Long-term trend and multi-annual variability of water temperature in the pristine Bela River basin (Slovakia)

Pekárová, Pavla; Miklánek, Pavol; Halmová, Dana; Onderka, Milan; Pekár, Ján; Kučárová, Katarína; Liová, Soňa; Škoda, Peter

doi:10.1016/j.jhydrol.2011.01.048

Cited by 24 publications

(23 citation statements)

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“…2) reported for rivers in the U.S.A. (0.009-0.077°C yr À1 , Kaushal et al, 2010;Isaak et al, 2012;Null et al, 2013a,b;Rice and Jastram, 2015), Europe (0.006-0.18°C yr À1 , Moatar and Gailhard, 2006;Albek and Albek, 2009;Pekárová et al, 2011;Žganec, 2012;Jurgelė naitė et al, 2012;Markovic et al, 2013;Lepori et al, 2014;Orr et al, 2015), and Australia (0.014-0.017°C yr À1 , Webb and Nobilis, 2007). Although no relevant reports are currently available for rivers in China, the rapid economic development and urbanization in China, especially in eastern China over the past several decades, are expected to enhance rising river water temperature rates in conjunction with the interactive effects of climate change for many rivers.…”

Section: Discussionmentioning

confidence: 93%

“…Higher water temperature can impair the habitat of a wide range of aquatic organisms from invertebrates to salmonids (Langan et al, 2001;Caissie, 2006;Isaak et al, 2012;Markovic et al, 2013;Null et al, 2013a,b), as well as degrade water quality such as decreased oxygen-holding capacity, increased oxygen consumption, and enhanced formation of potentially toxic NH 3 (Webb and Nobilis, 2007;Pekárová et al, 2011;El-Jabi et al, 2014). Furthermore, increasing riverine heat flux has a great potential to aggravate eutrophication (including harmful algal blooms) and hypoxia in downstream lakes, estuaries and coastal waters (Liu et al, 2005;Ozaki et al, 2008;Ye et al, 2011;Rice and Jastram, 2015), as well as to impair their biological communities (Seekell and Pace, 2011).…”

Section: Introductionmentioning

confidence: 99%

“…Depending on the river type and time scale, the air-water temperature dynamics can be effectively http://dx.doi.org/10.1016/j.jhydrol.2015.12.005 0022-1694/Ó 2015 Elsevier B.V. All rights reserved. expressed by a linear or logistic function (Mohseni and Stefan, 1999;Webb et al, 2003;Pekárová et al, 2011;van Vliet et al, 2012;Gu et al, 2014). For example, the slopes of the regression lines between water and air temperature generally increase with increasing time scales (daily, weekly, monthly and annually), while the slope decreases from small upstream to large downstream river reaches (Webb et al, 2003;Caissie, 2006).…”

Section: Introductionmentioning

confidence: 99%

“…Regarding land-use change, many studies suggest that decreasing forest area (or decreasing vegetation shading (Moore et al, 2005;Ozaki et al, 2008;Pekárová et al, 2011;Simmons et al, 2014) and increasing urban area (or increasing human density and increasing thermal effluent) within a catchment can significantly increase river water temperature in addition to climate warming (Langan et al, 2001;Caissie, 2006;Albek and Albek, 2009;Xin and Kinouchi, 2013;Gu et al, 2014;Lepori et al, 2014;Orr et al, 2015). For example, the observed water temperature increases of 0.11-0.21°C yr À1 in winter and spring for some stream segments in central Tokyo and its suburbs between 1978 and 1998 were ascribed to increases in anthropogenic heat input from urban wastewater (Kinouchi, 2007).…”

Section: Introductionmentioning

confidence: 99%

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Changes in river water temperature between 1980 and 2012 in Yongan watershed, eastern China: Magnitude, drivers and models

Chen

Guo

et al. 2016

Journal of Hydrology

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s u m m a r yClimate warming is expected to have major impacts on river water quality, water column/hyporheic zone biogeochemistry and aquatic ecosystems. A quantitative understanding of spatio-temporal air (T a ) and water (T w ) temperature dynamics is required to guide river management and to facilitate adaptations to climate change. This study determined the magnitude, drivers and models for increasing T w in three river segments of the Yongan watershed in eastern China. Over the 1980-2012 period, T w in the watershed increased by 0.029-0.046°C yr À1 due to a $0.050°C yr À1 increase of T a and changes in local human activities (e.g., increasing developed land and population density and decreasing forest area). A standardized multiple regression model was developed for predicting annual T w (R 2 = 0.88-0.91) and identifying/ partitioning the impact of the principal drivers on increasing T w :T a (76 ± 1%), local human activities (14 ± 2%), and water discharge (10 ± 1%). After normalizing water discharge, climate warming and local human activities were estimated to contribute 81-95% and 5-19% of the observed rising T w , respectively. Models forecast a 0.32-1.76°C increase in T w by 2050 compared with the 2000-2012 baseline condition based on four future scenarios. Heterogeneity of warming rates existed across seasons and river segments, with the lower flow river and dry season demonstrating a more pronounced response to climate warming and human activities. Rising T w due to changes in climate, local human activities and hydrology has a considerable potential to aggravate river water quality degradation and coastal water eutrophication in summer. Thus it should be carefully considered in developing watershed management strategies in response to climate change.

