scholarly journals A hybrid model for river water temperature as a function of air temperature and discharge

2015 ◽  
Vol 10 (11) ◽  
pp. 114011 ◽  
Author(s):  
Marco Toffolon ◽  
Sebastiano Piccolroaz
Keyword(s):  
Water Temperature ◽  
River Water ◽  
Hybrid Model ◽  
Air Temperature ◽  
River Water Temperature

scholarly journals Changes in the Water Temperature of Rivers Impacted by the Urban Heat Island: Case Study of Suceava City

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1343 ◽  
Author(s):  
Andrei-Emil Briciu ◽  
Dumitru Mihăilă ◽  
Adrian Graur ◽  
Dinu Iulian Oprea ◽  
Alin Prisăcariu ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Water Temperature ◽  
Urban Heat Island ◽  
River Water ◽  
Air Temperature ◽  
Stream Water ◽  
Heat Island ◽  
Urban Heat ◽  
The City ◽  
River Water Temperature

Cities alter the thermal regime of urban rivers in very variable ways which are not yet deciphered for the territory of Romania. The urban heat island of Suceava city was measured in 2019 and its impact on Suceava River was assessed using hourly and daily values from a network of 12 water and air monitoring stations. In 2019, Suceava River water temperature was 11.54 °C upstream of Suceava city (Mihoveni) and 11.97 °C downstream (Tişăuţi)—a 3.7% increase in the water temperature downstream. After the stream water passes through the city, the diurnal thermal profile of Suceava River water temperature shows steeper slopes and earlier moments of the maximum and minimum temperatures than upstream because of the urban heat island. In an average day, an increase of water temperature with a maximum of 0.99 °C occurred downstream, partly explained by the 2.46 °C corresponding difference between the urban floodplain and the surrounding area. The stream water diurnal cycle has been shifted towards a variation specific to that of the local air temperature. The heat exchange between Suceava River and Suceava city is bidirectional. The stream water diurnal thermal cycle is statistically more significant downstream due to the heat transfer from the city into the river. This transfer occurs partly through urban tributaries which are 1.94 °C warmer than Suceava River upstream of Suceava city. The wavelet coherence analyses and ANCOVA (analysis of covariance) prove that there are significant (0.95 confidence level) causal relationships between the changes in Suceava River water temperature downstream and the fluctuations of the urban air temperature. The complex bidirectional heat transfer and the changes in the diurnal thermal profiles are important to be analysed in other urban systems in order to decipher in more detail the observed causal relationships.

scholarly journals Anthropogenic influence on the Rhine water temperatures

2020 ◽  
Vol 24 (10) ◽  
pp. 5027-5041
Author(s):  
Alex Zavarsky ◽  
Lars Duester
Keyword(s):  
Water Temperature ◽  
River Water ◽  
Air Temperature ◽  
Nuclear Power ◽  
Important Variable ◽  
Anthropogenic Heat ◽  
River Rhine ◽  
River Temperature ◽  
Time Lagged ◽  
River Water Temperature

Abstract. River temperature is an important parameter for water quality and an important variable for physical, chemical and biological processes. River water is also used by production facilities as cooling agent. We introduced a new way of calculating a catchment-wide air temperature using a time-lagged and weighed average. Regressing the new air temperature vs. river water temperature, the meteorological influence and the anthropogenic heat input could be studied separately. The new method was tested at four monitoring stations (Basel, Worms, Koblenz and Cologne) along the river Rhine and lowered the root mean square error of the regression from 2.37 ∘C (simple average) to 1.02 ∘C. The analysis also showed that the long-term trend (1979–2018) of river water temperature was, next to the increasing air temperature, mostly influenced by decreasing nuclear power production. Short-term changes in timescales < 5 years were connected with changes in industrial production. We found significant positive correlations for the relationship.

Effects of Air Temperature, Precipitation and Solar Radiation Having with Different Timescales on River Water Temperature.

2001 ◽  
pp. 93-103
Author(s):  
Noriatsu OZAKI ◽  
Takehiko FUKUSHIMA ◽  
Hideo HARASAWA ◽  
Toshiharu KOJIRI ◽  
Katsunori KAWASHIMA
Keyword(s):  
Solar Radiation ◽  
Water Temperature ◽  
River Water ◽  
Air Temperature ◽  
River Water Temperature

scholarly journals Development of a Multilayer Deep Neural Network Model for Predicting Hourly River Water Temperature From Meteorological Data

2021 ◽  
Vol 9 ◽  
Author(s):  
Reza Abdi ◽  
Ashley Rust ◽  
Terri S. Hogue
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Water Temperature ◽  
River Water ◽  
Air Temperature ◽  
Deep Neural Network ◽  
Single Layer ◽  
Machine Learning Algorithms ◽  
Ecosystem Functions ◽  
River Water Temperature

Water temperature is a vital attribute of physical riverine habitat and one of the focal objectives of river engineering and management. However, in most rivers, there are not enough water temperature measurements to characterize thermal regimes and evaluate its effect on ecosystem functions such as fish migration. To aid in river restoration, machine learning-based algorithms were developed to predict hourly river water temperature. We trained, validated, and tested single-layer and multilayer linear regression (LR) and deep neural network (DNN) algorithms to predict water temperature in the Los Angeles River in southern CA, United States. For the single-layer models, we considered air temperature as the predictive feature, and for the multilayer models, relative humidity, wind speed, and barometric pressure were included in addition to air temperature as the considered features. We trained the LR and DNN algorithms on Google’s TensorFlow model using Keras artificial neural network library on Python. Results showed that multilayer predictions performed better compared to single-layer models by producing mean absolute errors (MAEs), that were 20% smaller (1.05°C), on average, compared to the single-layer models (1.3°C). The multilayer DNN algorithm outperformed the other model where the model’s coefficient of determination was 26 and 12% higher compared to the single-layer LR (the base model) and multilayer LR model, respectively. The multilayer machine learning algorithms, under proper data preparation protocols, may be considered useful tools for predicting water temperatures in sampled and unsampled rivers for current conditions and future estimations affected by different stressors such as climate and land-use change. River temperature predictions from the developed models provide valuable information for evaluating sustainability of river ecosystems and biota.

