{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T08:47:17Z","timestamp":1775033237064,"version":"3.50.1"},"reference-count":97,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,1,31]],"date-time":"2021-01-31T00:00:00Z","timestamp":1612051200000},"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>Microwave remote sensing techniques provide a direct measurement of surface soil moisture (SM), with advantages for all-weather observations and solid physics. However, most satellite microwave soil moisture products fail to meet the requirements of land surface studies for high-resolution surface soil moisture data due to their coarse spatial resolutions. Although many approaches have been proposed to downscale the spatial resolution of satellite soil moisture products, most of them have been tested in flat areas where the surface is relatively homogeneous. Thus, those established approaches are often inapplicable for downscaling in cold alpine areas with complex terrain where multiple factors control the variations in surface soil moisture. In this work, we re-inferred and verified the mathematical assumption behind a semi-physical approach for downscaling satellite soil moisture data and extended this approach for cold alpine areas. Instead of directly deriving SM from proxy variables, this approach relies on a relationship between two standardized variables of SM and apparent thermal inertia (ATI), in which the sub grid standard deviation for SM is estimated by a physical hydraulic model taking soil texture data as input. The approach was applied to downscale the soil moisture active passive (SMAP) daily data in a typical cold alpine basin, i.e., the Babao River basin located in the Qilian Mountains of Northwest China. We observed good linearity between the computed ATI and SM observations on most wireless sensor network sites installed in the study basin, which justifies the underlying assumption. The sub grid standard deviations for the SMAP grid estimated through the Mualem-van Genuchten model can broadly represent the real characteristics. The downscaled 1-km resolution results correlated well with the in-situ SM observations, with an average correlation coefficient of 0.74 and a small root mean square error (0.096 cm3\/cm3). The downscaled results show more and consistent textural details than the original SMAP data. After removal of biases in the original SMAP data even higher agreements with the observations can be achieved. These results demonstrate the adequacy of the proposed semi-physical approach for downscaling satellite soil moisture data in cold alpine areas, and the resultant fine-resolution data can serve as useful databases for land surface and hydrological studies in those areas.<\/jats:p>","DOI":"10.3390\/rs13030509","type":"journal-article","created":{"date-parts":[[2021,1,31]],"date-time":"2021-01-31T21:31:56Z","timestamp":1612128716000},"page":"509","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["A Semi-Physical Approach for Downscaling Satellite Soil Moisture Data in a Typical Cold Alpine Area, Northwest China"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6037-5387","authenticated-orcid":false,"given":"Zetao","family":"Cao","sequence":"first","affiliation":[{"name":"Key Laboratory of Ministry of Education on Virtual Geographic Environment, Nanjing Normal University, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongxia","family":"Gao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Ministry of Education on Virtual Geographic Environment, Nanjing Normal University, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7930-3850","authenticated-orcid":false,"given":"Zhuotong","family":"Nan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Ministry of Education on Virtual Geographic Environment, Nanjing Normal University, Nanjing 210023, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Zhao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Ministry of Education on Virtual Geographic Environment, Nanjing Normal University, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziyun","family":"Yin","sequence":"additional","affiliation":[{"name":"Key Laboratory of Ministry of Education on Virtual Geographic Environment, Nanjing Normal University, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1016\/j.rse.2018.02.065","article-title":"Spatially enhanced passive microwave derived soil moisture: Capabilities and opportunities","volume":"209","author":"Sabaghy","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1002\/2016RG000543","article-title":"A review of spatial downscaling of satellite remotely sensed soil moisture","volume":"55","author":"Peng","year":"2017","journal-title":"Rev. Geophys."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"704","DOI":"10.1109\/JPROC.2010.2043918","article-title":"The soil moisture active passive (SMAP) mission","volume":"98","author":"Entekhabi","year":"2010","journal-title":"Proc. IEEE"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.earscirev.2010.02.004","article-title":"Investigating soil moisture-climate interactions in a changing climate: A review","volume":"99","author":"Seneviratne","year":"2010","journal-title":"Earth Sci. Rev."