{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T05:21:08Z","timestamp":1771910468431,"version":"3.50.1"},"reference-count":32,"publisher":"Recent Advances S.L.","content-domain":{"domain":["www.recentadvancesin.com"],"crossmark-restriction":true},"short-container-title":["RARS"],"abstract":"<jats:p>The Pantanal region is the largest continuous wetland on Earth and one of the most biodiverse\nregions in the world. Its unique ecology relies on a natural flood pulse that sustains a great\nbiodiversity. However, in the last decade, this region experienced anomalous temperatures, dryness\nand wildfires. In particular, Pantanal underwent three consecutive drought episodes during the years\n2018, 2019 and 2020, which were analyzed in this study. In this paper we assess water and thermal\nstress conditions during these drought episodes using latent and sensible heat fluxes from reanalysis (ERA5land and FLDAS) as well as satellite LST and LAI products. Our results show a progressive intensification of soil moisture deficit, leading to high surface temperature amplitude (AMP-LST) anomalies, as actual evapotranspiration fails to match the evaporative demand. Drought conditions reached their maximum intensity in the September-October-November of 2020 season (SON-2020), when the combination of low soil moisture and high AMP-LST, associated to low Evaporative Fraction (EF), leads to thermal and water stress, further diminishing the ecosystem\u2019s capacity to recover from environmental disturbances. This study highlights the need for an integrated monitoring of land-atmosphere dynamics and the usefulness of satellite observations, with the aim to help and\nmitigate the impacts of extreme climatic events, such as drought episodes, over sensitive ecological\nareas, like Pantanal.<\/jats:p>","DOI":"10.62880\/rars25003","type":"journal-article","created":{"date-parts":[[2025,4,27]],"date-time":"2025-04-27T19:35:13Z","timestamp":1745782513000},"page":"1-12","update-policy":"https:\/\/doi.org\/10.62880\/rarsap1","source":"Crossref","is-referenced-by-count":2,"title":["Evapotranspiration anomalies over the Pantanal region during the droughts 2018-2020"],"prefix":"10.62880","author":[{"name":"Global Change Unit, Image Processing Laboratory, University of Valencia, Spain","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4027-8210","authenticated-orcid":false,"given":"Vitor F. V. V.","family":"Miranda","sequence":"first","affiliation":[]},{"name":"Earth Observation Unit, Portuguese Institute of Sea and Atmosphere, Lisbon, Portugal","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7562-4895","authenticated-orcid":false,"given":"Juan Carlos","family":"Jim\u00e9nez","sequence":"additional","affiliation":[]},{"name":"Global Change Unit, Image Processing Laboratory, University of Valencia, Spain","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8640-9170","authenticated-orcid":false,"given":"Isabel","family":"Trigo","sequence":"additional","affiliation":[]},{"name":"Earth Observation Unit, Portuguese Institute of Sea and Atmosphere, Lisbon, Portugal","sequence":"additional","affiliation":[]},{"name":"Instituto Dom Luiz (IDL), University of Lisbon, Campo Grande, Lisbon, Portugal","sequence":"additional","affiliation":[]}],"member":"49542","published-online":{"date-parts":[[2025,4,28]]},"reference":[{"key":"ref0","doi-asserted-by":"publisher","unstructured":"Bento, V. A., Gouveia, C. M., DaCamara, C. C., Libonati, R., & Trigo, I. F. (2020). The roles of NDVI and Land Surface Temperature when using the Vegetation Health Index over dry regions. Global and Planetary Change, 190. https:\/\/doi.org\/10.1016\/j.gloplacha.2020.103198","DOI":"10.1016\/j.gloplacha.2020.103198"},{"key":"ref1","unstructured":"Bosilovich, M. G., Lucchesi, R., & Suarez, M. (2015). Global Modeling and Assimilation Office MERRA-2: File Specification. http:\/\/gmao.gsfc.nasa.gov\/pubs\/office_notes."