Open Access
Knowl. Managt. Aquatic Ecosyst.
Number 398, 2010
Article Number 04
Number of page(s) 20
Published online 28 October 2010
  • Ahmadi-Nedushan B., St-Hilaire A., Ouarda T.B.M.J., Bilodeau L., Robichaud E., Thiemonge N. and Bobee B., 2007. Predicting river water temperatures using stochastic models: case study of the Moisie River (Quebec, Canada). Hydrol. Process., 21, 21–34. [CrossRef] [Google Scholar]
  • Akaike H., 1974. A new look at the statistical model identification. IEEE Trans. Automat. Contr., 19, 716–723. [Google Scholar]
  • Alabaster J.S., 1967. The survival of salmon (Salmo salar L.) ans sea trout (S. trutta L.) in fresh and saline water at high temperatures. Water Res., 1, 717–730. [CrossRef] [Google Scholar]
  • Benyahya L., Caissie D., St-Hilaire A., Ouarda T.B.M.J. and Bobee B., 2007a. A review of statistical water temperature models. Can. Water Resources J., 32, 179–192. [CrossRef] [Google Scholar]
  • Benyahya L., St-Hilaire A., Ouarda T.B.M.J., Bobee B. and Ahmadi-Nedushan B., 2007b. Modeling of water temperatures based on stochastic approaches: case study of the Deschutes River. J. Environ. Eng. Sci., 6, 437–448. [CrossRef] [Google Scholar]
  • Benyahya L., Caissie D., El-Jabi N. and Satish M.G., 2010. Comparison of microclimate vs. remote meteorological data and results applied to a water temperature model (Miramichi River, Canada). J. Hydrol., 380, 247–259. [CrossRef] [Google Scholar]
  • Berger J.O., 1985. Certain Standard Loss Functions. In: Statistical decision theory and Bayesian Analysis, 2nd edn., Springer-Verlag, New York, 60–64. [Google Scholar]
  • Caissie D., 2006. The thermal regime of rivers: a review. Freshw. Biol., 51, 1389–1406. [Google Scholar]
  • Caissie D., El-Jabi N. and St-Hilaire A., 1998. Stochastic modelling of water temperatures in a small stream using air to water relations. Can. J. Civ. Eng., 25, 250–260. [CrossRef] [Google Scholar]
  • Caissie D., Satish M.G. and El-Jabi N., 2005. Predicting river water temperatures using the equilibrium temperature concept with application on Miramichi River catchments (New Brunswick, Canada). Hydrol. Process., 19, 2137–2159. [CrossRef] [Google Scholar]
  • Caissie D., Satish M.G. and El-Jabi N., 2007. Predicting water temperatures using a deterministic model: Application on Miramichi River catchments (New Brunswick, Canada). J. Hydrol., 336, 303–315. [CrossRef] [Google Scholar]
  • Chanseau M., Croze O. and Larinier M., 1999. Impact des aménagements sur la migration anadrome du saumon atlantique (Salmo salar L.) sur le gave de Pau (France). Bull. Fr. Pêche Piscic., 353-354, 211–237. [CrossRef] [EDP Sciences] [Google Scholar]
  • Chenard J.F. and Caissie D., 2008. Stream temperature modelling using artificial neural networks: application on Catamaran Brook, New Brunswick, Canada. Hydrol. Process., 22, 3361–3372. [CrossRef] [Google Scholar]
  • Cluis D.A., 1972. Relationship between stream water temperature and ambient temperature – a simple autoregressive model for mean daily stream water temperature fluctuations. Nordic Hydrology, 3, 65–71. [Google Scholar]
  • Croze O., Blot E., Delmas F., Alesina R., Jourdan H., Bau F. and Breinig T., 2006. Suivi de la qualité de l’eau de la Garonne lors de la migration anadrome du saumon en amont de Golfech. RA06.04, GHAAPE, Toulouse. [Google Scholar]
  • Decola J.N., 1970. Water quality requirements for Atlantic salmon. CWT–10-16; PB–230733, Federal Water Quality Administration, Needham Heights, New England Basins Office. [Google Scholar]
  • Edinger J.E., Duttweiler D.W. and Geyer J.C., 1968. The response of water temperatures to meteorological conditions. Water Resour. Res., 4, 1137–1143. [CrossRef] [Google Scholar]
  • El-Jabi N., El-Kourdahi G. and Caissie D., 1995. Modélisation stochastique de la température de l’eau en rivière. Revue des Sciences de l’Eau, 8, 77–95. [Google Scholar]
  • Elliott J.M., 1991. Tolerance and resistance to thermal stress in juvenile Atlantic salmon, Salmo salar. Freshw. Biol., 25, 61–70. [CrossRef] [Google Scholar]
  • Erickson T.R. and Stefan H.G., 2000. Linear air/water temperature correlations for streams during open water periods. J. Hydrol. Eng., 5, 317–321. [CrossRef] [Google Scholar]