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Collow, T.W., Robock, A., Basara, J.B., and Illston, B.G. (2012). Evaluation of SMOS retrievals of soil moisture over the central United States with currently available in situ observations. J. Geophys. Res. Atmosph., 117.","DOI":"10.1029\/2011JD017095"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Crow, W.T., Berg, A.A., Cosh, M.H., Loew, A., Mohanty, B.P., Panciera, R., de Rosnay, P., Ryu, D., and Walker, J.P. (2012). Upscaling sparse ground-based soil moisture observations for the validation of coarse-resolution satellite soil moisture products. Rev. Geophys., 50.","DOI":"10.1029\/2011RG000372"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1002","DOI":"10.2136\/vzj2009.0173","article-title":"Potential of wireless sensor networks for measuring soil water content variability","volume":"9","author":"Bogena","year":"2010","journal-title":"Vadose Zone J."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2015","DOI":"10.1109\/LGRS.2014.2319085","article-title":"A nested ecohydrological wireless sensor network for capturing the surface heterogeneity in the midstream areas of the Heihe River basin, China","volume":"11","author":"Jin","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1002\/hyp.6609","article-title":"Operational performance of current synthetic aperture radar sensors in mapping soil surface characteristics in agricultural environments: Application to hydrological and erosion modelling","volume":"22","author":"Baghdadi","year":"2008","journal-title":"Hydrol. Proc. Int. J."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"El Hajj, M., Baghdadi, N., Zribi, M., Rodr\u00edguez-Fern\u00e1ndez, N., Wigneron, J.P., Al-Yaari, A., Al Bitar, A., Albergel, C., and Calvet, J. (2018). Evaluation of SMOS, SMAP, ASCAT and Sentinel-1 soil moisture products at sites in Southwestern France. Remote Sens., 10.","DOI":"10.3390\/rs10040569"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.rse.2013.02.027","article-title":"Soil moisture mapping using Sentinel-1 images: Algorithm and preliminary validation","volume":"134","author":"Paloscia","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.rse.2017.01.024","article-title":"Modelling the passive microwave signature from land surfaces: A review of recent results and application to the L-band SMOS & SMAP soil moisture retrieval algorithms","volume":"192","author":"Wigneron","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1729","DOI":"10.1109\/36.942551","article-title":"Soil moisture retrieval from space: The Soil Moisture and Ocean Salinity (SMOS) mission","volume":"39","author":"Kerr","year":"2001","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1612","DOI":"10.3390\/s7081612","article-title":"An overview of the \u201cTriangle Method\u201d for estimating surface evapotranspiration and soil moisture from satellite imagery","volume":"7","author":"Carlson","year":"2007","journal-title":"Sensors"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1080\/02757259409532220","article-title":"A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover","volume":"9","author":"Carlson","year":"1994","journal-title":"Remote Sens. Rev."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3156","DOI":"10.1109\/TGRS.2011.2120615","article-title":"Downscaling SMOS-derived soil moisture using modis visible\/infrared data","volume":"49","author":"Piles","year":"2011","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"4599","DOI":"10.1080\/0143116031000156837","article-title":"Spaceborne soil moisture estimation at high resolution: A microwave-optical\/IR synergistic approach","volume":"24","author":"Chauhan","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Xu, C., Qu, J.J., Hao, X., Cosh, M.H., Prueger, J.H., Zhu, Z., and Gutenberg, L. (2018). Downscaling of surface soil moisture retrieval by combining MODIS\/Landsat and in situ measurements. Remote Sens., 10.","DOI":"10.3390\/rs10020210"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"558","DOI":"10.1109\/TGRS.2015.2462074","article-title":"Spatial downscaling of satellite soil moisture data using a vegetation temperature condition index","volume":"54","author":"Peng","year":"2016","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/j.jhydrol.2013.12.047","article-title":"Combining SMOS with visible and near\/shortwave\/thermal infrared satellite data for high resolution soil moisture estimates","volume":"516","author":"Piles","year":"2014","journal-title":"J. Hydrol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2136\/vzj2013.05.0089","article-title":"Passive microwave soil moisture downscaling using vegetation index and skin surface temperature","volume":"12","author":"Fang","year":"2013","journal-title":"Vadose Zone J."