scholarly journals Long-term relationship between air and water temperatures in Lake Paldang, South Korea

2020 ◽  
Vol 26 (4) ◽  
pp. 200177-0
Author(s):  
Soon Ju Yu ◽  
In Gu Ryu ◽  
Min Ji Park ◽  
Jong Kwon Im

A long-term investigation into the relationship between air and water temperatures was conducted in Lake Paldang, which is the largest water source in South Korea, by studying hysteresis. From 1973 to 2018, the annual mean air temperature increased by 0.05°C/yr (seasonal Sen’s slope). The results of a numerical model (R > 0.86) showed that the ratios of the air and water temperatures increased (0.71‒0.77) in the rising limb and decreased (0.70‒0.76) in the falling limb. However, the intercept values were 0.13–3.52 and 6.62–7.78 in the rising and falling limbs, respectively, and hence there was a 4–5°C increase in temperature. In particular, in 2015, 2016, and 2018, the intercept values in the falling limb were ≥ 7, exhibiting hysteresis, whereby high water temperatures were slow to decline. Lake Paldang showed stronger water temperature hysteresis than its influent rivers and stream. The rising and falling limbs did not show a large difference in the extent of water temperature change (slope). However, the water temperature did not decrease rapidly, and the decrease continued for longer due to hysteresis, which is a type of inertia where the elevated temperature persists if the summer air temperature is significantly increased.

Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2341
Author(s):  
Soon-Ju Yu ◽  
Ju-Yeon Son ◽  
Ho-Yeong Kang ◽  
Yong-Chul Cho ◽  
Jong-Kwon Im

Long-term changes in air and water temperatures and the resulted stratification phenomena were observed for Soyang Lake (SY), Paldang Lake (PD), Chungju Lake (CJ), and Daecheong Lake (DC) in South Korea. Non-parametric seasonal Kendall and Mann-Kendall tests, Sen slope estimator, and potential energy anomaly (PEA) were applied. The lake surface water temperatures (LSWTs) of SY and DC increased at the same rate (0.125 °C/y), followed by those of CJ (0.071 °C/y) and PD (0.06 °C/y). Seasonally, the LSWT increase rates for all lakes, except PD, were 2–3 times higher than the air temperature increase rates. The lake stratification intensity order was similar to those of the LSWT increases and correlations. SY and DC displayed significant correlations between LSWT (0.99) and PEA (0.91). Thus, the LSWT significantly affected stratification when the water temperature increased. PD demonstrated the lowest correlation between LSWT and PEA. Inflow, outflow, rainfall, wind speed, and retention time were significantly correlated, which varied within and between lakes depending on lake topographical, hydraulic, and hydrological factors. Thus, hydraulic problems and nutrients should be managed to minimize their effects on lake water quality and aquatic ecosystems because lake cyanobacteria can increase as localized water temperatures increase.


Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1109
Author(s):  
Nobuaki Kimura ◽  
Kei Ishida ◽  
Daichi Baba

Long-term climate change may strongly affect the aquatic environment in mid-latitude water resources. In particular, it can be demonstrated that temporal variations in surface water temperature in a reservoir have strong responses to air temperature. We adopted deep neural networks (DNNs) to understand the long-term relationships between air temperature and surface water temperature, because DNNs can easily deal with nonlinear data, including uncertainties, that are obtained in complicated climate and aquatic systems. In general, DNNs cannot appropriately predict unexperienced data (i.e., out-of-range training data), such as future water temperature. To improve this limitation, our idea is to introduce a transfer learning (TL) approach. The observed data were used to train a DNN-based model. Continuous data (i.e., air temperature) ranging over 150 years to pre-training to climate change, which were obtained from climate models and include a downscaling model, were used to predict past and future surface water temperatures in the reservoir. The results showed that the DNN-based model with the TL approach was able to approximately predict based on the difference between past and future air temperatures. The model suggested that the occurrences in the highest water temperature increased, and the occurrences in the lowest water temperature decreased in the future predictions.


