{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T06:18:16Z","timestamp":1775024296738,"version":"3.50.1"},"reference-count":153,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2021,10,14]],"date-time":"2021-10-14T00:00:00Z","timestamp":1634169600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000844","name":"European Space Agency","doi-asserted-by":"publisher","award":["4000129870\/20\/I-NB"],"award-info":[{"award-number":["4000129870\/20\/I-NB"]}],"id":[{"id":"10.13039\/501100000844","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Irrigation represents one of the most impactful human interventions in the terrestrial water cycle. Knowing the distribution and extent of irrigated areas as well as the amount of water used for irrigation plays a central role in modeling irrigation water requirements and quantifying the impact of irrigation on regional climate, river discharge, and groundwater depletion. Obtaining high-quality global information about irrigation is challenging, especially in terms of quantification of the water actually used for irrigation. Here, we review existing Earth observation datasets, models, and algorithms used for irrigation mapping and quantification from the field to the global scale. The current observation capacities are confronted with the results of a survey on user requirements on satellite-observed irrigation for agricultural water resources\u2019 management. Based on this information, we identify current shortcomings of irrigation monitoring capabilities from space and phrase guidelines for potential future satellite missions and observation strategies.<\/jats:p>","DOI":"10.3390\/rs13204112","type":"journal-article","created":{"date-parts":[[2021,10,14]],"date-time":"2021-10-14T23:02:16Z","timestamp":1634252536000},"page":"4112","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":126,"title":["A Review of Irrigation Information Retrievals from Space and Their Utility for Users"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0983-1276","authenticated-orcid":false,"given":"Christian","family":"Massari","sequence":"first","affiliation":[{"name":"Research Institute for the Geo-Hydrological Protection, National Research Council (CNR), Via Madonna Alta 126, 06128 Perugia, Italy"}]},{"given":"Sara","family":"Modanesi","sequence":"additional","affiliation":[{"name":"Research Institute for the Geo-Hydrological Protection, National Research Council (CNR), Via Madonna Alta 126, 06128 Perugia, Italy"},{"name":"Department of Earth and Environmental Sciences, KU Leuven, Celestijnenlaan 200e, 3001 Leuven, Belgium"},{"name":"Department of Civil and Environmental Engineering (DICEA), University of Florence, Via di S. Marta 3, 50139 Firenze, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2740-5270","authenticated-orcid":false,"given":"Jacopo","family":"Dari","sequence":"additional","affiliation":[{"name":"Research Institute for the Geo-Hydrological Protection, National Research Council (CNR), Via Madonna Alta 126, 06128 Perugia, Italy"},{"name":"Department of Civil and Environmental Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3280-7023","authenticated-orcid":false,"given":"Alexander","family":"Gruber","sequence":"additional","affiliation":[{"name":"Department of Earth and Environmental Sciences, KU Leuven, Celestijnenlaan 200e, 3001 Leuven, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6743-7122","authenticated-orcid":false,"given":"Gabrielle J. M.","family":"De Lannoy","sequence":"additional","affiliation":[{"name":"Department of Earth and Environmental Sciences, KU Leuven, Celestijnenlaan 200e, 3001 Leuven, Belgium"}]},{"given":"Manuela","family":"Girotto","sequence":"additional","affiliation":[{"name":"Department of Environmental Science and Policy Management, University of California, 130 Mulford Hall #3114 Berkeley, Berkeley, CA 94720-3114, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7107-9671","authenticated-orcid":false,"given":"Pere","family":"Quintana-Segu\u00ed","sequence":"additional","affiliation":[{"name":"Observatori de l\u2019Ebre, Universitat Ramon Llull, Carrer Horta Alta 38, 43520 Roquetes, Spain"}]},{"given":"Michel","family":"Le Page","sequence":"additional","affiliation":[{"name":"CESBIO, CNES\/CNRS\/INRAE\/IRD\/UPS, 18 Avenue Edouard Belin, Universit\u00e9 de Toulouse, CEDEX 9, 31401 Toulouse, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6542-5793","authenticated-orcid":false,"given":"Lionel","family":"Jarlan","sequence":"additional","affiliation":[{"name":"CESBIO, CNES\/CNRS\/INRAE\/IRD\/UPS, 18 Avenue Edouard Belin, Universit\u00e9 de Toulouse, CEDEX 9, 31401 Toulouse, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6141-8222","authenticated-orcid":false,"given":"Mehrez","family":"Zribi","sequence":"additional","affiliation":[{"name":"CESBIO, CNES\/CNRS\/INRAE\/IRD\/UPS, 18 Avenue Edouard Belin, Universit\u00e9 de Toulouse, CEDEX 9, 31401 Toulouse, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3203-5278","authenticated-orcid":false,"given":"Nadia","family":"Ouaadi","sequence":"additional","affiliation":[{"name":"CESBIO, CNES\/CNRS\/INRAE\/IRD\/UPS, 18 Avenue Edouard Belin, Universit\u00e9 de Toulouse, CEDEX 9, 31401 Toulouse, France"},{"name":"LMFE, Department of Physics, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakech 4000, Morocco"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4913-0255","authenticated-orcid":false,"given":"Mari\u00ebtte","family":"Vreugdenhil","sequence":"additional","affiliation":[{"name":"Department of Geodesy and Geoinformation, Technische Universit\u00e4t Wien (TU Wien), Wiedner Hauptstra\u00dfe 8-10, 1040 Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0928-229X","authenticated-orcid":false,"given":"Luca","family":"Zappa","sequence":"additional","affiliation":[{"name":"Department of Geodesy and Geoinformation, Technische Universit\u00e4t Wien (TU Wien), Wiedner Hauptstra\u00dfe 8-10, 1040 Vienna, Austria"}]},{"given":"Wouter","family":"Dorigo","sequence":"additional","affiliation":[{"name":"Department of Geodesy and Geoinformation, Technische Universit\u00e4t Wien (TU Wien), Wiedner Hauptstra\u00dfe 8-10, 1040 Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7704-6857","authenticated-orcid":false,"given":"Wolfgang","family":"Wagner","sequence":"additional","affiliation":[{"name":"Department