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1109\/TGRS.2011.2161318","article-title":"Improving spatial soil moisture representation through integration of AMSR-E and MODIS products","volume":"50","author":"Kim","year":"2012","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1693","DOI":"10.1016\/j.agrformet.2009.05.011","article-title":"A general approach to estimate soil water content from thermal inertia","volume":"149","author":"Lu","year":"2009","journal-title":"Agr. Forest Meteorol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3567","DOI":"10.1080\/01431160601034886","article-title":"Soil moisture retrieval from MODIS data in Northern China Plain using thermal inertia model","volume":"28","author":"Cai","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","first-page":"752","article-title":"Estimation of root zone soil moisture using apparent thermal inertia with MODIS imagery over a tropical catchment in Northern Thailand","volume":"5","author":"Chang","year":"2012","journal-title":"IEEE J. STARS."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Scheidt, S., Ramsey, M., and Lancaster, N. (2010). Determining soil moisture and sediment availability at White Sands Dune Field, New Mexico, from apparent thermal inertia data. J. Geophys.Res. Earth Surf., 115.","DOI":"10.1029\/2009JF001378"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1157","DOI":"10.3724\/SP.J.1011.2011.01157","article-title":"Monitoring soil moisture by apparent thermal inertia method","volume":"19","author":"Yang","year":"2011","journal-title":"Chin J. Eco Agric."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2013.07.003","article-title":"Spatial upscaling of in-situ soil moisture measurements based on MODIS-derived apparent thermal inertia","volume":"138","author":"Qin","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3870","DOI":"10.1080\/01431161.2011.636080","article-title":"Soil moisture content retrieval based on apparent thermal inertia for Xinjiang province in China","volume":"33","author":"Veroustraete","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","first-page":"934","article-title":"The potential of multitemporal Aqua and Terra MODIS apparent thermal inertia as a soil moisture indicator","volume":"13","author":"Peters","year":"2011","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Kova\u010devi\u0107, J., Cvijetinovi\u0107, Z., Stan\u010di\u0107, N., Brodi\u0107, N., and Mihajlovi\u0107, D. (2020). New downscaling approach using ESA CCI SM products for obtaining high resolution surface soil moisture. Remote Sens., 12.","DOI":"10.3390\/rs12071119"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1029\/2018WR023354","article-title":"Downscaling SMAP radiometer soil moisture over the CONUS using an ensemble learning method","volume":"55","author":"Abbaszadeh","year":"2019","journal-title":"Water Resour. Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1120","DOI":"10.1007\/s12665-016-5917-6","article-title":"Downscaling of AMSR-E soil moisture with MODIS products using machine learning approaches","volume":"75","author":"Im","year":"2016","journal-title":"Environ. Earth Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2036","DOI":"10.1109\/TGRS.2005.853192","article-title":"A combined modeling and multispectral\/multiresolution remote sensing approach for disaggregation of surface soil moisture: Application to SMOS configuration","volume":"43","author":"Merlin","year":"2005","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"786","DOI":"10.1109\/TGRS.2007.914807","article-title":"A simple method to disaggregate passive microwave-based soil moisture","volume":"46","author":"Merlin","year":"2008","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"3935","DOI":"10.1016\/j.rse.2008.06.012","article-title":"Towards deterministic downscaling of SMOS soil moisture using MODIS derived soil evaporative efficiency","volume":"112","author":"Merlin","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2107","DOI":"10.1109\/LGRS.2017.2753203","article-title":"Spatial downscaling of SMAP soil moisture using MODIS land surface temperature and NDVI during SMAPVEX15","volume":"14","author":"Colliander","year":"2017","journal-title":"IEEE Geosci. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/j.rse.2016.02.045","article-title":"SMOS disaggregated soil moisture product at 1 km resolution: Processor overview and first validation results","volume":"180","author":"Molero","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_39","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_40","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_41","doi-asserted-by":"crossref","first-page":"123","DOI":"10.2166\/nh.1991.0009","article-title":"Principles and confidence in hydrological modelling","volume":"22","year":"1991","journal-title":"Hydrol. Res."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1138","DOI":"10.1126\/science.1100217","article-title":"Regions of strong coupling between soil moisture and precipitation","volume":"305","author":"Koster","year":"2004","journal-title":"Science"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"18987","DOI":"10.1029\/92JD00882","article-title":"Soil moisture variability within remote sensing pixels","volume":"97","author":"Groffman","year":"1992","journal-title":"J Geophys Res."