Browse > Article
http://dx.doi.org/10.17663/JWR.2016.18.3.313

Water temperature assessment on the small ecological stream under climate change  

Park, Jung Sool (Nakdong Flood Control Office, Ministry of Land, Infrastructure and Transport)
Kim, Sam Eun (Data Quality Management Departmant, Hydrological Survey Center)
Kwak, Jaewon (Nakdong Flood Control Office, Ministry of Land, Infrastructure and Transport)
Kim, Jungwook (Department of Civil Engineering, Inha University)
Kim, Hung Soo (Department of Civil Engineering, Inha University)
Publication Information
Journal of Wetlands Research / v.18, no.3, 2016 , pp. 313-323 More about this Journal
Abstract
Water temperature affects physical and biological processes in ecologies on river system and is important conditions for growth rate and spawning of fish species. The objective of this study is to compare models for water temperature during the summer season for the Fourchue River (St-Alexandre-de-Kamouraska, Quebec, Canada). For this, three different models, which are CEQUEAU, Auto-regressive Moving Average with eXogenous input and Nonlinear Autoregressive with eXogenous input, were applied and compared. Also, future water temperature in the Fourchue river were simulated and analyzed its result based on the CMIP5 climate models, RCP 2.6, 4.5, 8.5 climate change scenarios. As the result of the study, the water temperature in the Fourchue river are actually changed and median water temperature will increase $0.2{\sim}0.7^{\circ}C$ in June and could decrease by $0.2{\sim}1.1^{\circ}C$ in September. Also, the UILT ($24.9^{\circ}C$) for brook trout are also likely to occurred for several days.
Keywords
Water Temperature; Climate change; Temperature Modeling; UILT;
Citations & Related Records
Times Cited By KSCI : 11  (Citation Analysis)
연도 인용수 순위
1 Ahmadi-Nedushan, B, St-Hilaire, A, Ouarda, TB, 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). Hydrological Processes, 21(1), pp. 21-34.   DOI
2 Ahn, JB, Ryu, JH, Cho, EH, Park, JY, and Ryoo, SB(1997). A Study on Correlations between Air-Temperature and Precipitation in Korea and SST over the Tropical Pacific. Asia-Pacific J. of Atmospheric Sciences, 33(3), 487-495.
3 Ahn, JH and Han, DH(2010). Projected Climate Change Impact on Surface Water Temperature in Korea. J. of Korean Society on Water Quality, 26(1), pp. 133-139.
4 Bask, M and Gençay, R(1998). Testing chaotic dynamics via Lyapunov exponents. Physica D: Nonlinear Phenomena, 114(1), pp. 1-2.   DOI
5 Battiti, R(1994). Using mutual information for selecting features in supervised neural net learning. IEEE Transactions on Neural Networks, 5(4), pp. 537-550.   DOI
6 Barrow, E, Maxwell, B, and Gachon, P(2004). Climate Variability and Change in Canada. Past, Present and Future. Meteorological Service of Canada, Environment Canada: Toronto.
7 Benyahya, L, St-Hilaire, A, Ouarda, TB, Bobee, B, and Dumas, J(2008). Comparison of non-parametric and parametric water temperature models on the Nivelle River, France. Hydrological Sciences Journal, 53(3), pp. 640-655.   DOI
8 Bouck, GR, Chapman, GA, Schneider, PW, and Stevens, DG(1975). Effects of Holding Temperatures on Reproductive Development in Adult Sockeye Salmon (Oncorhynchus Nerka). In 26 th Annual Northwest Fish Culture Conference.
9 Breaker, LC and Brewster, JK(2009). Predicting offshore temperatures in Monterey Bay based on coastal observations using linear forecast models. Ocean Modelling, 27(1), pp. 82-97.   DOI
10 Brock, WA, Dechert, WD, and Scheinkman, JA(1987). A Test for Independence Based on the Correlation Dimension. Department of Economics, University of Wisconsin at Madison, University of Houston, and University of Chicago. Social Science Research Working Paper, 8762.
11 Caissie, D(2006). The thermal regime of rivers: a review. Freshwater Biology, 51(8), pp. 1389-1406.   DOI
12 Caissie, D, Satish, MG, and El-Jabi, N(2007). Predicting water temperatures using a deterministic model: application on Miramichi River catchments (New Brunswick, Canada). J. of Hydrology, 336(3), pp. 303-315.   DOI
13 Caldwell, RJ, Gangopadhyay, S, Bountry, J, Lai, Y, and Elsner, MM(2013). Statistical modeling of daily and subdaily stream temperatures: Application to the Methow River Basin, Washington. Water Resources Research, 49(7), pp. 4346-4361.   DOI
14 Danner, EM, Melton, FS, Pike, A, Hashimoto, H, Michaelis, A, Rajagopalan, B, and Nemani, RR(2012). River temperature forecasting: A coupled-modeling framework for management of river habitat. Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal, 5(6), pp. 1752-1760.
