{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T08:01:29Z","timestamp":1780732889525,"version":"3.54.1"},"reference-count":57,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2020,11,13]],"date-time":"2020-11-13T00:00:00Z","timestamp":1605225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"ERANETMED","award":["Real-Time Soil Moisture Forecast for Smart Irrigation (RET-SIF)"],"award-info":[{"award-number":["Real-Time Soil Moisture Forecast for Smart Irrigation (RET-SIF)"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Numerous Surface Soil Moisture (SSM) products are available from remote sensing, encompassing different spatial, temporal, and radiometric resolutions and retrieval techniques. Notwithstanding this variety, all products should be coherent with water inputs. In this work, we have cross-compared precipitation and irrigation with different SSM products: Soil Moisture Ocean Salinity (SMOS), Soil Moisture Active Passive (SMAP), European Space Agency (ESA) Climate Change Initiative (ESA-CCI) products, Copernicus SSM1km, and Advanced Microwave Scanning Radiometer 2 (AMSR2). The products have been analyzed over two agricultural sites in Italy (Chiese and Capitanata Irrigation Consortia). A Hydrological Consistency Index (HCI) is proposed as a means to measure the coherency between SSM and precipitation\/irrigation. Any time SSM is available, a positive or negative consistency is recorded, according to the rainfall registered since the previous measurement and the increase\/decrease of SSM. During the irrigation season, some agreements are labeled as \u201cirrigation-driven\u201d. No SSM dataset stands out for a systematic hydrological coherence with the rainfall. Negative consistencies cluster just below 50% in the non-irrigation period and lose 20\u201330% in the irrigation period. Hybrid datasets perform better (+15\u201320%) than single-technology measurements, among which active data provide slightly better results (+5\u201310%) than passive data.<\/jats:p>","DOI":"10.3390\/rs12223737","type":"journal-article","created":{"date-parts":[[2020,11,13]],"date-time":"2020-11-13T08:44:02Z","timestamp":1605257042000},"page":"3737","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Irrigation and Precipitation Hydrological Consistency with SMOS, SMAP, ESA-CCI, Copernicus SSM1km, and AMSR-2 Remotely Sensed Soil Moisture Products"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4580-7505","authenticated-orcid":false,"given":"Nicola","family":"Paciolla","sequence":"first","affiliation":[{"name":"Department of Civil and Environmental Engineering (DICA), Polytechnic University of Milan, 20133 Milano, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chiara","family":"Corbari","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering (DICA), Polytechnic University of Milan, 20133 Milano, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmad","family":"Al Bitar","sequence":"additional","affiliation":[{"name":"CESBIO, CNES, CNRS, IRD, University of Toulouse, 18 avenue Edouard Belin, BPI 2801, CEDEX 9, 31401 Toulouse, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6352-1717","authenticated-orcid":false,"given":"Yann","family":"Kerr","sequence":"additional","affiliation":[{"name":"CESBIO, CNES, CNRS, IRD, University of Toulouse, 18 avenue Edouard Belin, BPI 2801, CEDEX 9, 31401 Toulouse, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco","family":"Mancini","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering (DICA), Polytechnic University of Milan, 20133 Milano, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"639","DOI":"10.5194\/hess-13-639-2009","article-title":"Elevation based correction of snow coverage retrieved from satellite images tom improve model calibration","volume":"13","author":"Corbari","year":"2009","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"85","DOI":"10.5194\/hess-6-85-2002","article-title":"The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes","volume":"6","author":"Su","year":"2002","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1175\/JHM-D-12-0173.1","article-title":"Calibration and Validation of a Distributed Energy-Water Balance Model Using Satellite Data of Land Surface Temperature and Ground Discharge Measurements","volume":"15","author":"Corbari","year":"2014","journal-title":"J. Hydrometeorol."