A multifaceted analysis of the relationship between daily temperature of river water and air

Graf, Renata

doi:10.1007/s11600-019-00285-3

Artykuł - szczegóły

Tytuł artykułu

A multifaceted analysis of the relationship between daily temperature of river water and air

Autorzy

Graf Renata

Wybrane pełne teksty z tego czasopisma

https://www.springer.com/journal/11600

Identyfikatory

DOI

10.1007/s11600-019-00285-3

Warianty tytułu

Języki publikacji

Abstrakty

The aim of the study was to establish the strength and direction of the relationship between daily temperature of river water and air with the use of selected estimation methods. The relationship was assessed for the River Noteć and its tributaries (Western Poland), using the cross-correlation function and Granger causality. The study established cause-and-effect relations for “water–air” and “air–water” directions of influence. It was confirmed that forecasting the pattern of flowing water temperature from changes in air temperature yields better results when done based on data from the previous day. Results of modelling the relationship between data series with the use of the linear and natural cubic splines models confirmed the presence of a nonlinear relation. It was also established that there is a statistically significant correlation of random fluctuations for both temperature series on the same days. This made it possible to confirm the occurrence of short-term connections between water and air temperature. The results can be used to determine the qualities of thermal regimes and to predict temperature of river waters in the conditions of climate change.

Słowa kluczowe

cross-correlation linear model water temperature air Granger causality natural cubic splines model

korelacja krzyżowa model liniowy temperatura wody powietrze przyczynowość w sensie Grangera

Wydawca

Instytut Geofizyki PAN
Springer

Czasopismo

Acta Geophysica

Rocznik

2019

Tom

Vol. 67, no. 3

Strony

905--920

Opis fizyczny

Bibliogr. 64 poz.

Twórcy

autor

Graf Renata

rengraf@amu.edu.pl

Department of Hydrology and Water Management, Institute of Physical Geography and Environmental Planning, Adam Mickiewicz University in Poznan, Bogumiła Krygowskiego 10 str, 61‑680 Poznan, Poland