  • Fairchild W.L., Swansburg E.O., Arsenault J.T. and Brown S.B., 1999. Does an association between pesticide use and subsequent declines in catch of Atlantic salmon (Salmo salar) represent a case of endocrine disruption? Environ. Health Perspect., 107, 349–357. [CrossRef] [Google Scholar]
  • Kim K.S. and Chapra S.C., 1997. Temperature model for highly transient shallow streams. J. Hydraul. Eng., 123, 30–40. [CrossRef] [Google Scholar]
  • Kothandaraman V., 1971. Analysis of water temperature variations in large river. Journal of the Sanitary Engineering Division-ASCE, 97, 19–31. [Google Scholar]
  • Leopold L.B., Wolman M.G. and Miller J.P., 1964. Fluvial process in Geomorphology, W.H. Freeman and Co., San Francisco. [Google Scholar]
  • Marcé R. and Armengol J., 2008. Modelling river water temperature using deterministic, empirical, and hybrid formulations in a Mediterranean stream. Hydrol. Process., 22, 3418–3430. [CrossRef] [Google Scholar]
  • Marcotte N. and Duong V.-L., 1973. Le calcul de la température de l’eau des rivières. J. Hydrol., 18, 273–287. [CrossRef] [Google Scholar]
  • Moatar F. and Gailhard J., 2006. Water temperature behaviour in the River Loire since 1976 and 1881. C. R. Geosci., 338, 319–328. [CrossRef] [Google Scholar]
  • Mohseni O. and Stefan H.G., 1999. Stream temperature air temperature relationship: a physical interpretation. J. Hydrol., 218, 128–141. [CrossRef] [Google Scholar]
  • Mohseni O., Stefan H.G. and Erickson T.R., 1998. A nonlinear regression model for weekly stream temperatures. Water Resour. Res., 34, 2685–2692. [CrossRef] [Google Scholar]
  • Morin G. and Couillard D., 1990. Predicting river temperatures with a hydrological model. In: Encyclopedia of Fluid Mechanic, Surface and Groundwater Flow Phenomena, Golf Publishing Company, Houston, 171–209. [Google Scholar]
  • Pilgrim J.M., Fang X. and Stefan H.G., 1998. Stream temperature correlations with air temperatures in Minnesota: implications for climate warning. J. Am. Water Resour. Assoc., 34, 1109–1121. [CrossRef] [Google Scholar]
  • Poirel A., Lauters F. and Desaint B., 2008. 1977–2006 : Trente années de mesures des températures de l’eau dans le Bassin du Rhône. Hydroécol. Appl., 16, 191–213. [CrossRef] [EDP Sciences] [Google Scholar]
  • Raphael J.M., 1962. Prediction of temperature in rivers and reservoirs. Journal of the Power Division, 88, 157–181. [Google Scholar]
  • Sinokrot B.A. and Stefan H.G., 1984. Stream water-temperature sensitivity to weather and bed parameters. J. Hydraul. Eng., 120, 722–736. [CrossRef] [Google Scholar]
  • Sinokrot B.A. and Stefan H.G., 1993. Stream Temperature Dynamics – Measurements and Modeling. Water Resour. Res., 29, 2299–2312. [CrossRef] [Google Scholar]
  • Sinokrot B.A. and Stefan H.G., 1994. Stream water-temperature sensitivity to weather and bed parameters. J. Hydraul. Eng., 120, 722–736. [Google Scholar]
  • Stefan H.G. and Preud’homme E.B., 1993. Stream temperature estimation from air temperature. J. Am. Water Resour. Assoc., 29, 27–45. [CrossRef] [Google Scholar]
  • Swansburg E., Chaput G., Moore D., Caissie D. and El-Jabi N., 2002. Size variability of juvenile Atlantic salmon: links to environmental conditions. J. Fish Biol., 61, 661–683. [CrossRef] [Google Scholar]
  • Torgersen C.E., Faux R.N., McIntosh B.A., Poage N.J. and Norton D.J., 2001. Airborne thermal remote sensing for water temperature assessment in rivers and streams. Remote Sens. Environ., 76, 386–398. [CrossRef] [Google Scholar]
  • Webb B.W. and Zhang Y., 1999. Water temperatures and heat budgets in Dorset chalk water courses. Hydrol. Process., 13, 309–321. [CrossRef] [Google Scholar]
  • Webb B.W., Hannah D.M., Moore R.D., Brown L.E. and Nobilis F., 2008. Recent advances in stream and river temperature research. Hydrol. Process., 22, 902–918. [CrossRef] [Google Scholar]
  • Wilkie M.P., Brobel M.A., Davidson K., Forsyth L. and Tufts B.L., 1997. Influences of temperature upon the postexercise physiology of Atlantic salmon (Salmo salar). Can. J. Fish. Aquatic Sci., 54, 503–511. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.