of Geodesy and Geoinformation, Technische Universit\u00e4t Wien (TU Wien), Wiedner Hauptstra\u00dfe 8-10, 1040 Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9839-2986","authenticated-orcid":false,"given":"Joost","family":"Brombacher","sequence":"additional","affiliation":[{"name":"eLEAF Competence Center, Research & Development, Hesselink van Suchtelenweg 6, 6703CT Wageningen, The Netherlands"}]},{"given":"Henk","family":"Pelgrum","sequence":"additional","affiliation":[{"name":"eLEAF Competence Center, Research & Development, Hesselink van Suchtelenweg 6, 6703CT Wageningen, The Netherlands"}]},{"given":"Pauline","family":"Jaquot","sequence":"additional","affiliation":[{"name":"eLEAF Competence Center, Research & Development, Hesselink van Suchtelenweg 6, 6703CT Wageningen, The Netherlands"}]},{"given":"Vahid","family":"Freeman","sequence":"additional","affiliation":[{"name":"Spire Global, 33 Rue Sainte Zithe, 2763 Luxembourg, Luxembourg"}]},{"given":"Espen","family":"Volden","sequence":"additional","affiliation":[{"name":"European Space Agency (ESA), Via Galileo Galilei, 1, Frascati, 00044 Roma, Italy"}]},{"given":"Diego","family":"Fernandez Prieto","sequence":"additional","affiliation":[{"name":"European Space Agency (ESA), Via Galileo Galilei, 1, Frascati, 00044 Roma, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3487-1659","authenticated-orcid":false,"given":"Angelica","family":"Tarpanelli","sequence":"additional","affiliation":[{"name":"Research Institute for the Geo-Hydrological Protection, National Research Council (CNR), Via Madonna Alta 126, 06128 Perugia, Italy"}]},{"given":"Silvia","family":"Barbetta","sequence":"additional","affiliation":[{"name":"Research Institute for the Geo-Hydrological Protection, National Research Council (CNR), Via Madonna Alta 126, 06128 Perugia, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9080-260X","authenticated-orcid":false,"given":"Luca","family":"Brocca","sequence":"additional","affiliation":[{"name":"Research Institute for the Geo-Hydrological Protection, National Research Council (CNR), Via Madonna Alta 126, 06128 Perugia, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,14]]},"reference":[{"key":"ref_1","unstructured":"(2021, July 29). FAO 2016. AQUASTAT Database. Available online: https:\/\/www.fao.org\/aquastat\/en\/."},{"key":"ref_2","unstructured":"Gleick, P.H., Allen, L., Christian-Smith, J., Cohen, M.J., Cooley, H., Heberger, M., Eli Moore, E., Morrison, J., Orr, S., and Schulte, P. (2012). The World\u2019s Water: The Biennial Report on Freshwater Resources, Island Press."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1038\/nature10452","article-title":"Solutions for a cultivated planet","volume":"478","author":"Foley","year":"2011","journal-title":"Nature"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2274","DOI":"10.3390\/rs2092274","article-title":"Remote sensing of irrigated agriculture: Opportunities and challenges","volume":"2","author":"Ozdogan","year":"2010","journal-title":"Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1061\/(ASCE)0733-9496(2007)133:5(386)","article-title":"Boundaries and transboundary water conflicts","volume":"133","author":"Matthews","year":"2007","journal-title":"J. Water Resour. Plan. Manag."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"953","DOI":"10.5194\/hess-20-953-2016","article-title":"Mediterranean irrigation under climate change: More efficient irrigation needed to compensate for increases in irrigation water requirements","volume":"20","author":"Fader","year":"2016","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1007\/s10113-020-01665-y","article-title":"Climate change impacts on water resources in the Mediterranean","volume":"20","author":"Tramblay","year":"2020","journal-title":"Reg. Environ. Chang."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"29526","DOI":"10.1073\/pnas.2017796117","article-title":"Potential for sustainable irrigation expansion in a 3 \u00b0C warmer climate","volume":"117","author":"Rosa","year":"2020","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_9","first-page":"8.1","article-title":"Global modelling of irrigation water requirements","volume":"38","author":"Siebert","year":"2002","journal-title":"Water Resour. Res."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1126\/science.289.5477.284","article-title":"Global water resources: Vulnerability from climate change and population growth","volume":"289","author":"Green","year":"2000","journal-title":"Science"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"763","DOI":"10.1038\/ngeo2514","article-title":"Rainfall consistently enhanced around the Gezira Scheme in East Africa due to irrigation","volume":"8","author":"Alter","year":"2015","journal-title":"Nat. Geosci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1035","DOI":"10.5194\/hess-11-1035-2007","article-title":"Hydrologic effects of land and water management in North America and Asia: 1700\u20131992","volume":"11","author":"Haddeland","year":"2007","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"6167","DOI":"10.1002\/2014GL061213","article-title":"Improved methods for satellite-based groundwater storage estimates: A decade of monitoring the high plains aquifer from space and ground observations","volume":"41","author":"Kendall","year":"2014","journal-title":"Geophys. Res. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1016\/j.jhydrol.2016.10.020","article-title":"Estimation of actual irrigation amount and its impact on groundwater depletion: A case study in the Hebei Plain, China","volume":"543","author":"Hu","year":"2016","journal-title":"J. Hydrol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3209","DOI":"10.1007\/s11269-012-0068-3","article-title":"An integrated DSS for groundwater management based on remote sensing. the case of a semi-arid aquifer in morocco","volume":"26","author":"Berjamy","year":"2012","journal-title":"Water Resour. Manag."