2020 ◽  
Vol 92 (3) ◽  
pp. 391-408
Author(s):  
Maksym Łaszewski

Thermal regime has a critical impact on the lotic environment, as maximum temperature determines the boundaries of the occurrence of aquatic species, seasonal and diurnal water temperature variations affect their bioenergetics, while the timing of specific water temperature values during the year is important in the context of spawning and migrations. However, despite the great importance of water temperature studies in the context of environmental management and fisheries, as well as the development of accurate measurement techniques, such investigations have received relatively limited attention in Poland. The current study attempted to examine the seasonal differentiation of water temperature in lowland rivers. For this purpose, water temperature was recorded from the 1st of May 2015 to the 30th of April 2019 with a temporal resolution of 30-minutes. Digital temperature reorders used to make the measurements were distributed across six sites in Jeziorka, Świder and Utrata catchments located on the Mazovian Lowland and the Southern Podlachia Lowland near Warsaw. The hydrometeorological background of the water temperature monitoring was determined on the basis of data from the Warszawa-Okęcie station and water gauging stations. On the basis of the measurement data, mean, maximum, and minimum monthly water temperatures were calculated and presented on the background of the appropriate air temperature data, while statistical distribution of the 30-minute water temperature, aggregated in a monthly timescale, was presented on the box and whiskers plots. The Ward method was used to group months similar in terms of their thermal conditions, while the Pearson correlation coefficient was applied to evaluate the strength of the relationship between water and air temperature. The results indicate that the seasonal course of water temperature follows the course of air temperature, with the highest mean monthly water temperatures recorded in July, while the lowest in January. Statistical distribution analysis of water temperature in individual months and its grouping by the Ward method allowed to identify two periods characterized by relatively stable thermal conditions and two periods of dynamic changes of water temperature. In contrast to the maximum values of water temperature, which were observed in the summer as a result of intensive solar radiation and low streamflow rates, the greatest variability of water temperature, as indicated by reference to mean daily range and standard deviation, was found in the spring months, i.e. in April and May, while the lowest in winter, from December to February. The relationship between daily mean water temperature and air temperature, established with the use of the Pearson correlation coefficient on a monthly basis, was clearly stronger during the spring increase and the autumn fall of the water temperature, which can be linked with greater vulnerability to atmospheric heat fluxes. A definitely weaker relationship was found in the winter and summer months, when greater importance can be attached to other drivers of stream temperature, like the presence of ice cover, cloudiness, riparian shading, and groundwater inflows.


2021 ◽  
Vol 2 ◽  
pp. 138-146
Author(s):  
V.K. Smakhtin ◽  

Assessment of changes in air temperature and precipitation in Transbaikalia/ Smakhtin V.K. // Hydrometeorological Research and Forecasting, 2021, no. 2 (380), pp. 138-146. The paper analyzes long-term fluctuations in average air temperature and annual total precipitation in Transbaikalia. Between 1951 and 2020, air temperature increased by 2.3 °C according to 40 weather stations. Warming is mainly manifested in the air temperature rise in February, March and April. From 1955 to 2017, the decrease in annual total precipitation was 56 mm in the Amur basin and 39 mm in the Yenisei basin. The trends are reliable at the 5% significance level. In the Lena basin, annual total precipitation during the mentioned period increased by 7 mm, the trend is not reliable at the 5% significance level. The high-water phase has been observed since 2017. Taking into account that two previous high-water phases lasted 16‒17 years, it may be supposed that a risk of precipitation above the normal will be kept in the next 13–14 years. Keywords: climate change, air temperature, precipitation, phases of water content, trendsRef. 81.


2014 ◽  
Vol 18 (5) ◽  
pp. 1481-1485
Author(s):  
Xiao-Juan Chen ◽  
Xiao-Hua Yang ◽  
Jun He ◽  
Xing-Hui Xia ◽  
Never Mujere

Miyun reservoir is a surface water source of the city of Beijing. This paper explores the relationship between reservoir basin runoff and climate change. Statistical analyses are employed to analyze the variations in rainfall, air temperature, and runoff in the reservoir basin. Results show uneven inter-annual variability in rainfall data series. Air temperature show a rising trend with 1993 and 1994 being the two significant mutation years. Runoff has been decreasing over the years. Based one inter-annual analysis, July and August had the largest runoff. Elastic analysis shows no significant relationship between rainfall and runoff.