},{"key":"ref2","doi-asserted-by":"publisher","unstructured":"Calim Costa, M., Marengo, J. A., Alves, L. M., & Cunha, A. P. (2024). Multiscale analysis of drought, heatwaves, and compound events in the Brazilian Pantanal in 2019-2021. Theoretical and Applied Climatology, 155(1), 661-677. https:\/\/doi.org\/10.1007\/s00704-023-04655-2","DOI":"10.1007\/s00704-023-04655-2"},{"key":"ref3","unstructured":"Defourny, P., Boettcher, M., Bontemps, S., Kirches, G., Krueger, O., Lamarche, C., Lembr\u00e9e, C., Radoux, J., & Verheggen, A. (2014). Algorithm theoretical basis document for land cover climate change initiative, Technical report. http:\/\/due.esrin.esa.int\/page_globcover.php"},{"key":"ref4","doi-asserted-by":"publisher","unstructured":"Denissen, J. M. C., Teuling, A. J., Pitman, A. J., Koirala, S., Migliavacca, M., Li, W., Reichstein, M., Winkler, A. J., Zhan, C., & Orth, R. (2022). Widespread shift from ecosystem energy to water limitation with climate change. Nature Climate Change, 12(7), 677-684. https:\/\/doi.org\/10.1038\/s41558-022-01403-8","DOI":"10.1038\/s41558-022-01403-8"},{"key":"ref5","doi-asserted-by":"publisher","unstructured":"Dirmeyer, P. A., Balsamo, G., Blyth, E. M., Morrison, R., & Cooper, H. M. (2021). Land\u2010Atmosphere Interactions Exacerbated the Drought and Heatwave Over Northern Europe During Summer 2018. AGU Advances, 2(2). https:\/\/doi.org\/10.1029\/2020av000283","DOI":"10.1029\/2020AV000283"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1023\/a:1003951930525","article-title":"Flood pulse influence on phytoplankton communities of the south Pantanal floodplain, Brazil","author":"De Oliveira","year":"2000","unstructured":"Divina De Oliveira, M., D\u00e9bora, &, & Calheiros, F. (2000). Flood pulse influence on phytoplankton communities of the south Pantanal floodplain, Brazil. In Hydrobiologia (Vol. 427).","journal-title":"In Hydrobiologia (Vol"},{"key":"ref7","doi-asserted-by":"publisher","unstructured":"Donat, M. G., Pitman, A. J., & Seneviratne, S. I. (2017). Regional warming of hot extremes accelerated by surface energy fluxes. Geophysical Research Letters, 44(13), 7011-7019. https:\/\/doi.org\/10.1002\/2017GL073733","DOI":"10.1002\/2017GL073733"},{"key":"ref8","doi-asserted-by":"publisher","unstructured":"Feldman, A. F., Short Gianotti, D. J., Trigo, I. F., Salvucci, G. D., & Entekhabi, D. (2019). Satellite-Based Assessment of Land Surface Energy Partitioning-Soil Moisture Relationships and Effects of Confounding Variables. Water Resources Research, 55(12), 10657-10677. https:\/\/doi.org\/10.1029\/2019WR025874","DOI":"10.1029\/2019WR025874"},{"key":"ref9","doi-asserted-by":"publisher","unstructured":"Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A., & Michaelsen, J. (2015). The climate hazards infrared precipitation with stations - A new environmental record for monitoring extremes. Scientific Data, 2. https:\/\/doi.org\/10.1038\/sdata.2015.66","DOI":"10.1038\/sdata.2015.66"},{"key":"ref10","doi-asserted-by":"publisher","unstructured":"Garc\u00eda-Garc\u00eda, A., Cuesta-Valero, F. J., Miralles, D. G., Mahecha, M. D., Quaas, J., Reichstein, M., Zscheischler, J., & Peng, J. (2023). Soil heat extremes can outpace air temperature extremes. Nature Climate Change, 13(11), 1237-1241. https:\/\/doi.org\/10.1038\/s41558-023-01812-3","DOI":"10.1038\/s41558-023-01812-3"},{"key":"ref11","doi-asserted-by":"publisher","unstructured":"Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Hor\u00e1nyi, A., Mu\u00f1oz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., \u2026 Th\u00e9paut, J. N. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), 1999-2049. https:\/\/doi.org\/10.1002\/qj.3803","DOI":"10.1002\/qj.3803"},{"key":"ref12","unstructured":"Hulley, G., Malakar, N., & Freepartner, R. (2016). Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature and Emissivity Product (MxD21) Algorithm Theoretical Basis Document Collection 6.1."