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Le Page, M., Jarlan, L., El Hajj, M.M., Zribi, M., Baghdadi, N., and Boone, A. (2020). Potential for the detection of irrigation events on maize plots using sentinel-1 soil moisture products. Remote Sens., 12.","DOI":"10.5194\/egusphere-egu2020-8588"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"125356","DOI":"10.1016\/j.jhydrol.2020.125356","article-title":"Monitoring irrigation using landsat observations and climate data over regional scales in the Murray-Darling Basin","volume":"590","author":"Bretreger","year":"2020","journal-title":"J. Hydrol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"024004","DOI":"10.1088\/1748-9326\/aaf2be","article-title":"Assessing landscape scale heterogeneity in irrigation water use with remote sensing and in situ monitoring","volume":"14","author":"Foster","year":"2019","journal-title":"Environ. Res. Lett."},{"key":"ref_19","unstructured":"OECD (2015). Drying Wells, Rising Stakes: Towards Sustainable Agricultural Ground-Water Use, OECD."},{"key":"ref_20","unstructured":"(2021, July 29). Copernicus\u2014The European Earth Observation Programme. Available online: https:\/\/ec.europa.eu\/growth\/sectors\/space\/copernicus_en."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1959","DOI":"10.1080\/01431160412331291297","article-title":"GLC2000: A new approach to global land cover mapping from Earth observation data","volume":"26","author":"Belward","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_22","unstructured":"Tateishi, R., Zhu, L., and Sato, H.P. (2021, October 13). GLC2000 Database. The Land Cover Map for Central Asia for the Year 2000. European Commision Joint Research Centre. Available online: https:\/\/forobs.jrc.ec.europa.eu\/products\/glc2000\/publications.php."},{"key":"ref_23","unstructured":"Thenkabail, P.S., Biradar, C.M., Turral, H., Noojipady, P., Li, Y.J., Vithanage, J., Dheeravath, V., Velpuri, M., Schull, M., and Cai, X.L. (2006). An Irrigateed Area Map of the World (1999) Derived from Remote Sensing, International Water Management Institute. Research Report 105."},{"key":"ref_24","unstructured":"ESA (2017). Land Cover CCI Product User Guide Version 2. Tech. Rep., Available online: Maps.elie.ucl.ac.be\/CCI\/viewer\/download\/ESACCI-LC-Ph2-PUGv2_2.0.pdf."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"GB1011","DOI":"10.1029\/2008GB003435","article-title":"MIRCA2000-Global monthly irrigated and rainfed crop areas around the year 2000: A new high-resolution data set for agricultural and hydrological modeling","volume":"24","author":"Portmann","year":"2010","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1521","DOI":"10.5194\/hess-19-1521-2015","article-title":"A global data set of the extent of irrigated land from 1900 to 2005","volume":"19","author":"Siebert","year":"2015","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"535","DOI":"10.5194\/hess-9-535-2005","article-title":"Development and validation of the global map of irrigation areas","volume":"9","author":"Siebert","year":"2005","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_28","unstructured":"Hoffman, R.O., Edwards, D.E., Wallin, G., and Burton, T. (2013). Remote sensing instrumentation and methods used for identifying center pivot sprinkler irrigation systems and estimating crop water use. Proc. Int. Semin. Expo. Water Resour. Instrum., 312\u2013317."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1303","DOI":"10.1080\/014311600210191","article-title":"Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data","volume":"21","author":"Loveland","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"9350","DOI":"10.1002\/2017GL074071","article-title":"Annual irrigation dynamics in the US Northern High Plains derived from Landsat satellite data","volume":"44","author":"Deines","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.rse.2014.08.016","article-title":"Dynamic identification of summer cropping irrigated areas in a large basin experiencing extreme climatic variability","volume":"154","author":"McVicar","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"3520","DOI":"10.1016\/j.rse.2008.04.010","article-title":"A new methodology to map irrigated areas using multi-temporal MODIS and ancillary data: An application example in the continental US","volume":"112","author":"Ozdogan","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"103910","DOI":"10.1016\/j.advwatres.2021.103910","article-title":"A new dataset of global irrigation areas from 2001 to 2015","volume":"152","author":"Nagaraj","year":"2021","journal-title":"Adv. Water Resour."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"160118","DOI":"10.1038\/sdata.2016.118","article-title":"Remotely sensed high resolution irrigated area mapping in India for 2000 to 2015","volume":"3","author":"Ambika","year":"2016","journal-title":"Sci. Data"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1119","DOI":"10.5194\/hess-22-1119-2018","article-title":"A global approach to estimate irrigated areas\u2014a comparison between different data and statistics","volume":"22","author":"Meier","year":"2018","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2388","DOI":"10.3390\/rs2102388","article-title":"Mapping irrigated lands at 250-m scale by merging MODIS data and national agricultural statistics","volume":"2","author":"Pervez","year":"2010","journal-title":"Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1007\/s40333-014-0080-y","article-title":"Agricultural irrigation requirements under future climate scenarios in China","volume":"7","author":"Zhu","year":"2015","journal-title":"J. Arid. Land"},{"key":"ref_38","first-page":"321","article-title":"Global rain-fed, irrigated, and paddy croplands: A new high resolution map derived from remote sensing, crop inventories and climate data","volume":"38","author":"Salmon","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Jin, N., Tao, B., Ren, W., Feng, M., Sun, R., He, L., Zhuang, W., and Yu, Q. (2016). Mapping irrigated and rainfed wheat areas using multi-temporal satellite data. Remote Sens., 8.","DOI":"10.3390\/rs8030207"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.rse.2017.10.030","article-title":"Detecting irrigation extent, frequency, and timing in a heterogeneous arid agricultural region using MODIS time series, Landsat imagery, and ancillary data","volume":"204","author":"Chen","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1377","DOI":"10.1038\/srep03697","article-title":"Projected impacts of climate change on farmers\u2019 extraction of groundwater from crystalline aquifers in South India","volume":"4","author":"Ferrant","year":"2014","journal-title":"Sci. Rep."