{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T15:04:17Z","timestamp":1774969457634,"version":"3.50.1"},"reference-count":72,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,12,25]],"date-time":"2023-12-25T00:00:00Z","timestamp":1703462400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Joint International Laboratory TREMA (IRD, UCAM, DMN, CNESTEN, ABHT, and ORMVAH)"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Drought is a powerful natural hazard that has significant effects on ecosystems amid the constant threats posed by climate change. This study investigates agricultural drought in a semi-arid Mediterranean basin through the interconnections among four indices: precipitation (meteorological reanalysis), vegetation development, thermal stress, and soil water deficit (remote sensing observations). While drought seems to be a clear concept with effective assessment tools (e.g., SPI and SPEI), the definition of drought periods is blurrier. This article examines the main drivers of agricultural drought, precipitation, soil moisture deficit, incipient vegetation development, and rising soil surface temperature. Their temporal connections in various agrosystems of the basin and the determination of drought periods by revisiting the run theory were investigated. The Pearson correlations at different spatial scales showed a medium to low level of agreement between the indices, which was explained by the geographical heterogeneity and the climatic variability between the agrosystems within the basin. It was also shown that the cascade of impacts expected from lower precipitations was revealed by the cross-correlation analysis. The connection between precipitation deficit and vegetation remains significant for at least one month for most pairs of indices, especially during drought events, suggesting that agricultural drought spells can be connected in time through the three or four selected indices. Short-, mid-, and long-term impacts of precipitation deficiencies on soil moisture, vegetation, and temperature were revealed. As expected, the more instantaneous variables of soil moisture and surface temperature showed no lag with precipitation. Vegetation anomalies at the monthly time step showed a two-month lag with a preceding effect of vegetation to precipitation. Finally, the determination of drought events and stages with varying thresholds on the run theory showed large variability in duration, magnitude, and intensity according to the choice of both normality and dryness thresholds.<\/jats:p>","DOI":"10.3390\/rs16010083","type":"journal-article","created":{"date-parts":[[2023,12,25]],"date-time":"2023-12-25T03:42:12Z","timestamp":1703475732000},"page":"83","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Toward a Redefinition of Agricultural Drought Periods\u2014A Case Study in a Mediterranean Semi-Arid Region"],"prefix":"10.3390","volume":"16","author":[{"given":"Kaoutar","family":"Oukaddour","sequence":"first","affiliation":[{"name":"Geosciences Laboratory, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakech 40000, Morocco"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0671-2418","authenticated-orcid":false,"given":"Michel","family":"Le Page","sequence":"additional","affiliation":[{"name":"Centre d\u2019Etudes Spatiales de la Biosph\u00e8re (CESBIO), Universit\u00e9 de Toulouse, CNES\/CNRS\/INRAE\/IRD\/UPS, 31400 Toulouse, France"}]},{"given":"Younes","family":"Fakir","sequence":"additional","affiliation":[{"name":"Geosciences Laboratory, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakech 40000, Morocco"},{"name":"Center for Remote Sensing Applications (CRSA), Mohammed VI Polytechnic University (UM6P), Ben Guerir 43150, Morocco"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"EBouras, E.H., Jarlan, L., Er-Raki, S., Balaghi, R., Amazirh, A., Richard, B., and Khabba, S. (2021). Cereal yield forecasting with satellite drought-based indices, weather data and regional climate indices using machine learning in Morocco. Remote Sens., 13.","DOI":"10.5194\/egusphere-egu21-14590"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"127866","DOI":"10.1016\/j.jclepro.2021.127866","article-title":"Drought characterization across agricultural regions of China using standardized precipitation and vegetation water supply indices","volume":"313","author":"Javed","year":"2021","journal-title":"J. Clean. Prod."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"699","DOI":"10.1890\/08-0330.1","article-title":"Drought impact on forest growth and mortality in the southeast.pdf","volume":"19","author":"Klos","year":"2009","journal-title":"Ecol. Appl."