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"873","DOI":"10.1016\/j.jhydrol.2016.07.005","article-title":"Spatial-temporal variability of soil water content in a cropland-shelterbelt-desert site in an arid inland river basin of Northwest China","volume":"540","author":"Shen","year":"2016","journal-title":"J. Hydrol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1007\/s12665-010-0716-y","article-title":"Spatial variability of soil moisture at typical alpine meadow and steppe sites in the Qinghai-Tibetan Plateau permafrost region","volume":"63","author":"Yang","year":"2011","journal-title":"Environ. Earth Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1002\/2014GL062496","article-title":"Predicting subgrid variability of soil water content from basic soil information","volume":"42","author":"Qu","year":"2015","journal-title":"Geophys. Res. Lett."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"892","DOI":"10.2136\/sssaj1980.03615995004400050002x","article-title":"A closed-form equation for predicting the hydraulic conductivity of unsaturated soils 1","volume":"44","year":"1980","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Montzka, C., R\u00f6tzer, K., Bogena, H.R., Sanchez, N., and Vereecken, H. (2018). A new soil moisture downscaling approach for SMAP, SMOS, and ASCAT by predicting sub-grid variability. Remote Sens., 10.","DOI":"10.3390\/rs10030427"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1175\/BAMS-D-12-00154.1","article-title":"Heihe watershed allied telemetry experimental research (HiWATER): Scientific objectives and experimental design","volume":"94","author":"Li","year":"2013","journal-title":"B. Am. Meteorol. Soc."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1016\/j.rse.2017.01.027","article-title":"High spatio-temporal resolution mapping of soil moisture by integrating wireless sensor network observations and MODIS apparent thermal inertia in the Babao River Basin, China","volume":"191","author":"Kang","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.jhydrol.2011.11.056","article-title":"The response of soil moisture to rainfall event size in subalpine grassland and meadows in a semi-arid mountain range: A case study in northwestern China\u2019s Qilian Mountains","volume":"420","author":"He","year":"2012","journal-title":"J. Hydrol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1007\/s00254-006-0251-z","article-title":"The impact of the development of water resources on environment in arid inland river basins of Hexi region, Northwestern China","volume":"50","author":"Ji","year":"2006","journal-title":"Environ Geol."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Chaubell, J., Yueh, S., Entekhabi, D., and Peng, J. (2016, January 11\u201315). Resolution enhancement of SMAP radiometer data using the Backus Gilbert optimum interpolation technique. Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, Beijing, China.","DOI":"10.1109\/IGARSS.2016.7729065"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"904","DOI":"10.1175\/JHM-D-14-0034.1","article-title":"Modeling regional crop yield and irrigation demand using SMAP type of soil moisture data","volume":"16","author":"Wang","year":"2015","journal-title":"J. Hydrometeorol."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"727","DOI":"10.1175\/JHM-D-17-0228.1","article-title":"Improved hydrological simulation using SMAP data: Relative impacts of model calibration and data assimilation","volume":"19","author":"Koster","year":"2018","journal-title":"J. Hydrometeorol."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Holmes, T.R., Jackson, T.J., Reichle, R.H., and Basara, J.B. (2012). An assessment of surface soil temperature products from numerical weather prediction models using ground-based measurements. Water Resour. Res., 48.","DOI":"10.1029\/2011WR010538"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"931","DOI":"10.1016\/j.rse.2017.08.025","article-title":"Development and assessment of the SMAP enhanced passive soil moisture product","volume":"204","author":"Chan","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Cui, C., Xu, J., Zeng, J., Chen, K., Bai, X., Lu, H., Chen, Q., and Zhao, T. (2018). Soil moisture mapping from satellites: An intercomparison of SMAP, SMOS, FY3B, AMSR2, and ESA CCI over two dense network regions at different spatial scales. Remote Sens., 10.","DOI":"10.3390\/rs10010033"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1394","DOI":"10.1109\/TGRS.2017.2762462","article-title":"Soil moisture retrieval from SMAP: A validation and error analysis study using ground-based observations over the little Washita watershed","volume":"56","author":"Chen","year":"2017","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_60","unstructured":"O\u2019Neill, P., Chan, S., Njoku, E., Jackson, T., and Bindlish, R. (2018). Algorithm Theoretical Basis Document Level 2 & 3 Soil Moisture (Passive) Data Products, California Institute of Technology. Tom. JPL D-66480."