{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T19:16:05Z","timestamp":1773256565806,"version":"3.50.1"},"reference-count":58,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2023,10,31]],"date-time":"2023-10-31T00:00:00Z","timestamp":1698710400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Water"],"abstract":"<jats:p>Droughts are among the major natural hazards that are spreading to many parts of the world, with huge multi-dimensional impacts. An extensive analysis of drought phenomenon is presented for continental Croatia based on a meteorological E-OBS gridded dataset (0.25\u00b0 \u00d7 0.25\u00b0), within the period of 1950\u20132022. The drought events were characterized by the Standardized Precipitation Evapotranspiration Index (SPEI), applied to different time-scales (6 and 12 months), in order to describe the subannual and annual variability of drought. The spatiotemporal patterns of drought are obtained through principal component analysis (PCA) and K-means clustering (KMC) applied to the SPEI field. An areal drought evolution analysis and the changes in the frequency of occurrence of the periods under drought conditions were achieved using a kernel occurrence rate estimator (KORE). The modified Mann\u2013Kendall (MMK) test, coupled with the Sen\u2019s slope estimator test, are applied to the SPEI series in order to quantify the drought trends throughout the country. According to the history drought events and considering the different morphoclimatic characteristics of the study area, the results showed that Croatia could be divided into three different and spatially well-defined regions with specific temporal and spatial characteristics of droughts (central northern, eastern and southern regions). A manifest increase is shown in the percentage of area affected by drought, as well as in the yearly drought occurrences rates, in both central northern and eastern regions, and an evident decrease is shown in the southern region for both 6- and 12-month SPEI time-scales. In the observation of the drought\u2019s temporal characteristics, it was found that downward trends expressing increasing drought severities were strongly significant in northern and eastern regions, while a few significant upward trends were seen in the southern region. From this study, it is possible to obtain a broader view of the historical behaviour of droughts in Croatia, with the results providing useful support for drought risk assessment and decision-making processes.<\/jats:p>","DOI":"10.3390\/w15213806","type":"journal-article","created":{"date-parts":[[2023,10,31]],"date-time":"2023-10-31T12:48:31Z","timestamp":1698756511000},"page":"3806","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Drought Characterization in Croatia Using E-OBS Gridded Data"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4671-9884","authenticated-orcid":false,"given":"Jo\u00e3o F.","family":"Santos","sequence":"first","affiliation":[{"name":"School of Technology and Management, Polytechnic Institute of Beja, 7800-295 Beja, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4471-1157","authenticated-orcid":false,"given":"Lidija","family":"Tadic","sequence":"additional","affiliation":[{"name":"Faculty of Civil Engineering and Architecture, University of Osijek, 31000 Osijek, Croatia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5221-1139","authenticated-orcid":false,"given":"Maria Manuela","family":"Portela","sequence":"additional","affiliation":[{"name":"Instituto Superior T\u00e9cnico (IST), Civil Engineering Research and Innovation for Sustainability (CERIS), 1040-001 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0059-3953","authenticated-orcid":false,"given":"Luis Angel","family":"Espinosa","sequence":"additional","affiliation":[{"name":"Associa\u00e7\u00e3o do Instituto Superior T\u00e9cnico para a Investiga\u00e7\u00e3o e Desenvolvimento (IST-ID), CERIS, 1000-043 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5177-5824","authenticated-orcid":false,"given":"Tamara","family":"Brlekovi\u0107","sequence":"additional","affiliation":[{"name":"Faculty of Civil Engineering and Architecture, University of Osijek, 31000 Osijek, Croatia"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Dadson, S., Penning-Rowsell, E., Garrick, D., Hope, R., Hall, J., and Hughes, J. (2020). Water Science, Policy, and Management: A Global Challenge, Wiley Blackwell.","DOI":"10.1002\/9781119520627"},{"key":"ref_2","unstructured":"United Nations Convention to Combat Desertification (UNCCD) (2022). Drought in Numbers 2022-Restoration for Readiness and Resilience."},{"key":"ref_3","unstructured":"World Meteorological Organization (WMO) (2022). Drought and Water Scarcity (WMO-No. 1284), World Climate Programme (WCP)."