15 Grbic, R, Kurtagic, D, and Sliskovic, D(2013). Stream water temperature prediction based on Gaussian process regression. Expert Systems with Applications, 40(18), pp. 7407-7414.   DOI
16 Diaconescu, E(2008). The use of NARX neural networks to predict chaotic time series. WSEAS Transactions on Computer Research, 3(3), pp. 182-191.
17 Diversi, R, Guidorzi, R, and Soverini, U(2011). Identification of ARMAX models with noisy input and output. In World Congress, 18(1), pp. 13121-13126.
18 Fry, FEJ(1947). Effects of the environment on animal activity. Univ. Toronto Studies, Biol. Ser. 55, Ontario Fish. Res. Lab. Publ. 68, pp. 1-62.
19 Hadzima-Nyarko, M, Rabi, A, and sperac, M(2014). Implementation of Artificial Neural Networks in Modeling the Water-Air Temperature Relationship of the River Drava. Water Resources Management, 28(5), pp. 1379-1394.   DOI
20 Hasnain SS, Mins CK, Shuter BJ(2010). Key Ecological Temperature Metrics for Canadian Freshwater Fishes, Applied Research and Development Branch. Ontario Ministry of Natural Resources.
21 Haykin, S(1999). Neural networks: a comprehensive foundation (second ed.). Prentice hall.
22 Hyndman, RJ and Khandakar, Y(2007). Automatic time series for forecasting: the forecast package for R (No. 6/07). Monash University, Department of Econometrics and Business Statistics.
23 IPCC(2013). Region by Region: The Science of AR5 WG1 and the Consequences, IPCC.
24 Jeong, DI, Daigle, A, and St-Hilaire, A(2013). Development of a stochastic water temperature model and projection of future water temperature and extreme events in the Ouelle River basin in Quebec. Canada. River Research and Applications, 29(7), pp. 805-821.   DOI
25 Jung, HD, Hwang, JD, Jung, KG, Heo, S, Sung, KT, Ko, WJ, Yang, JY, and Kim, SW(2003). Long Term Trend of Change In Water Temperature and Salinity in Coastal Waters around Korean Peninsula. J. of the Korean society of marine environment & safety, 9(2), pp. 59-64.
26 Johnson FA(1971). Stream temperatures in an alpine area. J. of Hydrology, 14(3), pp. 322-336.   DOI
27 Jourdonnais JH, Walsh RP, Pickett F, and Goodman D(1992). Structure and calibration strategy for a water temperature model of the lower Madison River, Montana. Rivers, 3(3), pp. 153-169.
28 Ju, SJ and Kim, SJ(2013). Assessment of the Impact of Climate Change on Marine Ecosystem in the South Sea of Korea II. Ocean and Polar Research, 35(2), pp. 123-125.   DOI
29 Kothandaraman, V(1972). Air-water temperature relationshop in illinois. J. of the American Water Resources Association, 8(1), pp. 38-45.   DOI
30 Kim, BT, Eom, KH, Lee, JS, Park, HJ, and Yook, KH(2015). A Study on the Relationship Between the Catch of Coastal Fisheries and Climate Change Elements using Spatial Panel Model, J. Fish. Bus. Adm., 46(3), pp. 63-72.   DOI
31 Kim, SJ, Noh, HS, Hong, SJ, Kwak, JW, and Kim, HS(2013). Impact of Climate Change on Habitat of the Rhynchocypris Kumgangensis in Pyungchang River. J. of Wetlands Research, 15(2), pp. 271-280.   DOI
32 Larnier, K, Roux, H, Dartus, D, and Croze, O(2010). Water temperature modeling in the Garonne River (France). Knowledge and Management of Aquatic Ecosystems, 398(1), pp. 4.
33 Lee, KH(2016). Prediction of Climate-induced Water Temperature using Nonlinear Air-water Temperature Relationship for Aquatic Environments. J. of Environmental Science International, 25(6), pp. 877-888.   DOI
34 Matthews, K(2014). California Golden Trout: Can Their Warming Streams Handle Other Stressors?. In 144th Annual Meeting of the American Fisheries Society. Afs.
35 Levene, H(1960). Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling. Stanford University Press. pp. 278-292.
36 Ljung GM and Box GE(1978). On a Measure of a Lack of Fit in Time Series Models. Biometrika, 65(2), pp. 297-303.   DOI
37 Lynch, P(2006). "The ENIAC Integrations". The Emergence of Numerical Weather Prediction. Cambridge University Press. pp. 206-208.
38 Maier, HR and Dandy, GC(2000). Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications. Environmental Modelling & Software, 15(1), pp. 101-124.   DOI
39 Maurer, EP, Hidalgo, HG, Das, T, Dettinger, MD, and Cayan, DR(2010). The utility of daily large-scale climate data in the assessment of climate change impacts on daily streamflow in California. Hydrology and Earth System Sciences, 14(6), pp. 1125-1138.   DOI
40 Meinshausen, M, Smith, SJ, Calvin, K, Daniel, JS, Kainuma, ML, Lamarque, JF, Matsumoto, K, Montzka, SM, Raper, SC, Riahi, K, Thomson, A, Velders, GJ, and Van vuuren, DP(2011). The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Climatic change, 109(1-2), pp. 213-241.   DOI
41 Mohseni, O and Stefan, HG(1999). Stream temperature/air temperature relationship: a physical interpretation. J. of Hydrology, 218(3), pp. 128-141.   DOI
42 Morin G, Fortin JP, Lardeau JP, Sochanska W, and Paquette S(1981). Mode'le CEQUEAU: manuel d'utilisation. INRS-Eau, Ste-Foy, Que'bec, Canada.