},{"key":"ref_61","unstructured":"Entekhabi, D., Yueh, S., O Neill, P., Kellogg, K., Allen, A., Bindlish, R., Brown, M., Chan, S., Colliander, A., and Crow, W.T. (2014). SMAP Handbook, California Institute of Technology. JPL Publication JPL 400-1567."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Zhang, L., He, C., and Zhang, M. (2017). Multi-scale evaluation of the SMAP product using sparse in-situ network over a high mountainous watershed, Northwest China. Remote Sens., 9.","DOI":"10.3390\/rs9111111"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/S0022-1694(01)00466-8","article-title":"Rosetta: A computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions","volume":"251","author":"Schaap","year":"2001","journal-title":"J. Hydrol."},{"key":"ref_64","unstructured":"Fischer, G., Nachtergaele, F., Prieler, S., Van Velthuizen, H.T., Verelst, L., and Wiberg, D. (2008). Global Agro-Ecological Zones Assessment for Agriculture (GAEZ 2008), FAO."},{"key":"ref_65","first-page":"9477","article-title":"Impacts of human activities and climate variability on green and blue water flows in the Heihe River Basin in Northwest China","volume":"10","author":"Zang","year":"2013","journal-title":"Hydrol. Earth Syst. Sci Discuss."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"3086","DOI":"10.3390\/su7033086","article-title":"Scenario analysis for water resources in response to land use change in the middle and upper reaches of the Heihe River Basin","volume":"7","author":"Li","year":"2015","journal-title":"Sustainability"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.pce.2014.12.001","article-title":"Multilevel modeling of NPP change and impacts of water resources in the Lower Heihe River Basin","volume":"79","author":"Yan","year":"2015","journal-title":"Phys. Chem. Earth Parts ABC"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2136\/vzj2018.04.0072","article-title":"The heihe integrated observatory network: A basin-scale land surface processes observatory in China","volume":"17","author":"Liu","year":"2018","journal-title":"Vadose Zone J."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"832","DOI":"10.2136\/vzj2010.0134","article-title":"Temporal dynamics of soil moisture spatial variability in the Shale Hills Critical Zone Observatory","volume":"10","author":"Takagi","year":"2011","journal-title":"Vadose Zone J."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Teuling, A.J. (2005). Improved understanding of soil moisture variability dynamics. Geophys. Res. Lett., 32.","DOI":"10.1029\/2004GL021935"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"5341","DOI":"10.5194\/hess-22-5341-2018","article-title":"Global downscaling of remotely sensed soil moisture using neural networks","volume":"22","author":"Alemohammad","year":"2018","journal-title":"Hydrol. Earth Syst. Sc."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Zappa, L., Forkel, M., Xaver, A., and Dorigo, W. (2019). Deriving field scale soil moisture from satellite observations and ground measurements in a hilly agricultural region. Remote Sens., 11.","DOI":"10.3390\/rs11222596"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"1437","DOI":"10.1029\/98WR00317","article-title":"Stochastic analysis of steady-state unsaturated flow in heterogeneous media: Comparison of the Brooks-Corey and Gardner-Russo models","volume":"34","author":"Zhang","year":"1998","journal-title":"Water Resour. Res."},{"key":"ref_74","first-page":"37","article-title":"Hydraulic properties of porous media","volume":"24","author":"Brooks","year":"1964","journal-title":"Hydrol. Pap. Colorado State Univ."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1029\/WR024i003p00453","article-title":"Determining soil hydraulic properties by parameter estimation: On the selection of a model for the hydraulic properties","volume":"24","author":"Russo","year":"1988","journal-title":"Water Resour. Res."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/S0034-4257(00)00205-4","article-title":"Narrowband to broadband conversions of land surface albedo I: Algorithms","volume":"76","author":"Liang","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"9445","DOI":"10.1029\/1998JD200109","article-title":"Combining afternoon and morning NOAA satellites for thermal inertia estimation: 1. Algorithm and its testing with hydrologic atmospheric pilot experiment-Sahel data","volume":"104","author":"Sobrino","year":"1999","journal-title":"J. Geophys. Res. Atmosp."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"832","DOI":"10.1175\/2010JHM1223.1","article-title":"Performance metrics for soil moisture retrievals and application requirements","volume":"11","author":"Entekhabi","year":"2010","journal-title":"J. Hydrometeorol."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"111806","DOI":"10.1016\/j.rse.2020.111806","article-title":"Validation practices for satellite soil moisture retrievals: What are (the) errors?","volume":"244","author":"Gruber","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"3783","DOI":"10.3390\/rs70403783","article-title":"Performance metrics for soil moisture downscaling methods: Application to DISPATCH data in central Morocco","volume":"7","author":"Merlin","year":"2015","journal-title":"Remote Sens."