scholarly journals Detecting Patterns of Changes in River Water Temperature in Poland

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1327 ◽  
Author(s):  
Renata Graf ◽  
Dariusz Wrzesiński
Keyword(s):  
Water Temperature ◽  
River Water ◽  
Temperature Change ◽  
Air Temperature ◽  
Thermal Regime ◽  
Thermal Characteristics ◽  
Temperature Trends ◽  
Annual Water ◽  
River Water Temperature ◽  
Annual Water Temperature

The study determined water temperature trends of rivers in Poland in the period 1971–2015, and also their spatial and temporal patterns. The analysis covered daily water temperature of 53 rivers recorded at 94 water gauge stations and air temperature at 43 meteorological stations. Average monthly, annual, seasonal and maximum annual tendencies of temperature change were calculated using the Mann–Kendall (M–K) test. Regional patterns of water temperature change were determined on the basis of Ward’s hierarchical grouping for 16 correlation coefficients of average annual water temperature in successive 30-year sub-periods of the multi-annual period of 1971–2015. Moreover, regularities in monthly temperature trends in the annual cycle were identified using 12 monthly values obtained from the M–K Z test. The majority of average annual air and water temperature series demonstrate statistically significant positive trends. In three seasons: spring, summer and autumn, upward tendencies of temperature were detected at 70%–90% of the investigated water gauges. In 82% of the analysed rivers, similarity to the tendencies of change of monthly air temperature was concluded, with the climatic factor being recognised as of decisive importance for the changes in water thermal characteristics of the majority of rivers in Poland. In the winter months, positive trends of temperature were considerably weaker and in general statistically insignificant. On a regional scale, rivers with a quasi-natural thermal regime experienced temperature increases from April to November. In the other cases, different directions of change in river water temperature (RWT) were attributed to various forms of human impact. It was also found that for the majority of rivers the average annual water temperature in the analysed 30-year sub-periods displayed upward trends, statistically significant or close to the significance threshold. Stronger trends were observed in the periods after 1980, while a different nature of water temperature change was detected only in a couple of mountainous rivers or rivers transformed by human impact. In the beginning of the analysed period (1971–2015), the average annual water temperature of these rivers displayed positive and statistically significant trends, while after 1980 the trends were negative. The detected regularities and spatial patterns of water temperature change in rivers with a quasi-natural regime revealed a strong influence of climate on the modification of their thermal regime features. Rivers characterised by a clearly different nature of temperature change, both in terms of the direction of the tendencies observed and their statistical significance, were distinguished by alterations of water thermal characteristics caused by human activity. The results obtained may be useful in optimising the management of aquatic ecosystems, for which water temperature is a significant indicator of the ongoing environmental changes.

STUDY ON CHANGING IN RIVER WATER TEMPERATURE IN KYUSYU REGION

2018 ◽  
Vol 74 (5) ◽  
pp. I_79-I_84
Author(s):  
Yoji NODA ◽  
Tomoko MINAGAWA ◽  
Hidetaka ICHIYANAGI ◽  
Akihiko KOYAMA
Keyword(s):  
Water Temperature ◽  
River Water ◽  
River Water Temperature

scholarly journals Exploring and Quantifying River Thermal Response to Heatwaves

Water ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 1098 ◽  
Author(s):  
Sebastiano Piccolroaz ◽  
Marco Toffolon ◽  
Christopher Robinson ◽  
Annunziato Siviglia
Keyword(s):  
Water Temperature ◽  
River Water ◽  
Thermal Response ◽  
Hydrological Regime ◽  
Management Policy ◽  
Extreme Weather Events ◽  
Thermal Dynamics ◽  
Depth Analysis ◽  
River Water Temperature

Most of the existing literature on river water temperature focuseds on river thermal sensitivity to long-term trends of climate variables, whereas how river water temperature responds to extreme weather events, such as heatwaves, still requires in-depth analysis. Research in this direction is particularly relevant in that heatwaves are expected to increase in intensity, frequency, and duration in the coming decades, with likely consequences on river thermal regimes and ecology. In this study we analyzed the long-term temperature and streamflow series of 19 Swiss rivers with different hydrological regime (regulated, low-land, and snow-fed), and characterized how concurrent changes in air temperature and streamflow concurred to affect their thermal dynamics. We focused on quantifying the thermal response to the three most significant heatwave events that occurred in Central Europe since 1950 (July–August 2003, July 2006, and July 2015). We found that the thermal response of the analyzed rivers contrasted strongly depending on the river hydrological regime, confirming the behavior observed under typical weather conditions. Low-land rivers were extremely sensitive to heatwaves. In sharp contrast, high-altitude snow-fed rivers and regulated rivers receiving cold water from higher altitude hydropower reservoirs or diversions showed a damped thermal response. The results presented in this study suggest that water resource managers should be aware of the multiple consequences of heatwave events on river water temperature and incorporate expected thermal responses in adaptive management policy. In this respect, additional efforts and dedicated studies are required to deepen our knowledge on how extreme heatwave events can affect river ecosystems.

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