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1038\/s43017-020-0060-z","article-title":"A typology of compound weather and climate events","volume":"1","author":"Zscheischler","year":"2020","journal-title":"Nat. Rev. Earth Environ."},{"key":"ref_5","first-page":"314","article-title":"Le macroscope. Vers une vision globale","volume":"57","year":"1975","journal-title":"Rev. D\u2019histoire Et De Philos. Relig."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1149","DOI":"10.1175\/1520-0477-83.8.1149","article-title":"A review of twentieth-century drought indices used in the United States","volume":"83","author":"Heim","year":"2002","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_7","first-page":"179","article-title":"The relationship of drought frequency and duration to time scales","volume":"17","author":"McKee","year":"1993","journal-title":"Prepr. Eighth Conf. Appl. Climatol. Am. Meteor Soc."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3001","DOI":"10.1002\/joc.3887","article-title":"Standardized precipitation evapotranspiration index (SPEI) revisited: Parameter fitting, evapotranspiration models, tools, datasets and drought monitoring","volume":"34","author":"Reig","year":"2014","journal-title":"Int. J. Climatol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1696","DOI":"10.1175\/2009JCLI2909.1","article-title":"A multiscalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index","volume":"23","year":"2010","journal-title":"J. Clim."},{"key":"ref_10","first-page":"71","article-title":"Drought monitoring with NDVI-based Standardized Vegetation Index","volume":"68","author":"Peters","year":"2002","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1405","DOI":"10.1080\/01431169008955102","article-title":"Remote sensing of weather impacts on vegetation in non-homogeneous areas","volume":"11","author":"Kogan","year":"1990","journal-title":"Int. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1325","DOI":"10.5194\/nhess-22-1325-2022","article-title":"Estimating soil moisture conditions for drought monitoring with random forests and a simple soil moisture accounting scheme","volume":"1","author":"Tramblay","year":"2022","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.rse.2013.02.023","article-title":"Monitoring meteorological drought in semiarid regions using multi-sensor microwave remote sensing data","volume":"134","author":"AZhang","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_14","first-page":"353","article-title":"An objective approach to definitions and investigations of continental hydrologic droughts","volume":"7","author":"Yevjevich","year":"1967","journal-title":"J. Hydrol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"165550","DOI":"10.1016\/j.scitotenv.2023.165550","article-title":"A review of recent developments on drought characterization, propagation, and influential factors","volume":"898","author":"Raposo","year":"2023","journal-title":"Sci. Total Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1002\/wat2.1085","article-title":"Hydrological drought explained","volume":"2","year":"2015","journal-title":"Wiley Interdiscip. Rev. Water"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"156021","DOI":"10.1016\/j.scitotenv.2022.156021","article-title":"Drought propagation under global warming: Characteristics, approaches, processes, and controlling factors","volume":"838","author":"Zhang","year":"2022","journal-title":"Sci. Total Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"D20","DOI":"10.1029\/2011JD016168","article-title":"Drought onset and recovery over the United States","volume":"116","author":"Mo","year":"2011","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1718","DOI":"10.1002\/joc.5291","article-title":"Will drought events become more frequent and severe in Europe","volume":"38","author":"Spinoni","year":"2018","journal-title":"Int. J. Climatol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1080\/02626669709492003","article-title":"On the definition and modelling of streamflow drought duration and deficit volume","volume":"42","author":"Tallaksen","year":"1997","journal-title":"Hydrol. Sci. J."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1317","DOI":"10.1007\/s00477-015-1185-3","article-title":"Uncertainty and variability in bivariate modeling of hydrological droughts","volume":"30","author":"Tu","year":"2016","journal-title":"Stoch. Environ. Res. Risk Assess."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3635","DOI":"10.1175\/JCLI-D-19-0084.1","article-title":"Future Global Meteorological Drought Hot Spots: A Study Based on CORDEX Data","volume":"33","author":"Spinoni","year":"2020","journal-title":"J. Clim."