{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T12:53:43Z","timestamp":1766408023757,"version":"3.44.0"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2024,5,19]],"date-time":"2024-05-19T00:00:00Z","timestamp":1716076800000},"content-version":"vor","delay-in-days":3,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004837","name":"MICINN","doi-asserted-by":"publisher","award":["RTI2018-098160-B-I00"],"award-info":[{"award-number":["RTI2018-098160-B-I00"]}],"id":[{"id":"10.13039\/501100004837","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,8,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The objective of this research is to develop accurate forecasting models for chlorophyll-\u03b1 concentrations at various depths in El Mar Menor, Spain. Chlorophyll-\u03b1 plays a crucial role in assessing eutrophication in this vulnerable ecosystem. To achieve this objective, various deep learning forecasting techniques, including long short-term memory, bidirectional long short-term memory and gated recurrent uni networks, were utilized. The models were designed to forecast the chlorophyll-\u03b1 levels with a 2-week prediction horizon. To enhance the models\u2019 accuracy, a sliding window method combined with a blocked cross-validation procedure for time series was also applied to these techniques. Two input strategies were also tested in this approach: using only chlorophyll-\u03b1 time series and incorporating exogenous variables. The proposed approach significantly improved the accuracy of the predictive models, no matter the forecasting technique employed. Results were remarkable, with $\\overline{\\sigma}$ values reaching approximately 0.90 for the 0.5-m depth level and 0.80 for deeper levels. The proposed forecasting models and methodologies have great potential for predicting eutrophication episodes and acting as decision-making tools for environmental agencies. Accurate prediction of eutrophication episodes through these models could allow for proactive measures to be implemented, resulting in improved environmental management and the preservation of the ecosystem.<\/jats:p>","DOI":"10.1093\/jigpal\/jzae046","type":"journal-article","created":{"date-parts":[[2024,5,19]],"date-time":"2024-05-19T07:27:11Z","timestamp":1716103631000},"source":"Crossref","is-referenced-by-count":1,"title":["Chlorophyll-\u03b1 forecasting using LSTM, bidirectional LSTM and GRU networks in <i>El Mar Menor<\/i> (Spain)"],"prefix":"10.1093","volume":"33","author":[{"given":"Javier","family":"Gonz\u00c1lez-Enrique","sequence":"first","affiliation":[{"name":"Intelligent Modelling of Systems Research Group , Polytechnic School of Engineering (Algeciras), Avda. Ramon Puyol s\/n, 11202-Algeciras, ,","place":["Spain"]},{"name":"University of Cadiz , Polytechnic School of Engineering (Algeciras), Avda. Ramon Puyol s\/n, 11202-Algeciras, ,","place":["Spain"]}]},{"given":"Mar\u00cda Inmaculada","family":"Rodr\u00cdguez-Garc\u00cda","sequence":"additional","affiliation":[{"name":"Intelligent Modelling of Systems Research Group , Polytechnic School of Engineering (Algeciras), Avda. Ramon Puyol s\/n, 11202-Algeciras, ,","place":["Spain"]},{"name":"University of Cadiz , Polytechnic School of Engineering (Algeciras), Avda. Ramon Puyol s\/n, 11202-Algeciras, ,","place":["Spain"]}]},{"given":"Juan Jes\u00das","family":"Ruiz-Aguilar","sequence":"additional","affiliation":[{"name":"Intelligent Modelling of Systems Research Group , Polytechnic School of Engineering (Algeciras), Avda. Ramon Puyol s\/n, 11202-Algeciras, ,","place":["Spain"]},{"name":"University of Cadiz , Polytechnic School of Engineering (Algeciras), Avda. Ramon Puyol s\/n, 11202-Algeciras, ,","place":["Spain"]}]},{"given":"Mar\u00cda Gema","family":"Carrasco-Garc\u00cda","sequence":"additional","affiliation":[{"name":"Intelligent Modelling of Systems Research Group , Polytechnic School of Engineering (Algeciras), Avda. Ramon Puyol s\/n, 11202-Algeciras, ,","place":["Spain"]},{"name":"University of Cadiz , Polytechnic School of Engineering (Algeciras), Avda. Ramon Puyol s\/n, 11202-Algeciras, ,","place":["Spain"]}]},{"given":"Ivan Felis","family":"Enguix","sequence":"additional","affiliation":[{"name":"Centro Tecnol\u00f3gico Naval y del Mar (CTN) , 30320 Fuente \u00c1lamo, Murcia ,","place":["Spain"]}]},{"given":"Ignacio J","family":"Turias","sequence":"additional","affiliation":[{"name":"Intelligent Modelling of Systems Research Group , Polytechnic School of Engineering (Algeciras), Avda. Ramon Puyol s\/n, 11202-Algeciras, ,","place":["Spain"]},{"name":"University of Cadiz , Polytechnic School of Engineering (Algeciras), Avda. Ramon Puyol s\/n, 11202-Algeciras, ,","place":["Spain"]}]}],"member":"286","published-online":{"date-parts":[[2024,5,16]]},"reference":[{"volume-title":"A Kernel Method for Canonical Correlation Analysis","year":"2001","author":"Akaho","key":"2025092510213867400_ref1"},{"key":"2025092510213867400_ref2","first-page":"32","article-title":"Time series modelling and predictive analytics for sustainable environmental management. 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