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1483","DOI":"10.1002\/wrcr.20147","article-title":"Making the Distinction between Water Scarcity and Drought Using an Observation-Modeling Framework: Distinguishing between Water Scarcity and Drought","volume":"49","year":"2013","journal-title":"Water Resour. Res."},{"key":"ref_5","unstructured":"McKee, T.B., Doesken, N.J., and Kleist, J. (1993, January 17\u201322). The Relationship of Drought Frequency and Duration to Time Scales. Eighth Conference on Applied Climatology, Anaheim, CA, USA."},{"key":"ref_6","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_7","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1623\/hysj.51.1.83","article-title":"Spatial and Temporal Analysis of Droughts in the Iberian Peninsula (1910\u20132000)","volume":"51","year":"2006","journal-title":"Hydrol. Sci. J."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Santos, J.F., Pulido-Calvo, I., and Portela, M.M. (2010). Spatial and Temporal Variability of Droughts in Portugal. Water Resour. Res., 46.","DOI":"10.1029\/2009WR008071"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1007\/s11269-014-0690-3","article-title":"SPI Modes of Drought Spatial and Temporal Variability in Portugal: Comparing Observations, PT02 and GPCC Gridded Datasets","volume":"29","author":"Raziei","year":"2015","journal-title":"Water Resour. Manag."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Espinosa, L.A., and Portela, M.M. (2022). Grid-Point Rainfall Trends, Teleconnection Patterns, and Regionalised Droughts in Portugal (1919\u20132019). Water, 14.","DOI":"10.3390\/w14121863"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2349","DOI":"10.1007\/s00477-023-02390-8","article-title":"Spatio-Temporal Analysis of Drought in Southern Italy: A Combined Clustering-Forecasting Approach Based on SPEI Index and Artificial Intelligence Algorithms","volume":"37","author":"Granata","year":"2023","journal-title":"Stoch. Environ. Res. Risk Assess."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1016","DOI":"10.2166\/nh.2018.105","article-title":"Cluster Analysis of Drought Variation and Its Mutation Characteristics in Xinjiang Province, during 1961\u20132015","volume":"49","author":"Xie","year":"2018","journal-title":"Hydrol. Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"100938","DOI":"10.1016\/j.ejrh.2021.100938","article-title":"Revealing the Spatio-Temporal Characteristics of Drought in Mozambique and Their Relationship with Large-Scale Climate Variability","volume":"38","author":"Bermudez","year":"2021","journal-title":"J. Hydrol. Reg. Stud."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.gloplacha.2015.01.012","article-title":"European Drought Climatologies and Trends Based on a Multi-Indicator Approach","volume":"127","author":"Spinoni","year":"2015","journal-title":"Glob. Planet. Change"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2201","DOI":"10.5194\/nhess-22-2201-2022","article-title":"Lessons from the 2018\u20132019 European droughts: A collective need for unifying drought risk management","volume":"22","author":"Blauhut","year":"2022","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_16","unstructured":"Barron, E., and van Manen, H. (2022). The World Climate and Security Report 2022: Climate Security Snapshot-The Balkans, Center for Climate and Security. Product of the Expert Group of the International Military Council on Climate and Security; An institute of the Council on Strategic Risks."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13705-021-00328-y","article-title":"Climate Change in the Western Balkans and EU Green Deal: Status, Mitigation and Challenges","volume":"12","author":"Knez","year":"2022","journal-title":"Energy Sustain. Soc."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"41","DOI":"10.13167\/2021.22.4","article-title":"Application of Principal Component Analysis to Drought Indicators of Three Representative Croatian Regions","volume":"12","author":"Juraj","year":"2021","journal-title":"Elektron. \u010casopis Gra\u0111ev. Fak. Osijek"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Brlekovi\u0107, T., and Tadi\u0107, L. (2022). Hydrological Drought Assessment in a Small Lowland Catchment in Croatia. Hydrology, 9.","DOI":"10.3390\/hydrology9050079"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1007\/s00704-020-03330-0","article-title":"Drought Indices for the Zagreb-Gri\u010d Observatory with an Overview of Drought Damage in Agriculture in Croatia","volume":"142","author":"Likso","year":"2020","journal-title":"Theor. Appl. Climatol."