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Ferrant, S., Selles, A., Le Page, M., Herrault, P.-A., Pelletier, C., Al-Bitar, A., Mermoz, S., Gascoin, S., Bouvet, A., and Saqalli, M. (2017). Detection of irrigated crops from sentinel-1 and sentinel-2 data to estimate seasonal groundwater use in South India. Remote Sens., 9.","DOI":"10.3390\/rs9111119"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"285","DOI":"10.5194\/isprs-archives-XLII-3-W6-285-2019","article-title":"Sentinel-1&2 for near real time cropping pattern monitoring in drought prone areas. application to irrigation water needs in telangana, south-india","volume":"42","author":"Ferrant","year":"2019","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Demarez, V., Helen, F., Marais-Sicre, C., and Baup, F. (2019). In-season mapping of irrigated crops using landsat 8 and sentinel-1 time series. Remote Sens., 11.","DOI":"10.3390\/rs11020118"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Pageot, Y., Baup, F., Inglada, J., Baghdadi, N., and Demarez, V. (2020). Detection of irrigated and rainfed crops in temperate areas using sentinel-1 and sentinel-2 time series. Remote Sens., 12.","DOI":"10.3390\/rs12183044"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"111400","DOI":"10.1016\/j.rse.2019.111400","article-title":"Mapping three decades of annual irrigation across the US high plains aquifer using landsat and Google Earth Engine","volume":"233","author":"Deines","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2428","DOI":"10.1029\/2018MS001595","article-title":"Lessons learned from modeling irrigation from field to regional scales","volume":"11","author":"Xu","year":"2019","journal-title":"J. Adv. Modeling Earth Syst."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1016\/j.scitotenv.2019.04.365","article-title":"Detecting global irrigated areas by using satellite and reanalysis products","volume":"677","author":"Zohaib","year":"2019","journal-title":"Sci. Total. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"229","DOI":"10.14358\/PERS.81.3.229-238","article-title":"Mapping irrigated farmlands using vegetation and thermal thresholds derived from landsat and ASTER data in an irrigation district of Australia","volume":"81","author":"McAllister","year":"2015","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Pun, M., Mutiibwa, D., and Li, R. (2017). Land use classification: A surface energy balance and vegetation index application to map and monitor irrigated lands. Remote Sens., 9.","DOI":"10.3390\/rs9121256"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.agwat.2005.02.013","article-title":"Monitoring wheat phenology and irrigation in Central Morocco: On the use of relationships between evapotranspiration, crops coefficients, leaf area index and remotely-sensed vegetation indices","volume":"79","author":"Duchemin","year":"2006","journal-title":"Agric. Water Manag."},{"key":"ref_52","first-page":"179","article-title":"Monitoring crop coefficient of orange orchards using energy balance and the remote sensed NDVI","volume":"Volume 6359","author":"Owe","year":"2006","journal-title":"Remote Sensing for Agriculture, Ecosystems, and Hydrology VIII"},{"key":"ref_53","first-page":"1","article-title":"Evapotranspiration and crop coefficients of Italian zucchini cultivated with recycled paper as mulch","volume":"15","author":"Andrade","year":"2020","journal-title":"PLoS ONE"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"106266","DOI":"10.1016\/j.agwat.2020.106266","article-title":"Satellite-based NDVI crop coefficients and evapotranspiration with eddy covariance validation for multiple durum wheat fields in the US Southwest","volume":"239","author":"French","year":"2020","journal-title":"Agric. Water Manag."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.jhydrol.2009.02.013","article-title":"Scaling of potential evapotranspiration with MODIS data reproduces flux observations and catchment water balance observations across Australia","volume":"369","author":"Guerschman","year":"2009","journal-title":"J. Hydr."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"2017","DOI":"10.13031\/2013.24105","article-title":"Wheat irrigation management using multispectral crop coefficients: I. Crop evapotranspiration prediction","volume":"50","author":"Hunsaker","year":"2007","journal-title":"Trans. ASABE"},{"key":"ref_57","first-page":"83","article-title":"Estimation of evapotranspiration ETc and crop coefficient Kc of wheat, in south nile delta of egypt using integrated FAO-56 approach and remote sensing data","volume":"239","author":"Kamble","year":"2012","journal-title":"Remote Sens."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1588","DOI":"10.3390\/rs5041588","article-title":"Estimating crop coefficients using remote sensing-based vegetation index","volume":"5","author":"Kamble","year":"2013","journal-title":"Remote Sens."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1029\/2012WR012591","article-title":"AVHRR-NDVI-based crop coefficients for analyzing long-term trends in evapotranspiration in relation to changing climate in the U.S. High Plains","volume":"49","author":"Mutiibwa","year":"2013","journal-title":"Water Resour. Res."},{"key":"ref_60","unstructured":"Allen, R.G., Pereira, L., Raes, D., and Smith, M. (1998). FAO Irrigation and Drainage Paper No. 56, Food and Agriculture Organization of the United Nations."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1061\/(ASCE)0733-9437(2005)131:1(2)","article-title":"FAO-56 dual crop coefficient method for estimating evaporation from soil and application extensions","volume":"131","author":"Allen","year":"2005","journal-title":"J. Irrig. Drain. Eng."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Hunink, J.E., Eekhout, J.P.C., de Vente, J., Contreras, S., Droogers, P., and Baille, A. (2017). Hydrological modelling using satellite-based crop coefficients: A comparison of methods at the basin scale. Remote Sens., 9.","DOI":"10.3390\/rs9020174"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1007\/s00271-003-0074-6","article-title":"Estimating cotton evapotranspiration crop coefficients with a multispectral vegetation index","volume":"22","author":"Hunsaker","year":"2003","journal-title":"Irrig. Sci."