scholarly journals Effects of Long-Term Increases in Water Temperature and Stratification on Large Artificial Water-Source Lakes in South Korea

Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2341
Author(s):  
Soon-Ju Yu ◽  
Ju-Yeon Son ◽  
Ho-Yeong Kang ◽  
Yong-Chul Cho ◽  
Jong-Kwon Im
Keyword(s):  
South Korea ◽  
Water Temperature ◽  
Aquatic Ecosystems ◽  
Water Source ◽  
Lake Surface ◽  
Lake Water Quality ◽  
Slope Estimator ◽  
Artificial Water ◽  
Lake Stratification

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.

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
Keyword(s):  
Elevated Temperature ◽  
Numerical Model ◽  
South Korea ◽  
Water Temperature ◽  
Air Temperature ◽  
Water Source ◽  
High Water ◽  
Temperature Hysteresis ◽  
The Relationship

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.

scholarly journals Effect of under-ice light intensity and convective mixing on chlorophyll a distribution in a small mesotrophic lake

2019 ◽  
Vol 46 (3) ◽  
pp. 259-269
Author(s):  
N. I. Palshin ◽  
G. E. Zdorovennova ◽  
R. E. Zdorovennov ◽  
T. V. Efremova ◽  
G. G. Gavrilenko ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Water Temperature ◽  
Chlorophyll A ◽  
Chlorophyll Concentration ◽  
Bottom Surface ◽  
Lake Surface ◽  
Convective Mixing ◽  
Radiation Fluxes ◽  
Coefficients Of Variation

Data of long-term measurements of under-ice solar radiation, water temperature, and chlorophyll a are analyzed in four phytoplankton groups (green, diatoms, blue-green, and cryptophyte algae) in a small mesotrophic Vendyurskoe Lake (Karelia) in the period of spring under-ice convection. It is shown that, after thawing away of snow cover from lake surface, under-ice illumination increases, water temperature rises, the depth of convectively mixed layer (CML) increases, and microalga photosynthesis intensifies. In the daytime, chlorophyll a extremums appear in the CML, and, unlike the homogeneous characteristics (water electric conductivity, mineralization, etc.), the cells of different phytoplankton species can be used as tracers in studying convective mixing. A prognostic equation is obtained, reflecting an inverse dependence of the coefficients of variation of chlorophyll a concentration in CML on solar radiation fluxes, penetrating under ice bottom surface. A direct relationship was shown to exist between the increase in chlorophyll concentration in CML and its thickness.

scholarly journals Prediction of lake surface temperature using the air2water model: guidelines, challenges, and future perspectives

2016 ◽  
Vol 7 (1) ◽  
Author(s):  
Sebastiano Piccolroaz
Keyword(s):  
Surface Temperature ◽  
Water Temperature ◽  
Numerical Models ◽  
Model Performance ◽  
Primary Role ◽  
Future Perspectives ◽  
Lake Surface ◽  
Lake Water Quality ◽  
Ecological Processes ◽  
Wide Range

<p>Water temperature plays a primary role in controlling a wide range of physical, geochemical and ecological processes in lakes, with considerable influences on lake water quality and ecosystem functioning. Being able to reliably predict water temperature is therefore a desired goal, which stimulated the development of models of different type and complexity, ranging from simple regression-based models to more sophisticated process-based numerical models. However, both types of models suffer of some limitations: the first are not able to address some fundamental physical processes as e.g., thermal stratification, while the latter generally require a large amount of data in input, which are not always available. In this work, lake surface temperature is simulated by means of <em>air2water</em>, a hybrid physically-based/statistical model, which is able to provide a robust, predictive understanding of LST dynamics knowing air temperature only. This model showed performances that are comparable with those obtained by using process based models (a root mean square error on the order of 1°C, at daily scale), while retaining the simplicity and parsimony of regression-based models, thus making it a good candidate for long-term applications.</p><p>The aim of the present work is to provide the reader with useful and practical guidelines for proper use of the <em>air2water</em> model and for critical analysis of results. Two case studies have been selected for the analysis: Lake Superior and Lake Erie. These are clear and emblematic examples of a deep and a shallow temperate lake characterized by markedly different thermal responses to external forcing, thus are ideal for making the results of the analysis the most general and comprehensive. Particular attention is paid to assessing the influence of missing data on model performance, and to evaluating when an observed time series is sufficiently informative for proper model calibration or, conversely, data are too scarce thus leading to the risk of overfitting. The final aim of the work is to facilitate the use of the model also by scientists that do not necessarily have a solid background on modelling or physics. However, this work should not be considered simply as a collection of best practices, but also as the attempt to foster the communication and interaction among colleagues of a branch of science, limnology, that suffer of significant fragmentation. This is summarized in the future perspectives and challenges concerning potential improvements of the <em>air2water</em>, with a particular emphasis on possible cross-sectoral applications.</p>

