[Albek, M., Albek, E., 2009. Stream temperature trends in Turkey. Clean Soil Air & Water, 37, 142–149.10.1002/clen.200700159]Search in Google Scholar
[Ayllón, D., Almodóvar, A., Nicola, G.G., Parra, I., Elvira, B., 2012. A new biological indicator to assess the ecological status of Mediterranean trout type streams. Ecological Indicators, 20, 295–303.10.1016/j.ecolind.2012.02.028]Search in Google Scholar
[Bonacci, O., Andrić, I., 2010. Impact of an inter-basin water transfer and reservoir operation on a karst open streamflow hydro-logical regime: an example from the Dinaric karst (Croatia). Hydrological Processes, 24, 3852–3863.10.1002/hyp.7817]Search in Google Scholar
[Bonacci, O., Trninić, D., Roje-Bonacci, T., 2008. Analysis of the water temperature regime of the Danube and its tributaries in Croatia. Hydrological Processes, 22, 1014–1021.10.1002/hyp.6975]Search in Google Scholar
[Chen, D., Hu, M., Guo, Y., Dahlgren, R.A., 2016. Changes in river water temperature between 1980 and 2012 in Yongan water-shed, eastern China: magnitude, drivers and models. Journal of Hydrology, 533, 191–199.10.1016/j.jhydrol.2015.12.005]Search in Google Scholar
[Cingi, S., Keinänen, M., Vuorinen, P.J., 2010. Elevated water temperature impairs fertilization and embryonic development of whitefish Coregonus lavaretus. Journal of Fish Biology, 76, 502–521.10.1111/j.1095-8649.2009.02502.x]Search in Google Scholar
[Cox, B.A., Whitehead, P.G., 2009. Impacts of climate change scenarios on dissolved oxygen in the River Thames, UK. Hydrology Research, 40, 138–152.10.2166/nh.2009.096]Search in Google Scholar
[DeWeber, J.T., Wagner, T., 2014. A regional neural network ensemble for predicting mean daily river water temperature. Journal of Hydrology, 517, 187–200.10.1016/j.jhydrol.2014.05.035]Search in Google Scholar
[Feng, M., Zolezzi, G., Pusch, M., 2018. Effects of thermopeaking on the thermal response of alpine river systems to heatwaves. Science of the Total Environment, 612, 1266–1275.10.1016/j.scitotenv.2017.09.042]Search in Google Scholar
[Frančišković-Bilinski, S., Bhattacharya, A.K., Bilinski, H., Bhattacharya, B.D., Mitra, A., Sarkar, S.K., 2012. Fluvial geo-morphology of the Kupa River drainage basin, Croatia: a perspective of its application in river management and pollution studies. Zeitschrift für Geomorphologie, 56, 93–119.10.1127/0372-8854/2011/0056]Search in Google Scholar
[Fullerton, A.H., Torgersen, C.E., Lawler, J.J., Steel, E.A., Eber-sole, J.L., Lee, S.Y., 2018. Longitudinal thermal heterogeneity in rivers and refugia for coldwater species: effects of scale and climate change. Aquatic Sciences, 80, 3.10.1007/s00027-017-0557-9]Search in Google Scholar
[Gooseff, M.M., Strzepek, K., Chapra, S.C., 2005. Modeling the potential effects of climate change on water temperature downstream of a shallow reservoir, lower Madison River, MT. Climatic Change, 68, 331–353.10.1007/s10584-005-9076-0]Search in Google Scholar
[Hadzima-Nyarko, M., Rabi, A., Šperac, M., 2014. Implementation of artificial neural networks in modeling the water-air temperature relationship of the river Drava. Water Resources Management, 28, 1379–1394.10.1007/s11269-014-0557-7]Search in Google Scholar
[Hardenbicker, P., Viergutz, C., Becker, A., Kirchesch, V., Nilson, E., Fischer, H., 2017. Water temperature increases in the river Rhine in response to climate change. Regional Environmental Change, 17, 299–308.10.1007/s10113-016-1006-3]Search in Google Scholar
[Heddam, S., 2016. New modelling strategy based on radial basis function neural network (RBFNN) for predicting dissolved oxygen concentration using the components of the Gregorian calendar as inputs: case study of Clackamas River, Oregon, USA. Modeling Earth Systems & Environment, 2, 1–5.10.1007/s40808-016-0232-5]Search in Google Scholar
[Heddam, S., Kisi, O., 2017. Extreme learning machines: a new approach for modeling dissolved oxygen (DO) concentration with and without water quality variables as predictors. Environmental Science and Pollution Research, 24, 16702–16724.10.1007/s11356-017-9283-z]Search in Google Scholar
[Isaak, D.J., Wollrab, S., Horan, D., Chandler, G., 2012. Climate change effects on stream and river temperatures across the northwest U.S. from 1980–2009 and implications for salmonid fishes. Climatic Change, 113, 499–524.10.1007/s10584-011-0326-z]Search in Google Scholar
[Jackson, F.L., Fryer, R.J., Hannah, D.M., Millar, C.P., Malcolm, I.A., 2018. A spatio-temporal statistical model of maximum daily river temperatures to inform the management of Scotland’s Atlantic salmon rivers under climate change. Science of the Total Environment, 621, 1543–1558.10.1016/j.scitotenv.2017.09.010]Search in Google Scholar