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Han, W., Niu, X., and Li, G. (2019). Maize crop coefficient estimated from UAV-Measured multispectral vegetation indices. Sensors, 19.","DOI":"10.3390\/s19235250"},{"key":"ref_65","first-page":"103","article-title":"Climate change and Mediterranean agriculture: Impacts on winter wheat and tomato crop evapotranspiration, irrigation requirements and yield","volume":"147","author":"Saadi","year":"2015","journal-title":"Agric. Water Manag. Agric. Water Manag. Priorities Chall."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1351","DOI":"10.1016\/j.agwat.2010.03.017","article-title":"Estimating actual irrigation application by remotely sensed evapotranspiration observations","volume":"97","author":"Droogers","year":"2010","journal-title":"Agric. Water Manag."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1177","DOI":"10.3390\/rs2041177","article-title":"Potential of using remote sensing techniques for global assessment of water footprint of crops","volume":"2","author":"Romaguera","year":"2010","journal-title":"Remote Sens."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"4959","DOI":"10.5194\/hess-22-4959-2018","article-title":"Global 5\u2009km resolution estimates of secondary evaporation including irrigation through satellite data assimilation","volume":"22","author":"Schellekens","year":"2018","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.agee.2014.10.023","article-title":"A novel approach to estimate direct and indirect water withdrawals from satellite measurements: A case study from the Incomati basin","volume":"200","author":"Bastiaanssen","year":"2015","journal-title":"Agric. Ecosyst. Environ."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/S0022-1694(98)00253-4","article-title":"A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation","volume":"212","author":"Bastiaanssen","year":"1998","journal-title":"J. Hydrol."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/S0022-1694(98)00254-6","article-title":"A remote sensing surface energy balance algorithm for land (SEBAL): 2. Validation","volume":"212","author":"Bastiaanssen","year":"1998","journal-title":"J. Hydrol."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"1070","DOI":"10.1175\/JHM-D-14-0017.1","article-title":"Diagnosing neglected soil moisture source\u2013sink processes via a thermal infrared\u2013based two-source energy balance model","volume":"16","author":"Hain","year":"2015","journal-title":"J. Hydrometeorol."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1016\/j.scitotenv.2015.10.086","article-title":"Assessing irrigated agriculture\u2019s surface water and groundwater consumption by combining satellite remote sensing and hydrologic modelling","volume":"542","author":"Mainuddin","year":"2016","journal-title":"Sci. Total. Environ."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"111627","DOI":"10.1016\/j.rse.2019.111627","article-title":"Irrigation retrieval from Landsat optical\/thermal data integrated into a crop water balance model: A case study over winter wheat fields in a semi-arid region","volume":"239","author":"Merlin","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_75","first-page":"102067","article-title":"An object-based image analysis approach to assess irrigation-water consumption from MODIS products in Ethiopia","volume":"88","author":"Vogels","year":"2020","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"10306","DOI":"10.3390\/rs61110306","article-title":"Earth observation based assessment of the water production and water consumption of Nile basin agro-ecosystems","volume":"6","author":"Bastiaanssen","year":"2014","journal-title":"Remote Sens."},{"key":"ref_77","first-page":"102216","article-title":"Use of sentinel-2 MSI data to monitor crop irrigation in Mediterranean areas","volume":"93","author":"Maselli","year":"2020","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Aragon, B., Houborg, R., Tu, K., Fisher, J.B., and McCabe, M. (2018). CubeSats enable high spatiotemporal retrievals of crop-water use for precision agriculture. Remote Sens., 10.","DOI":"10.3390\/rs10121867"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"4463","DOI":"10.5194\/hess-19-4463-2015","article-title":"Evaluating the utility of satellite soil moisture retrievals over irrigated areas and the ability of land data assimilation methods to correct for unmodelled processes","volume":"19","author":"Kumar","year":"2015","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.rse.2016.02.046","article-title":"Comparison of remote sensing and simulated soil moisture data sets in Mediterranean landscapes","volume":"180","author":"Escorihuela","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1175\/JHM-D-16-0280.1","article-title":"Towards a surface soil moisture product at high spatio-temporal resolution: Temporally-interpolated spatially-disaggregated SMOS data","volume":"19","author":"Merlin","year":"2018","journal-title":"J. Hydrometeorol."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"303","DOI":"10.2166\/wcc.2016.122","article-title":"Discerning shifting irrigation practices from passive microwave radiometry over Punjab and Haryana","volume":"8","author":"Singh","year":"2017","journal-title":"J. Water Clim. Chang."},{"key":"ref_83","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_84","doi-asserted-by":"crossref","first-page":"5889","DOI":"10.5194\/hess-22-5889-2018","article-title":"The value of satellite remote sensing soil moisture data and the DISPATCH algorithm in irrigation fields","volume":"22","author":"Fontanet","year":"2018","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"786","DOI":"10.1109\/TGRS.2007.914807","article-title":"A simple method for downscaling passive microwave based soil moisture","volume":"46","author":"Merlin","year":"2008","journal-title":"IEEE Geosci. Remote. Sens. Lett."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"126129","DOI":"10.1016\/j.jhydrol.2021.126129","article-title":"Detecting and mapping irrigated areas in a Mediterranean environment by using remote sensing soil moisture and a land surface model","volume":"596","author":"Dari","year":"2021","journal-title":"J. Hydrol."