},{"key":"ref_21","unstructured":"Revelle, W. (2023). An Introduction to Psychometric Theory with Applications in R, Springer International Publishing. [2023rd ed.]."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/S0022-1694(97)00125-X","article-title":"A Modified Mann-Kendall Trend Test for Autocorrelated Data","volume":"204","author":"Hamed","year":"1998","journal-title":"J. Hydrol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1007\/s00704-022-04241-y","article-title":"Croatian High-Resolution Monthly Gridded Dataset of Homogenised Surface Air Temperature","volume":"151","author":"Guijarro","year":"2023","journal-title":"Theor. Appl. Climatol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1007\/s00704-014-1217-9","article-title":"Trends in Precipitation Indices in Croatia, 1961\u20132010","volume":"121","year":"2015","journal-title":"Theor. Appl. Climatol."},{"key":"ref_25","first-page":"31","article-title":"Drought Vulnerability in Croatia","volume":"79","author":"Cindric","year":"2014","journal-title":"Agric. Conspec. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Cindric Kalin, K., Patalen, L., Marinovic, I., and Pasaric, Z. (2022, January 5\u20139). Trends in Temperature and Precipitation Indices in Croatia, 1961\u20132020. Proceedings of the Copernicus Meetings, EMS Annual Meeting 2022, Bonn, Germany.","DOI":"10.5194\/ems2022-212"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"9391","DOI":"10.1029\/2017JD028200","article-title":"An Ensemble Version of the E-OBS Temperature and Precipitation Data Sets","volume":"123","author":"Cornes","year":"2018","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"55","DOI":"10.2307\/210739","article-title":"An Approach toward a Rational Classification of Climate","volume":"38","author":"Thornthwaite","year":"1948","journal-title":"Geogr. Rev."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.pce.2017.02.008","article-title":"Evaluation of Drought Using SPEI Drought Class Transitions and Log-Linear Models for Different Agro-Ecological Regions of India","volume":"100","author":"Alam","year":"2017","journal-title":"Phys. Chem. Earth Parts ABC"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"111979","DOI":"10.1016\/j.jenvman.2021.111979","article-title":"An Improved SPEI Drought Forecasting Approach Using the Long Short-Term Memory Neural Network","volume":"283","author":"Dikshit","year":"2021","journal-title":"J. Environ. Manag."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Svoboda, M.D., and Fuchs, B.A. (2016). Handbook of Drought Indicators and Indices, World Meteorological Organization.","DOI":"10.1201\/b22009-11"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1280","DOI":"10.1038\/s41598-020-80527-3","article-title":"Spatiotemporal Drought Analysis by the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) in Sichuan Province, China","volume":"11","author":"Liu","year":"2021","journal-title":"Sci. Rep."},{"key":"ref_33","unstructured":"Agnew, C. (Drought Network News, 2000). Using the SPI to Identify Drought, Drought Network News."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.jhydrol.2012.11.028","article-title":"Hydrological Response to Climate Variability at Different Time Scales: A Study in the Ebro Basin","volume":"477","author":"Zabalza","year":"2013","journal-title":"J. Hydrol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1023\/A:1024716530289","article-title":"Spatial Variability of Drought: An Analysis of the SPI in Sicily","volume":"17","author":"Bonaccorso","year":"2003","journal-title":"Water Resour. Manag."},{"key":"ref_36","unstructured":"Smith, L.I. (2002). A Tutorial on Principal Components Analysis, Cornell University."},{"key":"ref_37","unstructured":"Hair, J.F. (2006). Multivariate Data Analysis, Pearson Prentice Hall. [6th ed.]."},{"key":"ref_38","unstructured":"Rao, C.R., Miller, J.P., and Rao, D.C.R. (2011). Essential Statistical Methods for Medical Statistics, Elsevier."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"5","DOI":"10.3354\/cr026005","article-title":"Drought Patterns in the Mediterranean Area: The Valencia Region (Eastern Spain)","volume":"26","year":"2004","journal-title":"Clim. Res."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1061\/(ASCE)1084-0699(2008)13:4(205)","article-title":"Streamflow Regionalization: Case Study of Turkey","volume":"13","author":"Kahya","year":"2008","journal-title":"J. Hydrol. Eng."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1061\/(ASCE)1084-0699(2000)5:2(172)","article-title":"Multivariate Technique for Baseflow Separation Using Water Quality Data","volume":"5","author":"Shukla","year":"2000","journal-title":"J. Hydrol. Eng."