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"637","DOI":"10.5194\/hess-25-637-2021","article-title":"Projection of irrigation water demand based on the simulation of synthetic crop coefficients and climate change","volume":"25","author":"Fakir","year":"2021","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1029\/WR016i002p00289","article-title":"On the statistical characteristics of drought events","volume":"16","author":"Dracup","year":"1980","journal-title":"Water Resour. Res."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"459","DOI":"10.5194\/hess-14-459-2010","article-title":"Multilevel and multiscale drought reanalysis over France with the Safran-Isba-Modcou hydrometeorological suite","volume":"14","author":"Vidal","year":"2010","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1175\/1520-0477-83.8.1181","article-title":"The drought monitor","volume":"83","author":"Svoboda","year":"2002","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1080\/07055900.2011.594024","article-title":"Characterizing the Surface Features of the 1999\u20132005 Canadian Prairie Drought in Relation to Previous Severe Twentieth Century Events","volume":"49","author":"Bonsal","year":"2011","journal-title":"Atmosphere-Ocean"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1177\/0309133316652801","article-title":"Drought termination: Concept and characterization","volume":"40","author":"Parry","year":"2016","journal-title":"Prog. Phys. Geogr. Earth Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3519","DOI":"10.5194\/nhess-12-3519-2012","article-title":"Development of a Combined Drought Indicator to detect agricultural drought in Europe","volume":"12","author":"Horion","year":"2012","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"3461","DOI":"10.5194\/nhess-22-3461-2022","article-title":"Interactions between precipitation, evapotranspiration and soil moisture-based indices to characterize drought with high-resolution remote sensing and land-surface model data","volume":"22","author":"Gaona","year":"2022","journal-title":"Nat. Hazards Earth Syst. Sci. Discuss."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.wace.2015.05.002","article-title":"Comparison of drought indices for appraisal of drought characteristics in the Ken River Basin","volume":"8","author":"Jain","year":"2015","journal-title":"Weather. Clim. Extrem."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"134585","DOI":"10.1016\/j.scitotenv.2019.134585","article-title":"Monitoring drought using composite drought indices based on remote sensing","volume":"711","author":"Liu","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Pei, Z., Fang, S., Wang, L., and Yang, W. (2020). Comparative analysis of drought indicated by the SPI and SPEI at various timescales in inner Mongolia, China. Water, 12.","DOI":"10.3390\/w12071925"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Silva, T., Pires, V., Cota, T., and Silva, \u00c1. (2022). Detection of Drought Events in Set\u00fabal District: Comparison between Drought Indices. Atmosphere, 13.","DOI":"10.3390\/atmos13040536"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2187","DOI":"10.1007\/s11069-021-04775-w","article-title":"Evaluation of the similarity between drought indices by correlation analysis and Cohen\u2019s Kappa test in a Mediterranean area","volume":"108","author":"Vergni","year":"2021","journal-title":"Nat. Hazards"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1467","DOI":"10.5194\/hess-24-1467-2020","article-title":"Climate change impacts on the Water Highway project in Morocco","volume":"24","author":"Kang","year":"2020","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.gloplacha.2011.12.002","article-title":"Climate change impacts on extreme precipitation in Morocco","volume":"82\u201383","author":"Tramblay","year":"2012","journal-title":"Glob. Planet. Change"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1291","DOI":"10.1007\/s11269-017-1870-8","article-title":"Future Scenarios of Surface Water Resources Availability in North African Dams","volume":"32","author":"Tramblay","year":"2018","journal-title":"Water Resour. Manag."