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Section: Discussionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Changes in river water temperature between 1980 and 2012 in Yongan watershed, eastern China: Magnitude, drivers and models

Chen

Guo

et al. 2016

Journal of Hydrology

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“…It has been shown that Ta is a very strong predictor of Tw in streams and rivers (Webb and Nobilis, ). It has been reported that mean monthly Tw lags behind monthly Ta (Webb, ; Mohseni and Stefan, ; Pekarova et al, , ). The strong relationship between mean monthly and annual ( R 2 ~ 0.95 and R 2 ~ 0.5 respectively) Ta and Tw at investigated sites correspond to previous findings.…”

Section: Discussionmentioning

confidence: 98%

Trends and multi‐annual variability of water temperatures in the river Danube, Serbia

Basarin

Lukić

Pavić

et al. 2016

Hydrological Processes

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This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1002/hyp.10863 This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved. TRENDS AND MULTI-ANNUAL VARIABILITY OF WATER TEMPERATURES IN ABSTRACTThe relationship between air (Ta) and water temperature (Tw) is very important because it shows how the temperature of a water body might respond to future changes in surface Ta.Mean monthly Tw records of three gauging stations (Bezdan, Bogojevo i Veliko Gradište) were analyzed alongside mean monthly discharge (Q) for the same stations.Additionally, Ta series from two meteorological stations (Sombor and Veliko Gradište) were correlated with Tw variations over the period . Locally weighted scatter point smoothing (LOWESS) was used to investigate long-term trends in the raw data, alogside the Mann-Kendall (MK) trend test. Trend significance was established using Yue-Pilon's prewhitening approaches to determine trends in climate data. Also, the rescaled adjusted partial sums (RAPS) method was used to detect dates of possible changes in the time series.Statistically significant warming trends were observed for annual and seasonal minimum and maximum Tw at all investigated sites. The strongest warming was observed at Bogojevo gauging station for seasonal maximum Tw, with +0.05°C per year on average. RAPS established that the trend began in the 1980s. This behaviour is linked to climate patterns in the North and East Atlantic which determine the amount of heat advected onto mainland Europe. Statistically significant correlations were found for all Tw on an annual basis.Overall, the strongest correlations (p<0.01) between Tw residuals and the North Atlantic Oscillation (NAO) were recorded for the winter period. These findings suggest possible predictability of Tw over seasonal time-scales.Keywords: Danube; water temperature; air temperature; trends; variability; Serbia.This article is protected by copyright. All rights reserved. INTRODUCTIONTemperature is an important feature of flowing waters because it affects other physical properties and influences the chemical and biochemical reactions of lotic systems (Walling and Webb, 1992;Webb et al., 2008). The life-cycles of lotic biota are regulated by river temperature variations (Gore, 1992; Everall et al., 2015). Water temperature (Tw) also indirectly influences bulk density which causes thermal stratification in standing water bodies. In this way, temperature influences chemical and biochemical processes in the individual stratified layers (epilimnion and hypolimnion) (Pekarova et al., 2011). Changes in the thermal regime of river systems may result in the disruption of established patterns of synchrony between the aquatic communities (Woodward et al., 2010;Marković et al., 2013).Incomin...

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Characterization of sub‐daily thermal regime in alpine rivers: quantification of alterations induced by hydropeaking

Vanzo

Siviglia

Carolli

et al. 2015

Hydrological Processes

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Abstract:The thermal regime of rivers is threatened by anthropogenic stresses at a large variety of timescales. We focus on sub-daily thermal alterations induced by the release of hypolimnetic water for hydropower production (thermopeaking). We analyse the thermal signal focusing on the following characteristics that are potentially affected by hypolimnetic releases: (i) sub-daily thermal rate of change and (ii) oscillation frequencies contained in the thermal signal. Through a proper scaling, we derive two dimensionless at-a-station indicators to compare alterations among stations with different locations and physiographic characteristics of the basins. Then we analyse the data from two different thermal datasets (Italy/Switzerland) for a total of 48 stations with 10 min time resolution of temperature data. The stations are grouped according to the absence of upstream hydropeaking releases (29 stations, reference group) and the existence of upstream hydropeaking, hence potentially impacted by thermopeaking (19 stations, altered group). Using a simple statistical approach, based on a non-parametric definition of outliers, we identify the range of variability of the two indicators for the reference, unaltered group. This range measures the 'natural' sub-daily thermal variability of the proposed indicators. Finally, we investigate the seasonality effects on the two proposed indicators and it results, that sub-daily alterations mostly occur during summer. The two indicators represent a novel tool for the assessment of river thermal regime alterations and can be easily included in existing methodologies to assess river quality.

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Long-term trend and multi-annual variability of water temperature in the pristine Bela River basin (Slovakia)

Cited by 24 publications

References 14 publications

Changes in river water temperature between 1980 and 2012 in Yongan watershed, eastern China: Magnitude, drivers and models

Changes in river water temperature between 1980 and 2012 in Yongan watershed, eastern China: Magnitude, drivers and models

Trends and multi‐annual variability of water temperatures in the river Danube, Serbia

Characterization of sub‐daily thermal regime in alpine rivers: quantification of alterations induced by hydropeaking

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