{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T01:03:22Z","timestamp":1790643802673,"version":"4.1.0"},"reference-count":34,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T00:00:00Z","timestamp":1788393600000},"content-version":"vor","delay-in-days":2,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Water Environment Research"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Groundwater quality assessment in hyper arid aquifers is often limited by sparse monitoring, incomplete hydraulic data, and difficulty separating prior hydrochemical conditions from short\u2010term meteorological forcing. This study develops a hydrochemically grounded and machine learning framework with internal transferability testing to diagnose chloride\u2010dominated salinization in the Rawdatain\u2013Umm Al Aish freshwater aquifers of northern Kuwait. The framework combines four components: comparison of pre\u20101990 baseline chemistry with 2012\u20132015 observations, chloride\u2010specific salinization diagnostics, separation of predictors into meteorological, space\u2013time, prior\u2010chemistry, and hybrid groups, and model evaluation using random, temporal, and grouped\u2010well validation. The analysis also integrates spatial salinity mapping, Cl\u2013TDS analysis, Na:Cl ratios, carbonate\/sulfate balance, principal component analysis (PCA), and supervised learning models to evaluate both hydrochemical change and predictive structure. This integrated analysis shows substantial deterioration relative to the historical baseline. Median TDS increased from 905.5 to 1821.0\u2009mg\/L (+101.1%), whereas median Cl, Ca, Mg, and Na increased by 228.5%, 194.6%, 227.0%, and 75.3%, respectively. HCO\n                    <jats:sub>3<\/jats:sub>\n                    remained broadly stable, whereas NO\n                    <jats:sub>3<\/jats:sub>\n                    declined by 43.5%. Diagnostic plots and PCA indicate chloride\u2010rich salinization governed by mixed geochemical and mixing processes rather than simple halite dissolution alone. Random holdout models performed well, with\n                    <jats:italic>R<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    values of 0.947 for SO\n                    <jats:sub>4<\/jats:sub>\n                    , 0.913 for Na, 0.912 for Ca, 0.877 for HCO\n                    <jats:sub>3<\/jats:sub>\n                    , 0.868 for TDS, 0.808 for NO\n                    <jats:sub>3<\/jats:sub>\n                    , 0.807 for Cl, and 0.673 for Mg. However, validation performance was analyte\u2010specific: Cl declined mainly under temporal holdout, NO\n                    <jats:sub>3<\/jats:sub>\n                    declined under grouped\u2010well holdout, and Mg showed the lowest random\u2010holdout skill and largest train\u2013test gap despite higher grouped\u2010well performance. Predictor importance showed that spatial coordinates, elevation, and lagged chemistry were more influential than meteorological predictors alone. The framework supports targeted monitoring of chloride\u2010rich hotspots and validation\u2010aware groundwater quality decision support in hyper arid freshwater reserves.\n                  <\/jats:p>","DOI":"10.1002\/wer.70543","type":"journal-article","created":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T07:38:05Z","timestamp":1788421085000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Hydrochemical Evolution and Predictive Modeling of Chloride\u2010Dominated Groundwater Salinization in Northern Kuwait"],"prefix":"10.1002","volume":"98","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9148-3954","authenticated-orcid":false,"given":"Abdullah A.","family":"Alsumaiei","sequence":"first","affiliation":[{"name":"Department of Civil Engineering, College of Engineering and Petroleum (COEP) Kuwait University  Shadadiya Kuwait"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3132-8191","authenticated-orcid":false,"given":"Mosaed S.","family":"Alrashidi","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, College of Engineering and Petroleum (COEP) Kuwait University  Shadadiya Kuwait"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,3]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/hyp.70100"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/hyp.13649"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10661-025-14311-z"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF00767410"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1080\/1573062X.2026.2625397"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10040-021-02411-2"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1021\/acs.est.1c08682"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhydrol.2008.02.015"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1029\/2026WR043411"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40808\u2010025\u201002548\u2010z"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.3390\/w14030483"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11269-005-6810-3"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.1623\/hysj.53.1.204"},{"key":"e_1_2_11_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.heliyon.2024.e36606"},{"key":"e_1_2_11_16_1","doi-asserted-by":"publisher","DOI":"10.3390\/w16182639"},{"key":"e_1_2_11_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.gsd.2024.101272"},{"key":"e_1_2_11_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.infsof.2023.107268"},{"key":"e_1_2_11_19_1","doi-asserted-by":"publisher","DOI":"10.2166\/ws.2024.212"},{"key":"e_1_2_11_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0043-1354(99)00225-0"},{"key":"e_1_2_11_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.envpol.2024.124242"},{"key":"e_1_2_11_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2019.03.045"},{"key":"e_1_2_11_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.envres.2024.120683"},{"key":"e_1_2_11_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2025.3649568"},{"key":"e_1_2_11_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecolind.2023.110697"},{"key":"e_1_2_11_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/0012-8252(95)00068-2"},{"key":"e_1_2_11_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2019.06.320"},{"key":"e_1_2_11_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2987324"},{"key":"e_1_2_11_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.catena.2020.104864"},{"key":"e_1_2_11_30_1","doi-asserted-by":"publisher","DOI":"10.5194\/hess-14-1863-2010"},{"key":"e_1_2_11_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2024.174973"},{"key":"e_1_2_11_32_1","doi-asserted-by":"publisher","DOI":"10.1002\/wat2.1533"},{"key":"e_1_2_11_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.watres.2022.118530"},{"key":"e_1_2_11_34_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.envres.2022.115178"},{"key":"e_1_2_11_35_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2026.147698"}],"container-title":["Water 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