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Kharrou, M.H., Simonneaux, V., Er-Raki, S., Le Page, M., Khabba, S., and Chehbouni, A. (2021). Assessing irrigation water use with remote sensing-based soil water balance at an irrigation scheme level in a semi-arid region of Morocco. Remote Sens., 13.","DOI":"10.3390\/rs13061133"},{"key":"ref_40","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_41","doi-asserted-by":"crossref","first-page":"1999","DOI":"10.1002\/qj.3803","article-title":"The ERA5 global reanalysis","volume":"146","author":"Hersbach","year":"2020","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.rse.2017.05.005","article-title":"Satellite-based water use dynamics using historical Landsat data (1984\u20132014) in the southwestern United States","volume":"202","author":"Senay","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1007\/s00704-005-0227-z","article-title":"Spatial and temporal analysis of drought in Greece using the Standardized Precipitation Index (SPI)","volume":"89","author":"Livada","year":"2007","journal-title":"Theor. Appl. Climatol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.atmosres.2019.01.003","article-title":"Drought characterization for the state of Rio de Janeiro based on the annual SPI index: Trends, statistical tests and its relation with ENSO","volume":"220","author":"Sobral","year":"2019","journal-title":"Atmos. Res."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"127098","DOI":"10.1016\/j.jhydrol.2021.127098","article-title":"Assessing the accuracy and drought utility of long-term satellite-based precipitation estimation products using the triple collocation approach","volume":"603","author":"Bai","year":"2021","journal-title":"J. Hydrol."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Bouras, E.H., Jarlan, L., Er-Raki, S., Albergel, C., Richard, B., Balaghi, R., and Khabba, S. (2020). Linkages between rainfed cereal production and agricultural drought through remote sensing indices and a land data assimilation system: A case study in Morocco. Remote Sens., 12.","DOI":"10.3390\/rs12244018"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"21","DOI":"10.5194\/nhess-20-21-2020","article-title":"Evaluation of a combined drought indicator and its potential for agricultural drought prediction in southern Spain","volume":"20","author":"Tarquis","year":"2020","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.agrformet.2019.01.008","article-title":"A new multi-sensor integrated index for drought monitoring","volume":"268","author":"Jiao","year":"2019","journal-title":"Agric. For. Meteorol."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1016\/j.agrformet.2009.11.015","article-title":"Evaluating the utility of the Vegetation Condition Index (VCI) for monitoring meteorological drought in Texas","volume":"150","author":"Quiring","year":"2010","journal-title":"Agric. For. Meteorol."},{"key":"ref_50","first-page":"36","article-title":"Seasonal comparisons of meteorological and agricultural droughtindices in Morocco using open short time-series data","volume":"26","author":"Ezzine","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"45","DOI":"10.21523\/gcj3.2021050201","article-title":"Characterization and Quantification of Meteorological Drought in the Oued El-Abid Watershed, Central High Atlas, Morocco (1980\u20132019)","volume":"5","author":"Layati","year":"2021","journal-title":"Hydrospatial Anal."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1007\/s00704-018-2388-6","article-title":"Spatiotemporal characterization of current and future droughts in the High Atlas basins (Morocco)","volume":"135","author":"Zkhiri","year":"2019","journal-title":"Theor. Appl. Climatol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1998","DOI":"10.1007\/s12517-019-4656-x","article-title":"Analysis of precipitation time series and regional drought assessment based on the standardized precipitation index in the Oum Er-Rbia basin (Morocco)","volume":"12","author":"Zhim","year":"2019","journal-title":"Arab. J. Geosci."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"103425","DOI":"10.1016\/j.pce.2023.103425","article-title":"Spatio-temporal distribution and prediction of agricultural and meteorological drought in a Mediterranean coastal watershed via GIS and machine learning","volume":"131","author":"Acharki","year":"2023","journal-title":"Phys. Chem. Earth"},{"key":"ref_55","first-page":"1","article-title":"Comparative evaluation of various drought indices (DIs) to monitor drought status: A case study of Moroccan Lower Sebou basin","volume":"49","author":"Hakam","year":"2022","journal-title":"Kuwait J. Sci."},{"key":"ref_56","first-page":"121","article-title":"Assessment of climate and land use changes: Impacts on groundwater resources in the Souss-Massa river basin","volume":"53","author":"Malki","year":"2017","journal-title":"Handb. Environ. Chem."