Bibliografia

1. Allan JD, Castillo MM (2007) Stream ecology: structure and function of running waters, 2nd edn. Chapman and Hall, New York
2. Arismendi I, Safeeq M, Dunham JB, Johnson SL (2014) Can air temperature be used to project influences of climate change on stream temperature? Environ Res Lett 9:084015
3. Arscott DB, Tockner K, Ward JV (2001) Thermal heterogeneity along a braided floodplain river (Tagliamento River, northeastern Italy). Can J Fish Aquat Sci 58:2359–2373
4. Benyahya L, Caissie D, St-Hilaire A, Ouarda TBM, Bobée B (2007) A review of statistical water temperature models. Can Water Resources J 32:179–192
5. Bogan T, Mohseni O, Stefan HG (2003) Stream temperature—equilibrium temperature relationship. Water Resources Res 39:1245–1256
6. Bolker BM, Brooks ME, Clark CJ, Geange SW, Poulsen JR, Stevens MHH, White J-SS (2009) Generalized linear mixed models: a practical guide for ecology and evolution. Trends Ecol Evol 24:127–135
7. Caissie D (2006) The thermal regime of rivers: a review. Freshw Biol 51:1389–1406
8. Caissie D, El-Jabi N, St-Hilaire A (1998) Stochastic modeling of water temperatures in a small stream using air to water relations. Can J Civ Eng 25(2):250–260
9. Caissie D, El-Jabi N, Satish MG (2001) Modelling of maximum daily water temperatures in a small stream using air temperatures. J Hydrol 251:14–28
10. Caissie D, St-Hilaire A, El-Jabi N (2004) Prediction of water temperatures using regression and stochastic models. In: 57th Canadian water resources association annual congress, Montreal, QC, June 16–18, 2004, Ottawa, Ontario
11. Caissie D, Satish MG, El-Jabi N (2005) Predicting river water temperatures using the equilibrium temperature concept with application on the Miramichi River catchments (New Brunswick, Canada). Hydrol Process 19:2137–2159CrossRefGoogle Scholar
12. Cameron AC, Trivedi PK (2005) Microeconometrics methods and applications. Cambridge University Press, Cambridge
13. Conlan K, Lane S, Ormerod S, Wade T (2005) Preparing for climate change impacts on freshwater ecosystems (PRINCE). Environment Agency, Science Report: SC030300/SR. http://llynbrianne-lter.org/wp-content/uploads/2013/01. Accessed 10 Feb 2018
14. Detto M, Molini A, Katul G, Stoy P, Palmroth S, Baldocchi D (2012) Causality and persistence in ecological systems: a nonparametric spectral Granger causality approach. Am Nat 179:524–535
15. DeWeber JT, Wagner TA (2014) Regional neural network ensemble for predicting mean daily river water temperature. J Hydrol 517:187–200
16. Dickey DA, Fuller WA (1981) Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica 49:1057–1072
17. ETC/ICM (2015) European freshwater ecosystem assessment: cross-walk between the water framework directive and habitats directive types, status and pressures. ETC/ICM technical report 2/2015. European Topic Centre on inland, coastal and marine waters, Magdeburg. http://ecologic.eu/12451. Accessed 10 Feb 2018
18. Gallice A, Schaefli B, Lehning M, Parlange MP, Huwald H (2015) Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physically-based analytical model. Hydrol Earth Syst Sci 19:3727–3753
19. Gardner B, Sullivan PJ, Lembo AJ (2003) Predicting stream temperatures: geostatistical model comparison using alternative distance metrics. Can J Fish Aquat Sci 60:344–351
20. Gelman A, Hill J (2006) Data analysis using regression and multilevel/hierarchical models. Cambridge University Press, Cambridge
21. Graf R (2015) Variations of the thermal conditions of the Warta in the profile connecting the Urstromal and gorge sections of the valley (Nowa Wieś Podgórna-Śrem–Poznań) Zmiany termiki wód Warty w profilu łączącym pradolinny i przełomowy odcinek doliny (Nowa Wieś Podgórna-Śrem-Poznań). In: Absalon D, Matysik M, Ruman M (eds) Novel methods and solutions in hydrology and water management. Hydrological Committee PTG, PTG Department, Katowice, pp 177–194
22. Graf R (2018) Distribution properties of a measurement series of river water temperature at different time resolution levels (based on the example of the Lowland River Noteć, Poland). Water 10:203. https://doi.org/10.3390/w10020203
23. Graf R, Tomczyk AM (2018) The impact of cumulative negative air temperature degree-days on the appearance of ice cover on a river in relation to atmospheric circulation. Atmosphere 9(6):204
24. Graf R, Łukaszewicz JT, Jawgiel K (2018) The analysis of the structure and duration of ice phenomena on the Warta river in relation to thermic conditions in the years 1991–2010 (Analiza struktury i czasu trwania zjawisk lodowych na Warcie na tle warunków termicznych w okresie 1991–2010). Woda-Środowisko Obsz Wiej 18:5–28
25. Granger CWJ (1988) Some recent developments in a concept of causality. J Econom 39(1–2):199–211
26. 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 Manag 28(5):1379–1394
27. Hannah DM, Malcolm IA, Soulsby C, Youngson AF (2004) Heat exchanges and temperatures within a salmon spawning stream in the Cairngorms, Scotland: seasonal and sub-seasonal dynamics. River Res Appl 20:635–652
28. Hilderbrand RH, Kashiwagi MT, Prochaska AP (2014) Regional and local scale modeling of stream temperatures and spatio-temporal variation in thermal sensitivities. Environ Manag 54:14–22
29. Hox J (2002) Multilevel analysis: techniques and applications. Lawrence Erlbaum Associates, Publishers, Mahwah
30. Jackson MC, Loewen CJG, Vinebrooke RD, Chimimba CT (2016) Net effects of multiple stressors in freshwater ecosystems: a meta-analysis. Glob Change Biol 22:180–189
31. Kędra M, Wiejaczka Ł (2016) Disturbance of water-air temperature synchronisation by dam reservoirs. Water Environ J 30(1–2):31–39
32. Kondracki J (2008) Regional geography of Poland (Geografia regionalna Polski). Scientific Publishing House PWN, Warsaw
33. Lagergaard Pedersen N, Sand-Jensen K (2007) Temperature in lowland Danish streams: contemporary patterns, empirical models and future scenarios. Hydrol Process 21:348–358