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"6938","DOI":"10.1175\/JCLI-D-14-00754.1","article-title":"Bias correction of GCM precipitation by quantile mapping: How well do methods preserve changes in quantiles and extremes?","volume":"28","author":"Cannon","year":"2015","journal-title":"J. Climate"},{"key":"ref_82","doi-asserted-by":"crossref","unstructured":"Ringard, J., Seyler, F., and Linguet, L. (2017). A quantile mapping bias correction method based on hydroclimatic classification of the Guiana shield. Sensors, 17.","DOI":"10.3390\/s17061413"},{"key":"ref_83","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_84","doi-asserted-by":"crossref","unstructured":"Reichle, R.H., and Koster, R.D. (2004). Bias reduction in short records of satellite soil moisture. Geophys. Res. Lett., 31.","DOI":"10.1029\/2004GL020938"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"2742","DOI":"10.1360\/N972015-01237","article-title":"Active layer seasonal freeze-thaw processes and influencing factors in the alpine permafrost regions in the upper reaches of the Heihe River in Qilian Mountains","volume":"61","author":"Wang","year":"2016","journal-title":"Chin. Sci. Bull."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2136\/vzj2015.11.0143","article-title":"Spatial and temporal variability of soil water content in two regions of southwest Germany during a three-year observation period","volume":"15","author":"Poltoradnev","year":"2016","journal-title":"Vadose Zone J."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"576","DOI":"10.1016\/j.jhydrol.2015.03.019","article-title":"Investigating soil controls on soil moisture spatial variability: Numerical simulations and field observations","volume":"524","author":"Wang","year":"2015","journal-title":"J. Hydrol."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/S0022-1694(98)00187-5","article-title":"Variability in surface moisture content along a hillslope transect: Rattlesnake Hill, Texas","volume":"210","author":"Famiglietti","year":"1998","journal-title":"J. Hydrol."},{"key":"ref_89","doi-asserted-by":"crossref","unstructured":"Gao, B., Qin, Y., Wang, Y., Yang, D., and Zheng, Y. (2016). Modeling ecohydrological processes and spatial patterns in the upper Heihe basin in China. Forests, 7.","DOI":"10.3390\/f7010010"},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"1325","DOI":"10.5194\/hess-13-1325-2009","article-title":"Controls on the temporal and spatial variability of soil moisture in a mountainous landscape: The signature of snow and complex terrain","volume":"13","author":"Williams","year":"2009","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_91","doi-asserted-by":"crossref","unstructured":"Song, C., and Jia, L. (2016). A Method for Downscaling FengYun-3B Soil Moisture Based on Apparent Thermal Inertia. Remote Sens., 8.","DOI":"10.3390\/rs8090703"},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1002\/hyp.11039","article-title":"Factors affecting soil moisture spatial variability for a humid forest hillslope","volume":"31","author":"Gwak","year":"2017","journal-title":"Hydrol. Process."},{"key":"ref_93","doi-asserted-by":"crossref","unstructured":"Vereecken, H., Kamai, T., Harter, T., Kasteel, R., Hopmans, J., and Vanderborght, J. (2007). Explaining soil moisture variability as a function of mean soil moisture: A stochastic unsaturated flow perspective. Geophys. Res. Lett., 34.","DOI":"10.1029\/2007GL031813"},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"2362","DOI":"10.1109\/TGRS.2017.2778420","article-title":"Downscaling AMSR-2 soil moisture data with geographically weighted area-to-area regression kriging","volume":"56","author":"Jin","year":"2017","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"6208","DOI":"10.1002\/wrcr.20495","article-title":"Development of a deterministic downscaling algorithm for remote sensing soil moisture footprint using soil and vegetation classifications","volume":"49","author":"Shin","year":"2013","journal-title":"Water Resour. Res."},{"key":"ref_96","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_97","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1175\/JHM-D-12-092.1","article-title":"Global calibration of the GEOS-5 L-band microwave radiative transfer model over nonfrozen land using SMOS observations","volume":"14","author":"Reichle","year":"2013","journal-title":"J. Hydrometeorol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/3\/509\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:18:00Z","timestamp":1760159880000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/3\/509"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,31]]},"references-count":97,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2021,2]]}},"alternative-id":["rs13030509"],"URL":"https:\/\/doi.org\/10.3390\/rs13030509","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,31]]}}}