},{"key":"ref_57","first-page":"73","article-title":"Agricultural Drought Indices: Combining Crop, Climate, and Soil Factors","volume":"Volume 1","author":"Eslamian","year":"2017","journal-title":"Handbook of Drought and Water Scarcity, Principles of Drought and Water Scarcity"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"S\u00e1nchez, N., Gonz\u00e1lez-Zamora, \u00c1., Piles, M., and Mart\u00ednez-Fern\u00e1ndez, J.A. (2016). New Soil Moisture Agricultural Drought Index (SMADI) Integrating MODIS and SMOS Products: A Case of Study over the Iberian Peninsula. Remote Sens., 8.","DOI":"10.3390\/rs8040287"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Xu, Y., Wang, L., Ross, K.W., Liu, C., and Berry, K. (2018). Standardized soil moisture index for drought monitoring based on soil moisture active passive observations and 36 years of North American Land Data Assimilation System data: A case study in the Southeast United States. Remote Sens., 10.","DOI":"10.3390\/rs10020301"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Farhani, N., Carreau, J., Kassouk, Z., Le Page, M., Chabaane, Z.L., and Boulet, G. (2022). Analysis of Multispectral Drought Indices in Central Tunisia. Remote Sens., 14.","DOI":"10.3390\/rs14081813"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"5371","DOI":"10.1175\/JCLI-D-17-0775.1","article-title":"Global assessment of the standardized evapotranspiration deficit index (SEDI) for drought analysis and monitoring","volume":"31","author":"Miralles","year":"2018","journal-title":"J. Clim."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Zribi, M., Nativel, S., and Le Page, M. (2021). Analysis of Agronomic Drought in a Highly Anthropogenic Context Based on Satellite Monitoring of Vegetation and Soil Moisture. Remote Sens., 13.","DOI":"10.3390\/rs13142698"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/S0034-4257(03)00174-3","article-title":"Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices","volume":"87","author":"Ji","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1175\/2012EI000434.1","article-title":"Performance of drought indices for ecological, agricultural, and hydrological applications","volume":"16","author":"Camarero","year":"2012","journal-title":"Earth Interact."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"20408","DOI":"10.1007\/s11356-020-12120-0","article-title":"Comparative evaluation of drought indices for monitoring drought based on remote sensing data","volume":"28","author":"Wei","year":"2021","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1016\/j.rse.2013.08.022","article-title":"Using satellite based soil moisture to quantify the water driven variability in NDVI: A case study over mainland Australia","volume":"140","author":"Chen","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Brocca, L., Ciabatta, L., Massari, C., Camici, S., and Tarpanelli, A. (2017). Soil moisture for hydrological applications: Open questions and new opportunities. Water, 9.","DOI":"10.3390\/w9020140"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"5621","DOI":"10.5194\/hess-24-5621-2020","article-title":"The 2018 northern European hydrological drought and its drivers in a historical perspective","volume":"24","author":"Bakke","year":"2020","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1016\/j.jhydrol.2017.06.029","article-title":"Non-linear relationship of hydrological drought responding to meteorological drought and impact of a large reservoir","volume":"551","author":"Wu","year":"2017","journal-title":"J. Hydrol."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"10821","DOI":"10.1029\/2019GL084084","article-title":"Climate, Irrigation, and Land Cover Change Explain Streamflow Trends in Countries Bordering the Northeast Atlantic","volume":"46","author":"Hannaford","year":"2019","journal-title":"Geophys. Res. Lett."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"123990","DOI":"10.1016\/j.jhydrol.2019.123990","article-title":"Assessing the impact of human regulations on hydrological drought development and recovery based on a \u2018simulated-observed\u2019 comparison of the SWAT model","volume":"577","author":"Wu","year":"2019","journal-title":"J. Hydrol."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/0273-1177(95)00079-T","article-title":"Application of vegetation index and brightness temperature for drought detection","volume":"15","author":"Kogan","year":"1995","journal-title":"Adv. Space Res."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/1\/83\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:41:35Z","timestamp":1760132495000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/1\/83"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,25]]},"references-count":72,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,1]]}},"alternative-id":["rs16010083"],"URL":"https:\/\/doi.org\/10.3390\/rs16010083","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,25]]}}}