2020 ◽  
Vol 68 (3) ◽  
pp. 260-270 ◽  
Author(s):  
Mariusz Ptak ◽  
Mariusz Sojka ◽  
Bogumił Nowak

AbstractLake Śniardwy is the largest among more than 7000 Polish lakes. So far, it has not been a subject of detailed investigations concerning long-term changes in water temperature or ice regime. A considerable change in thermal and ice conditions has been observed in the period 1972–2019. Mean annual water temperature increased by 0.44°C dec−1 on average, and was higher than an increase in air temperature (0.33°C dec−1). In the monthly cycle, the most dynamic changes occurred in April (0.77°C dec−1). In the case of ice cover, it appeared increasingly later (5.3 days dec−1), and disappeared earlier (3.0 days dec−1). The thickness of ice cover also decreased (2.4 cm dec−1). Statistical analysis by means of a Pettitt test showed that the critical moment for the transformations of the thermal and ice regime was the end of the 1980’s. In addition to the obvious relations with air temperature for both characteristics, it was evidenced that the occurrence of ice cover depended on wind speed and snow cover. The recorded changes in the case of Lake Śniardwy are considered unfavourable, and their consequences will affect the course of physical, chemical, and biological processes in the largest lake in Poland.


2018 ◽  
Vol 13 (3) ◽  
pp. 345-355
Author(s):  
Noper Tulak ◽  
Handoko Handoko ◽  
Rini Hidayati ◽  
Upik Kesumawati ◽  
Lukman Hakim

Koya Barat village is one of the areas in Jayapura City which has high incidence of malaria. Malaria cases in this region are affected by local conditions, including the climate and environment of aquatic habitats.The purpose of this study was to analyze the effect of climatic factors and habitat characteristics on Anopheleslarval density in Koya Barat village. The method used is field observation with descriptive and statistical analysis approach.The results showed that there are four parameters that significantly affect on larval density, namely rainfall, air temperature, water temperature and salinity. The relationship between rainfall with the larval density in freshwater permanent habitat is negative linear. While in brackish water permanent habitat and semi permanent habitat is non-linear (2nd order polynomial). The relationship between air temperature, water temperature and salinity with the larval density in freshwater habitat are positive linear, while in brackish water habitat and semi permanent habitat are negative linear.


2021 ◽  
Vol 286 ◽  
pp. 04003
Author(s):  
Daniela-Elena Gogoașe-Nistoran ◽  
Cristina Sorana Ionescu ◽  
Ioana Opriș

Daily variation of Danube River temperature measured at Oltenitț gauging station over 9 years (2008-2016) was analysed in comparison with the air temperature measured by satellite in the same location between 1979-2020. Air temperature shows a nearly 2°C increase over the 40-years period, which can be attributed to both climate warming and anthropic impact. Water temperature was modeled with a sinusoidal function and variation with discharge was discussed. Long-term trend of hourly surface air temperature variation was obtained from Open Weather data. Air - water temperature dependency was fitted with a logistic function with good approximation. Resulting correlations help predict water temperature as a function of satellite - measured air temperature.


2006 ◽  
Vol 6 (2) ◽  
pp. 223-230
Author(s):  
A. Hashimoto

Good quality raw material gives a good quality product. This is a fundamental rule of production not only for commodities but also for our drinking water. The citizens of Kitakyushu city have been aware of this rule and started the campaign to preserve the drinking water source, and its surrounding natural environment. The catchphrase for the campaign is “Come back Ayufish to the river”. For Japanese people, ayufish is one of the most suitable indicators of clean water or clean river. More than a thousand citizens take part in this campaign every year. A group of environmental chemists have supported this campaign by sharing the long-term monitoring data for 40 years with the NGO and also the relationship between physiological impact of water quality such as BOD and MBAS on the behavior of ayufish to return to the river is discussed.


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