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Xu, W., Ren, X., and Smith, A. (2011, January 24\u201326). Remote Sensing, Crop Yield Estimation and Agricultural Vulnerability Assessment: A Case of Southern Alberta. Proceedings of the 19th International Conference on Geoinformatics, Shanghai, China.","DOI":"10.1109\/GeoInformatics.2011.5980692"},{"key":"ref_5","first-page":"817408","article-title":"River discharge estimation through MODIS data","volume":"8174","author":"Tarpanelli","year":"2011","journal-title":"SPIE Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Joshi, N., Baumann, M., Ehammer, A., Fensholt, R., Grogan, K., Hostert, P., Jepsen, M.R., Kuemmerle, T., Meyfroidt, P., and Mitchard, E.T.A. (2016). A Review of the Application of Optical and Radar Remote Sensing Data Fusion to Land Use Mapping and Monitoring. Remote Sens., 8.","DOI":"10.3390\/rs8010070"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1029\/2011EO170001","article-title":"A New International Network for in Situ Soil Moisture Data","volume":"92","author":"Dorigo","year":"2011","journal-title":"Eos Trans."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3845","DOI":"10.1109\/JSTARS.2014.2325398","article-title":"A Downscaling Approach for SMOS Land Observations: Evaluation of High-Resolution Soil Moisture Maps Over the Iberian Peninsula","volume":"7","author":"Piles","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_9","unstructured":"Grayson, R., and Bl\u00f6schl, G. (2000). Spatial Patterns in Catchment Hydrology: Observations and Modelling, Cambridge University Press."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1888","DOI":"10.2136\/sssaj2013.03.0093","article-title":"State of the Art in Large-Scale Soil Moisture Monitoring","volume":"77","author":"Ochsner","year":"2013","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1002\/2017JD027478","article-title":"Multi-Timescale Analysis of the Spatial Representativeness of In Situ Soil Moisture Data within Satellite Footprints","volume":"123","author":"Molero","year":"2018","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2136\/vzj2016.10.0105","article-title":"Soil Moisture Remote Sensing: State-of-the-Science","volume":"16","author":"Mohanty","year":"2017","journal-title":"Vadose Zone J."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Das, K., and Paul, P.K. (2015). Present status of soil moisture estimation by microwave remote sensing. Cogent Geosci., 1.","DOI":"10.1080\/23312041.2015.1084669"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"28001","DOI":"10.1117\/1.3534910","article-title":"Review and evaluation of remote sensing methods for soil-moisture estimation","volume":"2","author":"Nichols","year":"2011","journal-title":"J. Photon. Energy"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Raschke, E. (1996). Remote Sensing of Soil Moisture. Radiation and Water in the Climate System, Springer.","DOI":"10.1007\/978-3-662-03289-3"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/0022-1694(95)02970-2","article-title":"Passive microwave remote sensing of soil moisture","volume":"184","author":"Njoku","year":"1996","journal-title":"J. Hydrol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1384","DOI":"10.1109\/TGRS.2012.2184548","article-title":"The SMOS Soil Moisture Retrieval Algorithm","volume":"50","author":"Kerr","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_18","first-page":"27","article-title":"A new calibration of the effective scattering albedo and soil roughness parameters in the SMOS SM retrieval algorithm","volume":"62","author":"Wigneron","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Tomer, S.K., Al Bitar, A., Sekhar, M., Zribi, M., Bandyopadhyay, S., and Kerr, Y.H. (2016). MAPSM: A Spatio-Temporal Algorithm for Merging Soil Moisture from Active and Passive Microwave Remote Sensing. Remote Sens., 8.","DOI":"10.3390\/rs8120990"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1175\/JHM-D-16-0280.1","article-title":"Toward a Surface Soil Moisture Product at High Spatiotemporal Resolution: Temporally Interpolated, Spatially Disaggregated SMOS Data","volume":"19","author":"Merlin","year":"2018","journal-title":"J. Hydrometeorol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3383","DOI":"10.1080\/014311600750020000","article-title":"Developments in the \u2019validation\u2019 of satellite sensor products for the study of the land surface","volume":"21","author":"Justice","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"4256","DOI":"10.1109\/TGRS.2010.2051035","article-title":"Validation