330 cm) SM at &gt;70% and &gt; 50% stations of the basin, respectively. However, the assimilation effects on distributed streamflow simulation of the basin are un-significant and not robust. SM assimilation improved the simulated streamflow at two upstream stations, while it deteriorated the streamflow at the remaining stations. This can be largely attributed to the poor vertical soil water coupling of SWAT, suboptimal model parameters, satellite SM data quality, humid climate, and human disturbance to rainfall-runoff processes. This study offers strong evidence of integrating satellite SM into hydrological modeling in improving SM estimation and provides implications for achieving the added value of remotely sensed SM in streamflow improvement.<\/jats:p>","DOI":"10.3390\/rs16020429","type":"journal-article","created":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T06:49:31Z","timestamp":1705906171000},"page":"429","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["The Impact of Satellite Soil Moisture Data Assimilation on the Hydrological Modeling of SWAT in a Highly Disturbed Catchment"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0835-7325","authenticated-orcid":false,"given":"Yongwei","family":"Liu","sequence":"first","affiliation":[{"name":"Key Laboratory of Watershed Geograpic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China"}]},{"given":"Wei","family":"Cui","sequence":"additional","affiliation":[{"name":"Nanjing Hydraulic Research Institute, Nanjing 210029, China"}]},{"given":"Zhe","family":"Ling","sequence":"additional","affiliation":[{"name":"Water Resources Department of Jiangsu Province, Nanjing 210029, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0099-1839","authenticated-orcid":false,"given":"Xingwang","family":"Fan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Watershed Geograpic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China"}]},{"given":"Jianzhi","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Earth System Science, Tianjin University, Tianjin 300072, China"}]},{"given":"Chengmei","family":"Luan","sequence":"additional","affiliation":[{"name":"Hydrology and Water Resources Investigation Bureau of Jiangsu Province, Nanjing 210027, China"}]},{"given":"Rong","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Watershed Geograpic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6832-105X","authenticated-orcid":false,"given":"Wen","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8780-927X","authenticated-orcid":false,"given":"Yuanbo","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Watershed Geograpic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"6874","DOI":"10.1002\/2013WR014639","article-title":"The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models","volume":"50","author":"Wanders","year":"2014","journal-title":"Water Resour. Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.earscirev.2010.02.004","article-title":"Investigating soil moisture\u2013climate interactions in a changing climate: A review","volume":"99","author":"Seneviratne","year":"2010","journal-title":"Earth Sci. Rev."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3825","DOI":"10.5194\/hess-26-3825-2022","article-title":"Historical droughts manifest an abrupt shift to a wetter Tibetan Plateau","volume":"26","author":"Liu","year":"2022","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1002\/hyp.6629","article-title":"On the estimation of antecedent wetness conditions in rainfall\u2013runoff modelling","volume":"22","author":"Brocca","year":"2008","journal-title":"Hydrol. Process."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Massari, C., Camici, S., Ciabatta, L., and Brocca, L. (2018). Exploiting satellite-based surface soil moisture for flood forecasting in the Mediterranean area: State update versus rainfall correction. Remote Sens., 10.","DOI":"10.3390\/rs10020292"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Crow, W., Bindlish, R., and Jackson, T.J. (2005). The added value of spaceborn passive microwave soil moisture retrievals for forecasting rainfall-runoff partitioning. Geophys. Res. Lett., 32.","DOI":"10.1029\/2005GL023543"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2827","DOI":"10.5194\/hess-20-2827-2016","article-title":"Assimilation of SMOS soil moisture into a distributed hydrological model and impacts on the water cycle variables over the Ou\u00e9m\u00e9 catchment in Benin","volume":"20","author":"Leroux","year":"2016","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1515\/johh-2017-0011","article-title":"Investigating the impact of surface soil moisture assimilation on state and parameter estimation in SWAT model based on the ensemble Kalman filter in upper Huai River basin","volume":"65","author":"Liu","year":"2017","journal-title":"J. Hydrol. Hydromech."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"126311","DOI":"10.1016\/j.jhydrol.2021.126311","article-title":"High spatial resolution simulation of profile soil moisture by assimilating multi-source remote-sensed information into a distributed hydrological model","volume":"597","author":"Yang","year":"2021","journal-title":"J. Hydrol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"w11416","DOI":"10.1029\/2008WR007401","article-title":"State and parameter estimation of hydrologic models using the constrained ensemble Kalman filter","volume":"45","author":"Wang","year":"2009","journal-title":"Water Resour. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/S0022-1694(03)00229-4","article-title":"Sequential assimilation of soil moisture and streamflow data in a conceptual rainfall\u2013runoff model","volume":"280","author":"Aubert","year":"2003","journal-title":"J. Hydrol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"e2023WR034506","DOI":"10.1029\/2023WR034506","article-title":"Soil moisture estimation by assimilating in-situ and SMAP surface soil moisture using unscented weighted ensemble Kalman filter","volume":"59","author":"Fu","year":"2023","journal-title":"Water Resour. Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"6950","DOI":"10.1002\/2012WR013473","article-title":"One-dimensional soil temperature simulation with Common Land Model by assimilating in situ observations and MODIS LST with the temperature simulation with Common Land Model by assimilating in situ observations and MODIS LST with the ensemble particle filter","volume":"50","author":"Yu","year":"2014","journal-title":"Water Resour. Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.advwatres.2012.08.007","article-title":"Assimilation and downscaling of satellite observed soil moisture over the Little River Experimental Watershed in Georgia, USA","volume":"52","author":"Sahoo","year":"2013","journal-title":"Adv. Water Resour."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.rse.2013.07.018","article-title":"Assimilation of remotely sensed soil moisture and vegetation with a crop simulation model for maize yield prediction","volume":"138","author":"Ines","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1659","DOI":"10.5194\/hess-19-1659-2015","article-title":"Improving operational flood ensemble prediction by the assimilation of satellite soil moisture: Comparison between lumped and semi-distributed schemes","volume":"19","author":"Ryu","year":"2015","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.rse.2015.06.025","article-title":"SMOS soil moisture assimilation for improved hydrologic simulation in the Murray Darling Basin. Australia","volume":"168","author":"Lievens","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"7301314","DOI":"10.1155\/2018\/7301314","article-title":"ESA CCI Soil Moisture Assimilation in SWAT for Improved Hydrological Simulation in Upper Huai River Basin","volume":"2018","author":"Liu","year":"2018","journal-title":"Adv. Meteorol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"18791","DOI":"10.1038\/s41598-020-75710-5","article-title":"Multi-mission satellite remote sensing data for improving land hydrological models via data assimilation","volume":"10","author":"Khaki","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"e2021WR029643","DOI":"10.1029\/2021WR029643","article-title":"Assimilation of satellite soil moisture products for river flow prediction: An extensive experiment in over 700 catchments throughout Europe","volume":"57","author":"Biondi","year":"2021","journal-title":"Water Resour. Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"526","DOI":"10.1016\/j.advwatres.2011.01.011","article-title":"Improving hydrologic predictions of a catchment model via assimilation of surface soil moisture","volume":"34","author":"Chen","year":"2011","journal-title":"Adv. Water Resour."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.5194\/hess-13-1-2009","article-title":"A new data assimilation approach for improving runoff prediction using remotely-sensed soil moisture retrievals","volume":"13","author":"Crow","year":"2009","journal-title":"Hydrol. Earth Sys. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.jhydrol.2011.11.039","article-title":"Implementation of surface soil moisture data assimilation with watershed scale distributed hydrological model","volume":"416\u2013417","author":"Han","year":"2012","journal-title":"J. Hydrol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1029\/2007WR006357","article-title":"An adaptive ensemble Kalman filter for soil moisture data assimilation","volume":"44","author":"Reichle","year":"2008","journal-title":"Water Resour. Res."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"678","DOI":"10.1016\/j.advwatres.2010.03.012","article-title":"Data assimilation for distributed hydrological catchment modeling via ensemble Kalman filter","volume":"33","author":"Xie","year":"2010","journal-title":"Adv. Water Resour."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.advwatres.2014.02.008","article-title":"Improving the estimation of hydrological states in the SWAT model via the ensemble Kalman smoother: Synthetic experiments for the Heihe River Basin in northwest China","volume":"67","author":"Lei","year":"2014","journal-title":"Adv. Water Resour."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Brocca, L., Moramarco, T., Dorigo, W., and Wagner, W. (2013, January 21\u201326). Assimilation of satellite soil moisture data into rainfall-runoff modelling for several catchments worldwide. Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium-IGARSS, Melbourne, VIC, Australia.","DOI":"10.1109\/IGARSS.2013.6723273"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Corato, G., Matgen, P., Fenicia, F., Schlaffer, S., and Chini, M. (2014, January 13\u201318). Assimilating satellite derived soil moisture products into a distributed hydrological model. Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, Quebec City, QC, Canada.","DOI":"10.1109\/IGARSS.2014.6947189"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"126465","DOI":"10.1016\/j.jhydrol.2021.126465","article-title":"Role of hydrological model structure in the assimilation of soil moisture for streamflow prediction","volume":"598","author":"Nayak","year":"2021","journal-title":"J. Hydrol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"11403","DOI":"10.3390\/rs70911403","article-title":"Data assimilation of satellite soil moisture into rainfall-runoff modelling: A complex recipe?","volume":"7","author":"Massari","year":"2015","journal-title":"Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"108745","DOI":"10.1016\/j.agrformet.2021.108745","article-title":"Understanding the key factors that influence soil moisture estimation using the unscented weighted ensemble Kalman filter","volume":"313","author":"Fu","year":"2022","journal-title":"Agric. For. Meteorol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2542","DOI":"10.1109\/TGRS.2011.2177468","article-title":"Assimilation of Surface-and Root-Zone ASCAT Soil Moisture Products Into Rainfall\u2013Runoff Modeling","volume":"50","author":"Brocca","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1016\/j.rse.2014.07.023","article-title":"Evaluation of the ESA CCI soil moisture product using ground-based observations","volume":"162","author":"Dorigo","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_34","unstructured":"Neitsch, S.L., Arnold, J.G., Kiniry, J.R., and Williams, J.R. (2011). Soil and Water Assessment Tool Theoretical Documentation Version 2009, Texax A&M University. Available online: http:\/\/swat.tamu.edu\/media\/99192\/swat2009theory.pdf."},{"key":"ref_35","unstructured":"Monteith, J.L. (1965). 19th Symposia of the Society for Experimental Biology: The State and Movement of Water in Living Organisms, Cambridge University Press."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"10143","DOI":"10.1029\/94JC00572","article-title":"Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. Journal of Geophysical methods to forecast error statistics","volume":"99","author":"Evensen","year":"1994","journal-title":"J. Geophys. Res.-Ocean"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1007\/s10236-003-0036-9","article-title":"The Ensemble Kalman Filter: Theoretical formulation and practical implementation","volume":"53","author":"Evensen","year":"2003","journal-title":"Ocean Dynam."},{"key":"ref_38","unstructured":"O\u2019Neill, P.E., Chan, S., Njoku, E.G., Jackson, T., Bindlish, R., and Chaubell, J. (2021). L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture, Version 8, NASA National Snow and Ice Data Center Distributed Active Archive Center."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/S0034-4257(99)00036-X","article-title":"A method for estimating soil moisture from ERS scatterometer and soil data","volume":"70","author":"Wagner","year":"1999","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1999","DOI":"10.1109\/TGRS.2008.2011617","article-title":"An improved soil moisture retrieval algorithm for ERS and METOP scatterometer observations","volume":"47","author":"Naeimi","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.rse.2015.03.008","article-title":"Evaluation of remotely sensed and reanalysis soil moisture products over the Tibetan Plateau using in-situ observations","volume":"163","author":"Zeng","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1649","DOI":"10.5194\/hess-22-1649-2018","article-title":"Controls on surface soil drying rates observed by smap and simulated by the noah land surface model","volume":"22","author":"Shellito","year":"2018","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"111756","DOI":"10.1016\/j.rse.2020.111756","article-title":"Comparison of microwave remote sensing and land surface modeling for surface soil moisture climatology estimation","volume":"242","author":"Dong","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"7755","DOI":"10.1029\/97JC03180","article-title":"Toward the true near-surface wind speed: Error modeling and calibration using triple collocation","volume":"103","author":"Stoffelen","year":"1998","journal-title":"J. Geophys. Res."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"6229","DOI":"10.1002\/2014GL061322","article-title":"Extended triple collocation: Estimating errors and correlation coefficients with respect to an unknown target","volume":"41","author":"McColl","year":"2014","journal-title":"Geophys. Res. Lett."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.rse.2017.07.001","article-title":"ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions","volume":"203","author":"Dorigo","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"W12519","DOI":"10.1029\/2010WR009402","article-title":"An improved approach for estimating observation and model error parameters in soil moisture data assimilation","volume":"46","author":"Crow","year":"2010","journal-title":"Water Resour. Res."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"6419","DOI":"10.1002\/2013JD021043","article-title":"Beyond triple collocation: Applications to soil moisture monitoring","volume":"119","author":"Su","year":"2014","journal-title":"J. Geophys. Res.