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"10002","DOI":"10.3390\/rs61010002","article-title":"Irrigated grassland monitoring using a time series of TerraSAR-X and COSMO-SkyMed X-band SAR data","volume":"6","author":"Baghdadi","year":"2014","journal-title":"Remote Sens."},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"El Hajj, M., Baghdadi, N., Zribi, M., and Bazzi, H. (2017). Synergetic use of Sentinel1 and Sentinel2 images for operational soil moisture mapping at high spatial resolution over agricultural areas. Remote Sens., 9.","DOI":"10.3390\/rs9121292"},{"key":"ref_89","doi-asserted-by":"crossref","unstructured":"Santi, E., Dabboor, M., Pettinato, S., and Paloscia, S. (2019). Combining machine learning and compact polarimetry for estimating soil moisture from C-Band SAR data. Remote Sens., 11.","DOI":"10.3390\/rs11202451"},{"key":"ref_90","doi-asserted-by":"crossref","unstructured":"Gao, Q., Zribi, M., Escorihuela, M., and Baghdadi, N. (2017). Synergetic use of Sentinel-1 and Sentinel-2 data for soil moisture mapping at 100 m resolution. Sensors, 17.","DOI":"10.3390\/s17091966"},{"key":"ref_91","first-page":"520","article-title":"Toward global soil moisture monitoring with sentinel-1: Harnessing assets and overcoming obstacles","volume":"57","author":"Freeman","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_92","doi-asserted-by":"crossref","unstructured":"Bousbih, S., Zribi, M., El Hajj, M., Baghdadi, N., Lili-Chabaane, Z., Gao, Q., and Fanise, P. (2018). Soil moisture and irrigation mapping in a semi-arid region based on the synergic use of Sentinel-1 and Sentinel-2 data. Remote Sens., 10.","DOI":"10.3390\/rs10121953"},{"key":"ref_93","doi-asserted-by":"crossref","unstructured":"Gao, Q., Zribi, M., Escorihuela, M., Baghdadi, N., and Segui, P. (2018). Irrigation mapping using Sentinel-1 time series at field scale. Remote Sens., 10.","DOI":"10.3390\/rs10091495"},{"key":"ref_94","doi-asserted-by":"crossref","unstructured":"Bazzi, H., Baghdadi, N., Ienco, D., El Hajj, M., Zribi, M., Belhouchette, H., Escorihuela, M.J., and Demarez, V. (2019). Mapping irrigated areas using sentinel-1 time series in Catalonia, Spain. Remote Sens., 11.","DOI":"10.3390\/rs11151836"},{"key":"ref_95","doi-asserted-by":"crossref","unstructured":"Bazzi, H., Baghdadi, N., Fayad, I., Zribi, M., Belhouchette, H., and Demarez, V. (2020). Near real-time irrigation detection at plot scale using sentinel-1 data. Remote Sens., 12.","DOI":"10.3390\/rs12091456"},{"key":"ref_96","doi-asserted-by":"crossref","unstructured":"Dari, J., Brocca, L., Quintana-Segu\u00ed, P., Casadei, S., Escorihuela, M.J., Stefan, V., and Morbidelli, R. (2021). Double-scale analysis on the detectability of irrigation signals from remote sensing soil moisture over an area with complex topography in central Italy. Adv. Water Resour., under review.","DOI":"10.1016\/j.advwatres.2022.104130"},{"key":"ref_97","first-page":"752","article-title":"How much water is used for irrigation? A new approach exploiting coarse resolution satellite soil moisture products","volume":"73C","author":"Brocca","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"111226","DOI":"10.1016\/j.rse.2019.111226","article-title":"Quantification of irrigation water using remote sensing of soil moisture in a semi-arid region","volume":"231","author":"Jalilvand","year":"2019","journal-title":"Remote. Sens. Environ."},{"key":"ref_99","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_100","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_101","doi-asserted-by":"crossref","first-page":"136719","DOI":"10.1016\/j.scitotenv.2020.136719","article-title":"Satellite-based global-scale irrigation water use and its contemporary trends","volume":"714","author":"Zohaib","year":"2020","journal-title":"Sci. Total. Environ."},{"key":"ref_102","doi-asserted-by":"crossref","unstructured":"Dari, J., Brocca, L., Quintana-Segu\u00ed, P., Escorihuela, M.J., Stefan, V., and Morbidelli, R. (2020). Exploiting high-resolution remote sensing soil moisture to estimate irrigation water amounts over a mediterranean region. Remote Sens., 12.","DOI":"10.3390\/rs12162593"},{"key":"ref_103","doi-asserted-by":"crossref","unstructured":"Zappa, L., Schlaffer, S., Bauer-Marschallinger, B., Nendel, C., Zimmerman, B., and Dorigo, W. (2021). Detection and quantification of irrigation water amounts at 500 m using sentinel-1 surface soil moisture. Remote Sens., 13.","DOI":"10.3390\/rs13091727"},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1126\/science.1099192","article-title":"GRACE measurements of mass variability in the Earth system","volume":"305","author":"Tapley","year":"2004","journal-title":"Science"},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"e2020GL088306","DOI":"10.1029\/2020GL088306","article-title":"Extending the global mass change data record: GRACE Follow-On instrument and science data performance","volume":"47","author":"Landerer","year":"2020","journal-title":"Geophys. Res. Let."},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1038\/s41586-018-0123-1","article-title":"Emerging trends in global freshwater availability","volume":"557","author":"Rodell","year":"2018","journal-title":"Nature"},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"7547","DOI":"10.1002\/2016JB013007","article-title":"High-resolution CSR GRACE RL05 mascons","volume":"121","author":"Save","year":"2016","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_108","doi-asserted-by":"crossref","first-page":"L03703","DOI":"10.1029\/2006GL028679","article-title":"Irrigation cooling effect: Regional climate forcing by land-use change","volume":"34","author":"Kueppers","year":"2007","journal-title":"Geophys. Res. Let."},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"2248","DOI":"10.1175\/2008JCLI2703.1","article-title":"Regional differences in the influence of irrigation on climate","volume":"22","author":"Lobell","year":"2009","journal-title":"J. Clim."},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"4169","DOI":"10.5194\/hess-21-4169-2017","article-title":"Human\u2013water interface in hydrological modelling: Current status and future directions","volume":"21","author":"Wada","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1175\/2009JHM1116.1","article-title":"Simulating the effects of irrigation over the US in a land surface model based on satellite derived agricultural data","volume":"11","author":"Ozdogan","year":"2010","journal-title":"J. Hydrometeor."