34. Langan SJ, Johnston L, Donaghy MJ, Youngson AF, Hay DW, Soulsby C (2001) Variation in river water temperatures in an upland stream over a 30-year period. Sci Total Environ 265:195–207
35. Łaszewski M (2014) Methods of estimating stream water temperature and air temperature relationships—the Świder River case study (Metody określania związków temperatury wody rzecznej i temperatury powietrza na przykładzie rzeki Świder). Prace Geogr 136:45–60
36. Letcher BH, Hocking DJ, O’Neil K, Whiteley AR, Nislow KH, O’Donnell MJ (2016) A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags. PeerJ 4:e1727
37. Li H, Deng X, Kim D-Y, Smith EP (2014) Modeling maximum daily temperature using a varying coefficient regression model. Water Resources Res 50:3073–3087
38. Lisi PJ, Schindler DE, Cline TJ, Scheuerell MD, Walsh PB (2015) Watershed geomorphology and snowmelt control stream thermal sensitivity to air temperature Geophys. Res Lett 42:3380–3388
39. Liu B, Yang D, Ye B, Berezovskaya S (2005) Long-term open-water season stream temperature variations and changes over Lena River Basin in Siberia. Glob Planet Change 48:96–111
40. Marszelewski W, Pius B (2018) Relation between air temperature and inland surface water temperature during climate change (1961–2014): case study of the Polish Lowland. In: Zelenakova M (ed) Water management and the environment: case studies. Springer, Berlin, pp 175–195
41. Mohseni O, Stefan HG (1999) Stream temperature/air temperature relationship: a physical interpretation. J Hydrol 218:128–141
42. Mohseni O, Stefan HG, Erickson TR (1998) A nonlinear regression model for weekly stream temperatures. Water Resources Res 34:2685–2692
43. Morrill JC, Bales RC, Conklin MH (2005) Estimating stream temperature from air temperature: implications for future water quality. J Environ Eng 131:139–146
44. Napiórkowski MJ, Piotrowski AP, Napiórkowski JJ (2014) Stream temperature forecasting by means of ensemble of neural networks: importance of input variables and ensemble size. In: Schleiss AJ et al (eds) River flow. Taylor & Francis Group, London
45. Neumann DW, Rajagopalan B, Zagona EA (2003) Regression model for daily maximum stream temperature. J Environ Eng 7:667–674
46. Olden JD, Naiman RJ (2010) Incorporating thermal regimes into environmental flows assessments: modifying dam operations to restore freshwater ecosystem integrity. Freshw Biol 55:86–107
47. Padilla A, Rasouli K, Déry SJ (2015) Impacts of variability and trends in runoff and water temperature on salmon migration in the Fraser River Basin, Canada. Hydrol Sci J. https://doi.org/10.1080/02626667.2014.892602
48. Pilgrim JM, Fang X, Stefan HG (1998) Stream temperature correlations with air temperature in Minnesota : implications for climate warming. J Am Water Resources Assoc 34:1109–1121
49. Piotrowski AP, Napiórkowski JJ (2018) Performance of the air2stream model that relates air and stream water temperatures depends on the calibration method. J Hydrol 561:395–412
50. Poole C, Berman CH (2001) An ecological perspective on in-stream temperature: natural heat dynamics and mechanisms of human-caused thermal degradation. Environ Manag 27(6):787–802
51. R Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org. Accessed 10 Feb 2018
52. Rushworth AM, Peterson EE, Ver Hoef JM, Bowman AW (2015) Validation and comparison of geostatistical and spline models for spatial stream networks. Environmetrics 26:327–338
53. Sahoo GB, Schladow SG, Reuter JE (2009) Forecasting stream water temperature using regression analysis, artificial neural network, and chaotic non-linear dynamic models. J Hydrol 378:325–342
54. Sinokrot BA, Stefan HG (1994) Stream water temperature sensitivity to weather and bed parameters. ASCE J Hydraul Eng 120:722–736
55. Sinokrot BA, Stefan HG, McCormick JH, Eaton JG (1995) Modeling of climate change effects on stream temperatures and fish habitats below dams and near groundwater inputs. Clim Change 30:181–200
56. Toffolon M, Piccolroaz S (2015) A hybrid model for river water temperature as a function of air temperature and discharge. Environ Res Lett 10:114011. https://doi.org/10.1088/1748-9326/10/11/114011
57. Webb BW, Nobilis F (2007) Long-term changes in river temperature and the influence of climatic and hydrological factors. Hydrol Sci 52:74–85
58. Webb BW, Clack PD, Walling DE (2003) Water–air temperature relationships in a Devon river system and the role of flow. Hydrol Process 17:3069–3084. https://doi.org/10.1002/hyp.1280
59. Wiejaczka Ł (2007) Relationship between water temperature in the river and air temperature -on the Ropa River as an example. (Relacje pomiędzy temperaturą wody w rzece a temperaturą powietrza - na przykładzie rzeki Ropy). Folia Geogr Geograph Phys 37–38:95–105
60. Wiejaczka Ł (2011) Influence of storage reservoir on the relations between the temperature of water in the river and the air temperature (Wpływ zbiornika retencyjnego na relacje między temperaturą wody w rzece a temperaturą powietrza). Przegląd Naukowy Inżynieria i Kształtowanie Środowiska 53:183–195
61. Woś A (2010) The climate of Poland in the second half of the 20th century (Klimat Polski w drugiej połowie 20. Wieku). Scientific Publishing House UAM, Poznan
62. Younus M, Hondzo M, Engel BA (2000) Stream temperature dynamics in upland agricultural watersheds. J Environ Eng 126:518–526
63. Żelazny M, Rajwa-Kuligiewicz A, Bojarczuk A, Pęksa Ł (2018) Water temperature fluctuation patterns in surface waters of the Tatra Mts, Poland. J Hydrol 564:824–835. https://doi.org/10.1016/j.jhydrol.2018.07.051
64. Zhu S, Nyarko EK, Hadzima-Nyarko M (2018) Modelling daily water temperature from air temperature for the Missouri River. PeerJ 6:e4894. https://doi.org/10.7717/peerj.4894

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-0b43ee8f-fe87-4a7c-aa59-84ed8fcf1a17