of Advanced Microwave Scanning Radiometer Soil Moisture Products","volume":"48","author":"Jackson","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/j.rse.2017.01.021","article-title":"Validation of SMAP surface soil moisture products with core validation sites","volume":"191","author":"Colliander","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3390","DOI":"10.1016\/j.rse.2011.08.003","article-title":"Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe","volume":"115","author":"Brocca","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1572","DOI":"10.1109\/TGRS.2012.2186581","article-title":"Evaluation of SMOS Soil Moisture Products Over Continental, U.S. Using the SCAN\/SNOTEL Network","volume":"50","author":"Leroux","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.rse.2016.02.042","article-title":"Overview of SMOS performance in terms of global soil moisture monitoring after six years in operation","volume":"180","author":"Kerr","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Cui, C., Xu, J., Zeng, J., Chen, K.-S., Bai, X., Lu, H., Chen, Q., and Zhao, T. (2017). 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_28","doi-asserted-by":"crossref","unstructured":"El Hajj, M., Baghdadi, N., Zribi, M., Rodr\u00edguez-Fern\u00e1ndez, N.J., Wigneron, J.-P., Al-Yaari, A., Al Bitar, A., Albergelb, C., and Albergel, C. (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_29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2018.05.008","article-title":"Global-scale evaluation of SMAP, SMOS and ASCAT soil moisture products using triple collocation","volume":"214","author":"Chen","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_30","first-page":"200","article-title":"Recent advances in (soil moisture) triple collocation analysis","volume":"45","author":"Gruber","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1016\/j.rse.2014.07.014","article-title":"Spectral detection of near-surface moisture content and water-table position in northern peatland ecosystems","volume":"152","author":"Meingast","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_32","first-page":"752","article-title":"How much water is used for irrigation? A new approach exploiting coarse resolution satellite soil moisture products","volume":"73","author":"Brocca","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"11860","DOI":"10.1002\/2017GL075733","article-title":"Irrigation Signals Detected From SMAP Soil Moisture Retrievals","volume":"44","author":"Lawston","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Zhang, X., Qiu, J., Leng, G., Yang, Y., Gao, Q., Fan, Y., and Luo, J. (2018). The Potential Utility of Satellite Soil Moisture Retrievals for Detecting Irrigation Patterns in China. Water, 10.","DOI":"10.3390\/w10111505"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"897","DOI":"10.5194\/hess-23-897-2019","article-title":"Estimating irrigation water use over the contiguous United States by combining satellite and reanalysis soil moisture data","volume":"23","author":"Zaussinger","year":"2019","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2451","DOI":"10.1175\/1520-0442(1999)012<2451:EOCSMP>2.0.CO;2","article-title":"Effects of Clouds, Soil Moisture, Precipitation, and Water Vapour on Diurnal Temperature Range","volume":"12","author":"Dai","year":"1999","journal-title":"J. Clim."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1111\/j.1936-704X.2019.03324.x","article-title":"Investigating Relationship Between Soil Moisture and Precipitation Globally Using Remote Sensing Observations","volume":"168","author":"Sehler","year":"2019","journal-title":"J. Contemp. Water Res. Educ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1016\/j.rse.2007.03.027","article-title":"Hydrological consistency using multi-sensor remote sensing data for water and energy cycle studies","volume":"112","author":"McCabe","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"4157","DOI":"10.1007\/s00382-017-3646-5","article-title":"Detecting hydrological consistency between soil moisture and precipitation and changes of soil moisture in summer over the Tibetan Plateau","volume":"51","author":"Meng","year":"2017","journal-title":"Clim. Dyn."},{"key":"ref_40","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_41","unstructured":"(2020, August 07). Agenzia Regionale per la Prevenzione e la Protezione dell\u2019Ambiente (ARPA) Puglia. Available online: http:\/\/www.arpa.puglia.it\/web\/guest\/serviziometeo."