},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"7251","DOI":"10.1029\/95JD02165","article-title":"Modeling of land surface evaporation by four schemes and comparison with fife observations","volume":"101","author":"Chen","year":"1996","journal-title":"J. Geophys. Res.-Atmos."},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"W08448","DOI":"10.1029\/2007WR006671","article-title":"Modeling the large-scale water balance impact of different irrigation systems","volume":"44","author":"Evans","year":"2008","journal-title":"Water Resour. Res."},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"1135","DOI":"10.1175\/JHM-D-14-0203.1","article-title":"Impact of irrigation methods on land surface model spinup and initialization of WRF forecasts","volume":"16","author":"Lawston","year":"2015","journal-title":"J. Hydrometeorol."},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1175\/JHM-D-11-013.1","article-title":"Incorporating anthropogenic water regulation modules into a land surface model","volume":"13","author":"Pokhrel","year":"2012","journal-title":"J. Hydrometeorol."},{"key":"ref_116","doi-asserted-by":"crossref","unstructured":"De Rosnay, P., Polcher, J., Laval, K., and Sabre, M. (2003). Integrated parameterization of irrigation in the land surface model ORCHIDEE. Validation over Indian Peninsula. Geophys. Res. Lett., 30.","DOI":"10.1029\/2003GL018024"},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"4107","DOI":"10.1002\/2017GL072994","article-title":"Benefits and pitfalls of GRACE data assimilation: A case study of terrestrial water storage depletion in India","volume":"44","author":"Girotto","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_118","doi-asserted-by":"crossref","first-page":"5282","DOI":"10.1029\/2017WR022178","article-title":"Groundwater withdrawals under drought: Reconciling GRACE and land surface models in the United States High Plains Aquifer","volume":"54","author":"Nie","year":"2018","journal-title":"Water Resour. Res."},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"11274","DOI":"10.1029\/2019WR025363","article-title":"Assimilating GRACE into a land surface model in the presence of an irrigation-induced groundwater trend","volume":"55","author":"Nie","year":"2019","journal-title":"Water Resour. Res."},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"1715","DOI":"10.1007\/s00382-014-2204-7","article-title":"Irrigation as an historical climate forcing","volume":"44","author":"Cook","year":"2015","journal-title":"Clim. Dyn."},{"key":"ref_121","doi-asserted-by":"crossref","first-page":"D08114","DOI":"10.1029\/2010JD014740","article-title":"Simulated impacts of irrigation on the atmospheric circulation over Asia","volume":"116","author":"Lee","year":"2011","journal-title":"J. Geophys. Res."},{"key":"ref_122","doi-asserted-by":"crossref","first-page":"597","DOI":"10.1007\/s00382-004-0402-4","article-title":"Direct human influence of irrigation on atmospheric water vapour and climate","volume":"22","author":"Boucher","year":"2004","journal-title":"Clim. Dyn."},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"4547","DOI":"10.5194\/hess-19-4547-2015","article-title":"Climate response to Amazon forest replacement by heterogeneous crop cover","volume":"19","author":"Badger","year":"2015","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_124","doi-asserted-by":"crossref","first-page":"838","DOI":"10.1016\/j.joen.2012.03.002","article-title":"Comparison of the cleaning efficacy of different final irrigation techniques","volume":"38","author":"Jiang","year":"2012","journal-title":"J. Endod."},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"1280","DOI":"10.1002\/hyp.6267","article-title":"Estimation of irrigation flow by hydrograph analysis in a complex agricultural catchment in subtropical China","volume":"21","author":"Tang","year":"2007","journal-title":"Hydrol. Process."},{"key":"ref_126","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.jhydrol.2005.09.028","article-title":"Effects of irrigation on the water and energy balances of the Colorado and Mekong river basins","volume":"324","author":"Haddeland","year":"2006","journal-title":"J. Hydrol."},{"key":"ref_127","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1002\/2013WR014194","article-title":"Comparison of prognostic and diagnostic surface flux modeling approaches over the Nile River basin","volume":"50","author":"Yilmaz","year":"2014","journal-title":"Water Resour. Res."},{"key":"ref_128","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.agrformet.2016.02.004","article-title":"Impacts of agricultural irrigation on ozone concentrations in the Central Valley of California and in the contiguous United States based on WRF-Chem simulations","volume":"221","author":"Li","year":"2016","journal-title":"Agric. For. Meteorol."},{"key":"ref_129","doi-asserted-by":"crossref","first-page":"2981","DOI":"10.1175\/JHM-D-15-0223.1","article-title":"Regional impacts of irrigation in Mexico and southwestern U.S. on hydrometeorological fields in the North American Monsoon region","volume":"17","author":"Mahalov","year":"2016","journal-title":"J. Hydrometeorol."},{"key":"ref_130","doi-asserted-by":"crossref","first-page":"E1080","DOI":"10.1073\/pnas.1704665115","article-title":"Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data","volume":"115","author":"Scanlon","year":"2018","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"1491","DOI":"10.13031\/2013.42256","article-title":"SWAT: Model use, calibration, and validation","volume":"55","author":"Arnold","year":"2012","journal-title":"Trans. ASABE"},{"key":"ref_132","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1623\/hysj.48.3.317.45290","article-title":"Development and testing of the WaterGAP 2 global model of water use and availability","volume":"48","author":"Alcamo","year":"2003","journal-title":"Hydrolog. Sci. J."},{"key":"ref_133","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1016\/j.jhydrol.2009.07.032","article-title":"The significance of local water resources captured in small reservoirs for crop production\u2013A global-scale analysis","volume":"384","author":"Wisser","year":"2010","journal-title":"J. Hydrol."