{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T23:58:31Z","timestamp":1770681511340,"version":"3.49.0"},"reference-count":50,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,4,25]],"date-time":"2024-04-25T00:00:00Z","timestamp":1714003200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Program for Research of the National Association of Technical Universities-GNaC","award":["174\/4.12.2023"],"award-info":[{"award-number":["174\/4.12.2023"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Water bodies can offer local microclimates that have the potential to attenuate the effects of urban heat islands by reducing local temperature. This capability is shaded when the river is channelized. In such cases, the river temperature rises during hot periods, leading to negative impacts on the water quality. The main aim of this paper is to develop a local simple model to predict the temperature of the D\u00e2mbovi\u021ba River at its exit from Bucharest City, the capital of Romania. The location is chosen based on the historical critical impacts, in terms of extreme heatwaves that took place during hot summers, as well as future possible risks due to climate change. The water temperature prediction model is based on an artificial neural network that uses the Levenberg\u2013Marquardt algorithm, due to its stability and rapid convergence capabilities. The model forecasts, with an accuracy of \u00b11 \u00b0C, the water temperature in an ungauged, downstream location, as a function of measured air and upstream water temperatures. The proposed model represents a first attempt to provide water managers in Bucharest City with a useful tool that will allow them to take timely measures to counteract the unwanted effects that can be generated by high water temperatures.<\/jats:p>","DOI":"10.3390\/rs16091513","type":"journal-article","created":{"date-parts":[[2024,4,25]],"date-time":"2024-04-25T05:26:13Z","timestamp":1714022773000},"page":"1513","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Simple Artificial Neural Model to Predict Dambovita River Temperature Affected by Urban Heat Islands in Bucharest City"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9343-2336","authenticated-orcid":false,"given":"Cristina-Sorana","family":"Ionescu","sequence":"first","affiliation":[{"name":"Department of Hydraulics, Hydraulic Machinery and Environmental Engineering, Faculty of Energy Engineering, National University of Science and Technology Politehnica Bucharest, 060042 Bucuresti, Romania"}]},{"given":"Ioana","family":"Opri\u0219","sequence":"additional","affiliation":[{"name":"Department of Power Generation and Use, Faculty of Energy Engineering, National University of Science and Technology Politehnica Bucharest, 060042 Bucuresti, Romania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8841-0981","authenticated-orcid":false,"given":"Daniela-Elena","family":"Gogoa\u0219e Nistoran","sequence":"additional","affiliation":[{"name":"Department of Hydraulics, Hydraulic Machinery and Environmental Engineering, Faculty of Energy Engineering, National University of Science and Technology Politehnica Bucharest, 060042 Bucuresti, Romania"}]},{"given":"Cristian","family":"Copil\u0103u","sequence":"additional","affiliation":[{"name":"Department of Power Generation and Use, Faculty of Energy Engineering, National University of Science and Technology Politehnica Bucharest, 060042 Bucuresti, Romania"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.proeng.2016.10.002","article-title":"Research on Urban Heat-Island Effect","volume":"169","author":"Yang","year":"2016","journal-title":"Procedia Eng."},{"key":"ref_2","first-page":"127","article-title":"Monitoring patterns of urban heat islands of the fast-growing Shanghai metropolis, China: Using time-series of Landsat TM\/ETM+ data","volume":"19","author":"Li","year":"2012","journal-title":"Int. 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