[Kim, J.H., Park, H.J., Hwang, I.K., Han, J.M., Kim, D.H., Oh, C.W., Lee, J.S., Kang, J.C., 2017. Toxic effects of juvenile sablefish, Anoplopoma fimbria by ammonia exposure at different water temperature. Environmental Toxicology and Pharmacology, 54, 169–176.10.1016/j.etap.2017.07.008]Search in Google Scholar
[Leblanc, R.T., Brown, R.D., Fitzgibbon, J.E., 1997. Modeling the effects of land use change on the water temperature in unregulated urban streams. Journal of Environmental Management, 49, 445–469.10.1006/jema.1996.0106]Search in Google Scholar
[Lepori, F., Pozzoni, M., Pera, S., 2014. What drives warming trends in streams? A case study from the Alpine Foothills. River Research and Applications, 31, 663–675.10.1002/rra.2763]Search in Google Scholar
[Markovic, D., Scharfenberger, U., Schmutz, S., Pletterbauer, F., Wolter, C., 2013. Variability and alterations of water temperatures across the Elbe and Danube River Basins. Climatic Change, 119, 375–389.10.1007/s10584-013-0725-4]Search in Google Scholar
[Moatar, F., Gailhard, J., 2006. Water temperature behaviour in the River Loire since 1976 and 1881. Comptes Rendus Geoscience, 338, 319–328.10.1016/j.crte.2006.02.011]Search in Google Scholar
[Null, S.E., Viers, J.H., Deas, M.L., Tanaka, S.K., Mount, J.F., 2013. Stream temperature sensitivity to climate warming in California’s Sierra Nevada: impacts to coldwater habitat. Climatic Change, 116, 149–170.10.1007/s10584-012-0459-8]Search in Google Scholar
[Orr, H.G., Simpson, G.L., des Clers, S., Watts, G., Hughes, M., Hannaford, J., Dunbar, M.J., Laizé, C.L.R., Wilby, R.L., Battarbee, R.W., Evans, R., 2015. Detecting changing river temperatures in England and Wales. Hydrological Processes, 29, 752–766.10.1002/hyp.10181]Search in Google Scholar
[Pekárová, P., Miklánek, P., Halmová, D., Onderka, M., Pekár, J., Kučárová, K., Liová, S., Škoda, P., 2011. Long-term trend and multi-annual variability of water temperature in the pristine Bela River basin (Slovakia). Journal of Hydrology, 400, 333–340.10.1016/j.jhydrol.2011.01.048]Search in Google Scholar
[Piotrowski, A.P., Napiorkowski, M.J., Napiorkowski, J.J., Osuch, M., 2015. Comparing various artificial neural network types for water temperature prediction in rivers. Journal of Hydrology, 529, 302–315.10.1016/j.jhydrol.2015.07.044]Search in Google Scholar
[Rice, K.C., Jastram, J.D., 2015. Rising air and stream-water temperatures in Chesapeake Bay region, USA. Climatic Change, 128, 127–138.10.1007/s10584-014-1295-9]Search in Google Scholar
[Schär, C., Vidale, P.L., Lüthi, D., Frei, C., Häberli, C., Liniger, M.A., Appenzeller, C., 2004. The role of increasing temperature variability in European summer heatwaves. Nature, 427, 332–336.10.1038/nature02300]Search in Google Scholar
[Sohrabi, M.M., Benjankar, R., Tonina, D., Wenger, S.J., Isaak, D.J., 2017. Estimation of daily stream water temperatures with a Bayesian regression approach. Hydrological Processes, 31, 1719–1733.10.1002/hyp.11139]Search in Google Scholar
[Temizyurek, M., Dadaser-Celik, F., 2018. Modelling the effects of meteorological parameters on water temperature using artificial neural networks. Water Science and Technology, 77, 1724–1733.10.2166/wst.2018.058]Search in Google Scholar
[Toffolon, M., Piccolroaz, S., 2015. A hybrid model for river water temperature as a function of air temperature and discharge. Environmental Research Letters, 10, 114011.10.1088/1748-9326/10/11/114011]Search in Google Scholar
[van Vliet, M.T.H., Ludwig, F., Zwolsman, J.J.G., Weedon, G.P., Kabat, P., 2011. Global river temperatures and sensitivity to atmospheric warming and changes in river flow. Water Resources Research, 47, 247–255.10.1029/2010WR009198]Search in Google Scholar
[van Vliet, M.T.H., Franssen, W.H.P., Yearsley, J.R., Ludwig, F., Haddeland, I., Lettenmaier, D.P., Kabat, P., 2013. Global river discharge and water temperature under climate change. Global Environmental Change, 23, 450–464.10.1016/j.gloenvcha.2012.11.002]Search in Google Scholar
[Webb, B.W., Clack, P.D., Walling, D.E., 2003. Water–air temperature relationships in a Devon river system and the role of flow. Hydrological Processes, 17, 3069–3084.10.1002/hyp.1280]Search in Google Scholar
[Žganec, K., 2012. The effects of water diversion and climate change on hydrological alteration and temperature regime of karst rivers in central Croatia. Environmental Monitoring and Assessment, 184, 5705–5723.10.1007/s10661-011-2375-1]Search in Google Scholar
[Zhu, S., Heddam, S., Nyarko, E.K., Hadzima-Nyarko, M., Piccolroaz, S., Wu, S., 2019. Modeling daily water temperature for rivers: comparison between adaptive neuro-fuzzy inference systems and artificial neural networks models. Environmental Science and Pollution Research, 26, 402–420.10.1007/s11356-018-3650-2]Search in Google Scholar