},{"key":"ref13","doi-asserted-by":"publisher","unstructured":"Junk, W. J., da Cunha, C. N., Wantzen, K. M., Petermann, P., Str\u00fcssmann, C., Marques, M. I., & Adis, J. (2006). Biodiversity and its conservation in the Pantanal of Mato Grosso, Brazil. Aquatic Sciences, 68(3), 278-309. https:\/\/doi.org\/10.1007\/s00027-006-0851-4","DOI":"10.1007\/s00027-006-0851-4"},{"key":"ref14","doi-asserted-by":"publisher","unstructured":"Kumar, S., Getirana, A., Libonati, R., Hain, C., Mahanama, S., & Andela, N. (2022). Changes in land use enhance the sensitivity of tropical ecosystems to fire-climate extremes. Scientific Reports, 12(1). https:\/\/doi.org\/10.1038\/s41598-022-05130-0","DOI":"10.1038\/s41598-022-05130-0"},{"key":"ref15","doi-asserted-by":"publisher","unstructured":"Li, H., Li, R., Yang, Y., Cao, B., Bian, Z., Hu, T., Du, Y., Sun, L., & Liu, Q. (2021). Temperature-Based and Radiance-Based Validation of the Collection 6 MYD11 and MYD21 Land Surface Temperature Products over Barren Surfaces in Northwestern China. IEEE Transactions on Geoscience and Remote Sensing, 59(2), 1794-1807. https:\/\/doi.org\/10.1109\/TGRS.2020.2998945","DOI":"10.1109\/TGRS.2020.2998945"},{"key":"ref16","doi-asserted-by":"publisher","unstructured":"Libonati, R., Geirinhas, J. o. L., Silva, P. S., Russo, A., Rodrigues, J. A., Bel\u00e9m, L. B. C., Nogueira, J., Roque, F. O., Dacamara, C. C., Nunes, A. M. B., Marengo, J. A., & Trigo, R. M. (2022). Assessing the role of compound drought and heatwave events on unprecedented 2020 wildfires in the Pantanal. Environmental Research Letters, 17(1). https:\/\/doi.org\/10.1088\/1748-9326\/ac462e","DOI":"10.1088\/1748-9326\/ac462e"},{"key":"ref17","doi-asserted-by":"publisher","unstructured":"Lorenz, C., Libonati, R., Coelho Bel\u00e9m, L. B., Oliveira, A., Chiaravalloti, R. M., Nunes, A. V., Luciano Batista, E. K., Fernandes, G. W., Chiaravalloti-Neto, F., Damasceno-Junior, G. A., Berlinck, C. N., & de Oliveira Roque, F. (2024). Historical association between respiratory diseases hospitalizations and fire occurrence in the Pantanal wetland, Brazil. Atmospheric Pollution Research, 15(8). https:\/\/doi.org\/10.1016\/j.apr.2024.102182","DOI":"10.1016\/j.apr.2024.102182"},{"key":"ref18","doi-asserted-by":"publisher","unstructured":"Marcuzzo, F. F. N., Rocha, H. M., and Melo, DCR. (2011). Mapeamento da precipitac,\u00e3o pluviom\u00e9trica no bioma Pantanal do estado do Mato Grosso. Geoambiente On-line 16, 66-84.","DOI":"10.21168\/rbrh.v16n4.p157-167"},{"key":"ref19","doi-asserted-by":"publisher","unstructured":"Marengo, J. A., Alves, L. M., and Torres, RR. (2016). Regional climate change scenarios in the Brazilian Pantanal watershed. Clim Res. 68, 201-213. doi: 10.3354\/cr01324","DOI":"10.3354\/cr01324"},{"key":"ref20","doi-asserted-by":"publisher","unstructured":"Marengo, J. A., Cunha, A. P., Cuartas, L. A., Deusdar\u00e1 Leal, K. R., Broedel, E., Seluchi, M. E., Michelin, C. M., de Praga Bai\u00e3o, C. F., Chuch\u00f3n \u00c2ngulo, E., Almeida, E. K., Kazmierczak, M. L., Mateus, N. P. A., Silva, R. C., & Bender, F. (2021). Extreme Drought in the Brazilian Pantanal in 2019-2020: Characterization, Causes, and Impacts. Frontiers in Water, 3. https:\/\/doi.org\/10.3389\/frwa.2021.639204","DOI":"10.3389\/frwa.2021.639204"},{"key":"ref21","doi-asserted-by":"publisher","unstructured":"McNally, A., Arsenault, K., Kumar, S., Shukla, S., Peterson, P., Wang, S., Funk, C., Peters-Lidard, C. D., & Verdin, J. P. (2017). A land data assimilation system for sub-Saharan Africa food and water security applications. Scientific Data, 4. https:\/\/doi.org\/10.1038\/sdata.2017.12","DOI":"10.1038\/sdata.2017.12"},{"key":"ref22","doi-asserted-by":"publisher","unstructured":"Miranda, V. F. V. V., Jimenez, J. C., Dutra, E., & Trigo, I. F. (2024). Consistency assessment of latent heat flux and observational datasets over the Amazon basin. Environmental Research Letters, 19(5). https:\/\/doi.org\/10.1088\/1748-9326\/ad40c3","DOI":"10.1088\/1748-9326\/ad40c3"},{"key":"ref23","doi-asserted-by":"publisher","unstructured":"Mu\u00f1oz-Sabater, J., Dutra, E., Agust\u00ed-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodr\u00edguez-Fern\u00e1ndez, N. J., Zsoter, E., Buontempo, C., & Th\u00e9paut, J. N. (2021). ERA5-Land: A state-of-the-art global reanalysis dataset for land applications. Earth System Science Data, 13(9), 4349-4383. https:\/\/doi.org\/10.5194\/essd-13-4349-2021","DOI":"10.5194\/essd-13-4349-2021"},{"key":"ref24","unstructured":"Myneni, R., Knyazikhin, Y., & Park, T. (2021). MODIS\/Terra+Aqua Leaf Area Index\/FPAR 8-Day L4 Global 500m SIN Grid V061 [Data set]. NASA EOSDIS Land Processes Distributed Active Archive Center."