-Atmos."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"L19501","DOI":"10.1029\/2004GL020938","article-title":"Bias reduction in short records of satellite soil moisture","volume":"31","author":"Reichle","year":"2004","journal-title":"Geophys. Res. Lett."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1101","DOI":"10.1016\/j.advwatres.2008.04.013","article-title":"Assimilation of a ERS scatterometer derived soil moisture index in the ECMWF numerical weather prediction system","volume":"31","author":"Scipal","year":"2008","journal-title":"Adv. Water Resour."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1309","DOI":"10.1016\/j.advwatres.2008.06.005","article-title":"Hydrological data assimilation with the ensemble Kalman filter: Use of streamflow observations to update states in a distributed hydrological model","volume":"31","author":"Clark","year":"2008","journal-title":"Adv. Water Resour."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1340","DOI":"10.2136\/vzj2004.1340","article-title":"Estimating uncertain flow and transport parameters using a sequential uncertainty fitting procedure","volume":"3","author":"Abbaspour","year":"2004","journal-title":"Vadose Zone J."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/j.advwatres.2013.06.010","article-title":"Hydrological data assimilation with the ensemble square-root-filter: Use of streamflow observations to update model states for real-time flash flood forecasting","volume":"59","author":"Chen","year":"2013","journal-title":"Adv. Water Resour."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1534","DOI":"10.1175\/2009JHM1134.1","article-title":"Role of Subsurface Physics in the Assimilation of Surface Soil Moisture Observations","volume":"10","author":"Kumar","year":"2009","journal-title":"J. Hydrometeor."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1016\/j.jhydrol.2017.10.058","article-title":"Improving streamflow simulations and forecasting performance of SWAT model by assimilating remotely sensed soil moisture observations","volume":"555","author":"Patil","year":"2017","journal-title":"J. Hydrol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.advwatres.2018.08.010","article-title":"Improved streamflow simulations by coupling soil moisture analytical relationship in EnKF based hydrological data assimilation framework","volume":"121","author":"Patil","year":"2018","journal-title":"Adv. Water Resour."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/S0022-1694(01)00421-8","article-title":"Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology","volume":"249","author":"Beven","year":"2001","journal-title":"J. Hydrol."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1016\/j.jhydrol.2015.03.027","article-title":"A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model","volume":"524","author":"Abbaspour","year":"2015","journal-title":"J. Hydrol."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1038\/s41467-021-27938-6","article-title":"Land transpiration-evaporation partitioning errors responsible for modeled summertime warm bias in the central United States","volume":"13","author":"Dong","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"7350","DOI":"10.1002\/2012WR012853","article-title":"A partitioned update scheme for state-parameter estimation of distributed hydrologic models based on the ensemble Kalman filter","volume":"49","author":"Xie","year":"2013","journal-title":"Water Resour. Res."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"04016060","DOI":"10.1061\/(ASCE)HE.1943-5584.0001475","article-title":"Data assimilation for streamflow forecasting: State-parameter assimilation versus output assimilation","volume":"22","author":"Sun","year":"2017","journal-title":"J. Hydrol. Eng."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1016\/j.jhydrol.2016.10.040","article-title":"Simultaneous assimilation of in situ soil moisture and streamflow in the SWAT model using the Extended Kalman Filter","volume":"543","author":"Sun","year":"2016","journal-title":"J. Hydrol."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"e2019WR026325","DOI":"10.1029\/2019WR026325","article-title":"Improving hydrological models with the assimilation of crowdsourced data","volume":"56","author":"Avellaneda","year":"2020","journal-title":"Water Resour. Res."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"124367","DOI":"10.1016\/j.jhydrol.2019.124367","article-title":"Assimilation of Sentinel 1 and SMAP\u2013based satellite soil moisture retrievals into SWAT hydrological model: The impact of satellite revisit time and product spatial resolution on flood simulations in small basins","volume":"581","author":"Azimi","year":"2020","journal-title":"J. Hydrol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/2\/429\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T13:47:11Z","timestamp":1760104031000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/2\/429"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,22]]},"references-count":64,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2024,1]]}},"alternative-id":["rs16020429"],"URL":"https:\/\/doi.org\/10.3390\/rs16020429","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,22]]}}}