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1038\/nature01928","article-title":"No Upward Trends in the Occurrence of Extreme Floods in Central Europe","volume":"425","author":"Mudelsee","year":"2003","journal-title":"Nature"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"241","DOI":"10.5194\/hess-16-241-2012","article-title":"Nonstationarities in the Occurrence Rates of Flood Events in Portuguese Watersheds","volume":"16","author":"Silva","year":"2012","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"792","DOI":"10.2166\/nh.2014.074","article-title":"Drought Analysis in Southern Paraguay, Brazil and Northern Argentina: Regionalization, Occurrence Rate and Rainfall Thresholds","volume":"46","author":"Portela","year":"2015","journal-title":"Hydrol. Res."},{"key":"ref_45","first-page":"15","article-title":"A Comprehensive Drought Analysis in Slovakia Using SPI","volume":"51","author":"Portela","year":"2015","journal-title":"Eur. Water"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"138","DOI":"10.2307\/2347366","article-title":"A Kernel Method for Smoothing Point Process Data","volume":"34","author":"Diggle","year":"1985","journal-title":"Appl. Stat."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1379","DOI":"10.1080\/01621459.1968.10480934","article-title":"Estimates of the Regression Coefficient Based on Kendall\u2019s Tau","volume":"63","author":"Sen","year":"1968","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"245","DOI":"10.2307\/1907187","article-title":"Nonparametric Tests Against Trend","volume":"13","author":"Mann","year":"1945","journal-title":"Econometrica"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"20694","DOI":"10.1038\/s41598-022-24146-0","article-title":"Spatiotemporal Drought Analysis in Bangladesh Using the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI)","volume":"12","author":"Kamruzzaman","year":"2022","journal-title":"Sci. Rep."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1007\/s00704-014-1368-8","article-title":"Analysis of the Extraordinary 2011\/2012 Drought in Croatia","volume":"123","year":"2016","journal-title":"Theor. Appl. Climatol."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Silverman, B.W. (2018). Density Estimation for Statistics and Data Analysis, Routledge. [1st ed.].","DOI":"10.1201\/9781315140919"},{"key":"ref_52","unstructured":"(2023, June 11). Climate change adaptation strategy in the Republic of Croatia for the period up to 2040 with a view to 2070. Official Gazette of the Republic of Croatia 46\/2020. Available online: https:\/\/faolex.fao.org\/docs\/pdf\/cro207819.pdf."},{"key":"ref_53","unstructured":"(2023, May 20). Seventh National Communication of the Republic of Croatia under the United Nation Framework Convention on the Climate Change (UNFCCC). Available online: https:\/\/unfccc.int\/sites\/default\/files\/resource\/IDR7_HRV_complete.pdf."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"5503","DOI":"10.1002\/joc.7545","article-title":"Regional Patterns of Dry Spell Durations in Croatia","volume":"42","year":"2022","journal-title":"Int. J. Climatol."},{"key":"ref_55","unstructured":"Agricultural Regions of Croatia (2013). The Soils of Croatia, Springer."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Vrsalovi\u0107, A., Andri\u0107, I., Bonacci, O., and Kov\u010di\u0107, O. (2023). Climate Variability and Trends in Imotski, Croatia: An Analysis of Temperature and Precipitation. Atmosphere, 14.","DOI":"10.3390\/atmos14050861"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"3219","DOI":"10.1007\/s13762-021-03453-5","article-title":"Multi-Temporal Analysis for Drought Classifying Based on SPEI Gridded Data and Hybrid Maximal Overlap Discrete Wavelet Transform","volume":"19","author":"Roushangar","year":"2022","journal-title":"Int. J. Environ. Sci. Technol."},{"key":"ref_58","unstructured":"Food and Agriculture Organization of the United Nations (1998). Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements, Food and Agriculture Organization of the United Nations. FAO Irrigation and Drainage Paper."}],"container-title":["Water"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-4441\/15\/21\/3806\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:14:47Z","timestamp":1760130887000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-4441\/15\/21\/3806"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,31]]},"references-count":58,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2023,11]]}},"alternative-id":["w15213806"],"URL":"https:\/\/doi.org\/10.3390\/w15213806","relation":{},"ISSN":["2073-4441"],"issn-type":[{"value":"2073-4441","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,31]]}}}