43 Nash, JE and Sutcliffe, JV(1970). River flow forecasting through conceptual models part I-A discussion of principles. J. of Hydrology, 10 (3), pp. 282-290.   DOI
44 Morin G, Sochanski W, Paquet P(1998). Le mode'le de simulation de quantite' CEQUEAU-ONU, Manuel dere'fe'rences. Organisation des Nations-Unies et INRS-Eau. Rapport de recherche no. 519, 252.
45 Moriasi, DN, Arnold, JG, Van Liew, MW, Bingner, RL, Harmel, RD, Veith, TL(2007). Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations. Transactions of the ASABE, 50 (3), pp. 885-900.   DOI
46 Myers, JL and Well, AD(2003). Research Design and Statistical Analysis (2nd ed.). Lawrence Erlbaum. 508. ISBN 0-8058-4037-0.
47 Nunn, AD, Cowx, IG, Frear, PA, and Harvey, JP(2003). Is water temperature an adequate predictor of recruitment success in cyprinid fish populations in lowland rivers?, Freshwater Biology, 48(4), pp. 579-588.   DOI
48 Park, YG, Choi, SH, Kim, SD, and Kim, CH(2012). Assessment of Changes in Temperature and Primary Production over the East China Sea and South Sea during the 21st Century using an Earth System Model. Ocean and Polar Research, 34(2), pp. 229-237.   DOI
49 Parra, I, Almodovar, A, Ayllon, D, Nicola, GG, and Elvira, B(2012). Unravelling the effects of water temperature and density dependence on the spatial variation of brown trout (Salmo trutta) body size. Canadian J. of Fisheries and Aquatic Sciences, 69(5), pp. 821-832.   DOI
50 Seiller, G and Anctil, F(2014). Climate change impacts on the hydrologic regime of a Canadian river: comparing uncertainties arising from climate natural variability and lumped hydrological model structures. Hydrology and Earth System Sciences, 18(6), pp. 2033-2047.   DOI
51 Stefan, HG and Preud'Homme, EB(1993). Stream temperature estimation from air temperature. J. of the American Water Resources Association, 29(1), pp. 27-45.   DOI
52 Seong, KT, Hwang, JD, Han, IS, Go, WJ, Suh, YS, and Lee, JY(2010). Characteristic for Long-term Trends of Temperature in the Korean Waters. 16(4), pp. 353-360.
53 Sillmann, J, Kharin, VV, Zhang, X, Zwiers, FW, and Bronaugh, D(2013). Climate extremes indices in the CMIP5 multimodel ensemble: Part 1. Model evaluation in the present climate. J. of Geophysical Research: Atmospheres, 118(4), pp. 1716-1733.   DOI
54 Smith, N(2014). Evaluation of Growth, Survival, and Recruitment of Chinook Salmon in Southeast Alaska Rivers. In 144th Annual Meeting of the American Fisheries Society. Afs.
55 Webb, BW, Hannah, DM, Moore, RD, Brown, LE, and Nobilis, F(2008). Recent advances in stream and river temperature research. Hydrological Processes, 22(7), pp. 902-918.   DOI
56 Wenger, SJ, Isaak, DJ, Luce, CH, Neville, HM, Fausch, KD, Dunham, JB, and Williams, JE(2011). Flow regime, temperature, and biotic interactions drive differential declines of trout species under climate change. Proceedings of the National Academy of Sciences, 108(34), pp. 14175-14180.   DOI
57 Wismer, DA and Christie, AE(1987). Temperature relationships of Great Lakes fishes. Great Lakes Fishery Commission Special Publication, Great Lakes Fishery Commission, MI, USA.
58 Yi, HS, Kim, DS, Hwang, MH, and An, KG(2016). Assessment of Runoff and Water temperature variations under RCP Climate Change Scenario in Yongdam dam watershed, South Korea. J. of Korean Society on Water Environment, 32(2), pp. 173-182.   DOI
59 Yoon, SW, Park, GY, Chung, SW, and Kang, BS(2014). Projection of the Climate Change Effects on the Vertical Thermal Structure of Juam Reservoir. J. of Korean Society on Water Environment, 30(5), pp. 491-502.   DOI
60 Yoon, DY and Choi, HW(2011). A Comparison of Spatio-Temporal Variation Pattern of Sea Surface Temperature According to the Regional Scale in the South Sea of Korea. J. of the Korean Association of Geographic Information Studies, 14(4), pp. 182-193.   DOI