},{"key":"ref_134","doi-asserted-by":"crossref","first-page":"111","DOI":"10.2166\/wp.2015.024","article-title":"Knowledge, participation and transparency in groundwater management","volume":"18","author":"Sanz","year":"2016","journal-title":"Water Policy"},{"key":"ref_135","unstructured":"(2021, July 29). WUEMoCA. Available online: https:\/\/wuemoca.geo.uni-halle.de\/app\/."},{"key":"ref_136","unstructured":"FAO (2020). WaPOR Database Methodology, FAO. Version 2 release."},{"key":"ref_137","doi-asserted-by":"crossref","unstructured":"Foster, T., Mieno, T., and Brozovic, N. (2020). Satellite-based monitoring of irrigation water use: Assessing measurement errors and their implications for agricultural water management policy. Water Resour. Res., 56.","DOI":"10.1029\/2020WR028378"},{"key":"ref_138","doi-asserted-by":"crossref","unstructured":"Garc\u00eda-Moll\u00e1, M., Sanchis-Ibor, C., Avell\u00e0-Reus, L., Albiac, J., Isidoro, D., and Lecina, S. (2019). Spain. Irrigation in the Mediterranean, Springer.","DOI":"10.1007\/978-3-030-03698-0"},{"key":"ref_139","doi-asserted-by":"crossref","first-page":"5901","DOI":"10.5194\/hess-22-5901-2018","article-title":"Do users benefit from additional information in support of operational drought management decisions in the Ebro basin?","volume":"22","author":"Iglesias","year":"2018","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_140","doi-asserted-by":"crossref","unstructured":"Molle, F., Sanchis-Ibor, C., and Avell\u00e0-Reus, L. (2019). Irrigation policies in the mediterranean: Trends and challenges. Irrigation in the Mediterranean: Technologies, Institutions and Policies, Global Issues in Water Policy, Springer International Publishing.","DOI":"10.1007\/978-3-030-03698-0"},{"key":"ref_141","unstructured":"Lagouarde, J.-P., Bhattacharya, B., Cr\u00e9bassol, P., Gamet, P., Adlakha, D., Murthy, C., Singh, S., Mishra, M., Nigam, R., and Raju, P. (2019, January 18\u201320). Indo-french high-resolution thermal infrared space mission for earth natural resources assessment and monitoring-concept and definition of TRISHNA. Proceedings of the ISPRS-GEOGLAM-ISRS Joint International Workshop on \u201cEarth Observations for Agricultural Monitoring\u201d, New Delhi, India."},{"key":"ref_142","doi-asserted-by":"crossref","unstructured":"Koetz, B., Bastiaanssen, W., Berger, M., Defourney, P., Del Bello, U., Drusch, M., Drinkwater, M., Duca, R., Fernandez, V., and Ghent, D. (2018, January 5). High spatio-temporal resolution land surface temperature mission\u2014a copernicus candidate mission in support of agricultural monitoring. Proceedings of the IGARSS 2018\u20142018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8517433"},{"key":"ref_143","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.rse.2015.12.043","article-title":"Evaluating Landsat 8 evapotranspiration for water use mapping in the Colorado River Basin","volume":"185","author":"Senay","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_144","doi-asserted-by":"crossref","unstructured":"Guzinski, R., Nieto, H., Sandholt, I., and Karamitilios, G. (2020). Modelling high-resolution actual evapotranspiration through sentinel-2 and sentinel-3 data fusion. Remote Sens., 12.","DOI":"10.3390\/rs12091433"},{"key":"ref_145","doi-asserted-by":"crossref","first-page":"1697","DOI":"10.1002\/hyp.13708","article-title":"Evaluation of hydrologic impact of an irrigation curtailment program using Landsat satellite data","volume":"34","author":"Velpuri","year":"2020","journal-title":"Hydrol. Process."},{"key":"ref_146","doi-asserted-by":"crossref","unstructured":"Ragettli, S., Herberz, T., and Siegfried, T. (2018). An unsupervised classification algorithm for multi-temporal irrigated area mapping in central Asia. Remote Sens., 10.","DOI":"10.3390\/rs10111823"},{"key":"ref_147","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/j.rse.2018.12.026","article-title":"Crop type mapping without field-level labels: Random forest transfer and unsupervised clustering techniques","volume":"222","author":"Wang","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_148","doi-asserted-by":"crossref","first-page":"8785","DOI":"10.1175\/JCLI-D-17-0762.1","article-title":"Irrigation-induced land\u2013atmosphere feedbacks and their impacts on Indian summer monsoon","volume":"31","author":"Chou","year":"2018","journal-title":"J. Clim."},{"key":"ref_149","doi-asserted-by":"crossref","first-page":"945","DOI":"10.1038\/nclimate2425","article-title":"The global groundwater crisis","volume":"4","author":"Famiglietti","year":"2014","journal-title":"Nat. Clim. Chang."},{"key":"ref_150","doi-asserted-by":"crossref","unstructured":"Modanesi, S., Massari, C., Gruber, A., Lievens, H., Tarpanelli, A., Morbidelli, R., and De Lannoy, G.J.M. (2021). Optimizing a backscatter forward operator using Sentinel-1 data over irrigated land. Hydrol. Earth Syst. Sci. Discuss., 1\u201339.","DOI":"10.5194\/hess-2021-273"},{"key":"ref_151","doi-asserted-by":"crossref","first-page":"4049","DOI":"10.1029\/2018GL077905","article-title":"Soil moisture sensing using spaceborne GNSS reflections: Comparison of CYGNSS reflectivity to SMAP soil moisture","volume":"45","author":"Chew","year":"2018","journal-title":"Geophys. Res. Lett."},{"key":"ref_152","doi-asserted-by":"crossref","first-page":"8272","DOI":"10.1029\/2018GL078923","article-title":"Use of cyclone global navigation satellite system (CyGNSS) observations for estimation of soil moisture","volume":"45","author":"Kim","year":"2018","journal-title":"Geophys. Res. Let."},{"key":"ref_153","unstructured":"ROSE-L (2021, October 13). 2018, Copernicus L-band SAR Mission Requirements Document, ESA, ESA-EOPSM-CLIS-MRD-3371, NISAR, 2018. NASA-ISRO SAR (NISAR) Mission Science Users\u2019 Handbook. NASA Jet Propulsion Laboratory. 261p, Available online: https:\/\/nisar.jpl.nasa.gov\/system\/documents\/files\/26_NISAR_FINAL_9-6-19.pdf."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/20\/4112\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:14:28Z","timestamp":1760166868000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/20\/4112"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,14]]},"references-count":153,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2021,10]]}},"alternative-id":["rs13204112"],"URL":"https:\/\/doi.org\/10.3390\/rs13204112","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10,14]]}}}