},{"key":"ref25","doi-asserted-by":"publisher","unstructured":"Orth, R. (2021). When the Land Surface Shifts Gears. AGU Advances, 2(2). https:\/\/doi.org\/10.1029\/2021av000414","DOI":"10.1029\/2021AV000414"},{"key":"ref26","doi-asserted-by":"publisher","unstructured":"Panwar, A., Kleidon, A., & Renner, M. (2019). Do Surface and Air Temperatures Contain Similar Imprints of Evaporative Conditions? Geophysical Research Letters, 46(7), 3802-3809. https:\/\/doi.org\/10.1029\/2019GL082248","DOI":"10.1029\/2019GL082248"},{"key":"ref27","doi-asserted-by":"publisher","unstructured":"Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B., & Teuling, A. J. (2010). Investigating soil moisture-climate interactions in a changing climate: A review. In Earth-Science Reviews (Vol. 99, Issues 3-4, pp. 125-161). https:\/\/doi.org\/10.1016\/j.earscirev.2010.02.004","DOI":"10.1016\/j.earscirev.2010.02.004"},{"key":"ref28","doi-asserted-by":"publisher","unstructured":"Seneviratne, S. I., Viterbo, P., L\u00fcthi, D., Sch\u00e4r, C. (2003). Inferring Changes in Terrestrial Water Storage Using ERA-40 Reanalysis Data: The Mississippi River Basin.","DOI":"10.1175\/1520-0442(2004)017<2039:ICITWS>2.0.CO;2"},{"key":"ref29","doi-asserted-by":"publisher","unstructured":"Silva, P. S., Rodrigues, J. A., Nogueira, J., Moura, L. C., Enout, A., Cuiab\u00e1lia, C., DaCamara, C. C., Pereira, A. A., & Libonati, R. (2024). Joining forces to fight wildfires: Science and management in a protected area of Pantanal, Brazil. Environmental Science and Policy, 159. https:\/\/doi.org\/10.1016\/j.envsci.2024.103818","DOI":"10.1016\/j.envsci.2024.103818"},{"key":"ref30","doi-asserted-by":"publisher","unstructured":"Thielen, D., Ramoni-Perazzi, P., Puche, M. L., M\u00e1rquez, M., Quintero, J. I., Rojas, W., Soto-Werschitz, A., Thielen, K., Nunes, A., & Libonati, R. (2021). The pantanal under siege-on the origin, dynamics and forecast of the megadrought severely affecting the largest wetland in the world. Water (Switzerland), 13(21). https:\/\/doi.org\/10.3390\/w13213034","DOI":"10.3390\/w13213034"},{"key":"ref31","doi-asserted-by":"publisher","unstructured":"Wantzen, K. M., Assine, M. L., Bortolotto, I. M., Calheiros, D. F., Campos, Z., Catella, A. C., Chiaravalotti, R. M., Collischonn, W., Couto, E. G., da Cunha, C. N., Damasceno-Junior, G. A., da Silva, C. J., Eberhard, A., Ebert, A., de Figueiredo, D. M., Friedlander, M., Garcia, L. C., Girard, P., Hamilton, S., Ikeda-Castrillon S., Libonati R., Lourival R., de Azevedo Macedo H., Junior J., Mateus L., Morato R., Mour\u00e3o G., Muniz C., Nunes A., de Oliveira M., da Rosa Oliveira M., Junior E., Padovani C., Penha J., Ribeiro D., de Oliveira Roque F., Silva A., Soriano B., Sousa Junior W., Tomas W., Tortao F., Urbanetz C. (2024). The end of an entire biome? World's largest wetland, the Pantanal, is menaced by the Hidrovia project which is uncertain to sustainably support large-scale navigation. Science of the Total Environment, 908. https:\/\/doi.org\/10.1016\/j.scitotenv.2023.167751","DOI":"10.1016\/j.scitotenv.2023.167751"}],"container-title":["Recent Advances in Remote Sensing"],"original-title":[],"link":[{"URL":"https:\/\/www.recentadvancesin.com\/wp-content\/uploads\/2025\/04\/rars25003.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,31]],"date-time":"2025-08-31T15:01:58Z","timestamp":1756652518000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.recentadvancesin.com\/remote-sensing\/3020-6448-rars25003\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,28]]},"references-count":32,"URL":"https:\/\/doi.org\/10.62880\/rars25003","relation":{},"ISSN":["3020-6448"],"issn-type":[{"value":"3020-6448","type":"print"}],"subject":[],"published":{"date-parts":[[2025,4,28]]}}}