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"666","DOI":"10.1109\/JPROC.2010.2043032","article-title":"The SMOS Mission: New Tool for Monitoring Key Elements ofthe Global Water Cycle","volume":"98","author":"Kerr","year":"2010","journal-title":"Proc. IEEE"},{"key":"ref_43","unstructured":"Ulaby, F.T., Moore, M.K., and Fung, A.K. (1982). Microwave Remote Sensing, Active and Passive, Artech House."},{"key":"ref_44","unstructured":"(2020, August 07). SMOS Level 2 Processor Soil Moisture ATBD from ESA Earth Online. Available online: https:\/\/earth.esa.int\/documents\/10174\/1854519\/SMOS_L2_SM_ATBD."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"293","DOI":"10.5194\/essd-9-293-2017","article-title":"The global SMOS Level 3 daily soil moisture and brightness temperature maps","volume":"9","author":"Mialon","year":"2017","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_46","unstructured":"Laboratory, J.P. (2014). SMAP Handbook\u2014Soil Moisture Active Passive\u2014Mapping Soil Moisture and Freeze\/Thaw from Space, JPL Publication."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"717","DOI":"10.5194\/essd-11-717-2019","article-title":"Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology","volume":"11","author":"Gruber","year":"2019","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_48","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_49","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1016\/j.rse.2012.03.014","article-title":"Trend-preserving blending of passive and active microwave soil moisture retrievals","volume":"123","author":"Liu","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"6780","DOI":"10.1109\/TGRS.2017.2734070","article-title":"Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals","volume":"55","author":"Gruber","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_51","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_52","doi-asserted-by":"crossref","unstructured":"Bauer-Marschallinger, B., Paulik, C., Hochst\u00f6ger, S., Mistelbauer, T., Modanesi, S., Ciabatta, L., Massari, C., Brocca, L., and Wagner, W. (2018). Soil Moisture from Fusion of Scatterometer and SAR: Closing the Scale Gap with Temporal Filtering. Remote Sens., 10.","DOI":"10.3390\/rs10071030"},{"key":"ref_53","unstructured":"Bill, T. (2014). AMSR2\/GCOM-W1 Surface Soil Moisture (LPRM) L3 1 Day 10 km \u00d7 10 km Descending V001, Goddard Earth Sciences Data and Information Services Center (GES DISC)."},{"key":"ref_54","unstructured":"Scanlon, T., Dorigo, W., Preimesberger, W., Kidd, R., van der Schalie, R., de Jeu, R., and Thevenon, H. (2020, November 10). Algorithm Development Plan (ADP)\u2014D1.2 Version 0.1. 2019, deliverable D1.2 ADP for the ESA Climate Change Initiative Plus Soil Moisture Project (ESRIN Contract no: 4000126684\/19\/I-NB). Available online: https:\/\/www.esa-soilmoisture-cci.org\/sites\/default\/files\/documents\/ESA_CCI_SM_ADP_version_1.0.pdf."},{"key":"ref_55","unstructured":"Bauer-Marschallinger, B., and Paulik, C. (2020, November 10). Product user manual\u2014Surface Soil Moisture\u2014Collection 1 km\u2014Version 1. 2019 Copernicus Land Operations \u201cVegetation and Energy\u201d, Date Issued: 08\/04\/2020. Available online: https:\/\/land.copernicus.eu\/global\/sites\/cgls.vito.be\/files\/products\/CGLOPS1_PUM_SWI1km-V1_I1.20.pdf."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1016\/j.rse.2005.10.017","article-title":"Vegetation and surface roughness effects on AMSR-E land observations","volume":"100","author":"Njoku","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_57","first-page":"47","article-title":"Effect of vegetation index choice on soil moisture retrievals via the synergistic use of synthetic aperture radar and optical remote sensing","volume":"80","author":"Qiu","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/22\/3737\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:33:01Z","timestamp":1760178781000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/22\/3737"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,13]]},"references-count":57,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2020,11]]}},"alternative-id":["rs12223737"],"URL":"https:\/\/doi.org\/10.3390\/rs12223737","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,13]]}}}