scholarly journals Regional variability in black carbon and carbon monoxide ratio from long-term observations over East Asia: assessment of representativeness for black carbon (BC) and carbon monoxide (CO) emission inventories

2020 ◽  
Vol 20 (1) ◽  
pp. 83-98 ◽  
Author(s):  
Yongjoo Choi ◽  
Yugo Kanaya ◽  
Seung-Myung Park ◽  
Atsushi Matsuki ◽  
Yasuhiro Sadanaga ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
South Korea ◽  
East Asia ◽  
Black Carbon ◽  
North Korea ◽  
Northeast China ◽  
Emission Inventory ◽  
East China ◽  
Co Emission

Abstract. The black carbon (BC) and carbon monoxide (CO) emission ratios were estimated and compiled from long-term, harmonized observations of the ΔBC∕ΔCO ratios under conditions unaffected by wet deposition at four sites in East Asia, including two sites in South Korea (Baengnyeong and Gosan) and two sites in Japan (Noto and Fukuoka). Extended spatio-temporal coverage enabled estimation of the full seasonality and elucidation of the emission ratio in North Korea for the first time. The estimated ratios were used to validate the Regional Emission inventory in ASia (REAS) version 2.1 based on six study domains (“East China”, “North China”, “Northeast China”, South Korea, North Korea, and Japan). We found that the ΔBC∕ΔCO ratios from four sites converged into a narrow range (6.2–7.9 ng m−3 ppb−1), suggesting consistency in the results from independent observations and similarity in source profiles over the regions. The BC∕CO ratios from the REAS emission inventory (7.7 ng m−3 ppb−1 for East China – 23.2 ng m−3 ppb−1 for South Korea) were overestimated by factors of 1.1 for East China to 3.0 for South Korea, whereas the ratio for North Korea (3.7 ng m−3 ppb−1 from REAS) was underestimated by a factor of 2.0, most likely due to inaccurate emissions from the road transportation sector. Seasonal variation in the BC∕CO ratio from REAS was found to be the highest in winter (China and North Korea) or summer (South Korea and Japan), whereas the measured ΔBC∕ΔCO ratio was the highest in spring in all source regions, indicating the need for further characterization of the seasonality when creating a bottom-up emission inventory. At levels of administrative districts, overestimation in Seoul, the southwestern regions of South Korea, and Northeast China was noticeable, and underestimation was mainly observed in the western regions in North Korea, including Pyongyang. These diagnoses are useful for identifying regions where revisions in the inventory are necessary, providing guidance for the refinement of BC and CO emission rate estimates over East Asia.

scholarly journals Surface Water Temperature Predictions at a Mid-Latitude Reservoir under Long-Term Climate Change Impacts Using a Deep Neural Network Coupled with a Transfer Learning Approach

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1109
Author(s):  
Nobuaki Kimura ◽  
Kei Ishida ◽  
Daichi Baba
Keyword(s):  
Climate Change ◽  
Surface Water ◽  
Water Temperature ◽  
Transfer Learning ◽  
Air Temperature ◽  
Climate Models ◽  
Temporal Variations ◽  
Training Data ◽  
Surface Water Temperature

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.

scholarly journals Is Establishing a New Partnership Useful Information for Investors in the Smartphone Supply Market?

2021 ◽  
Vol 13 (10) ◽  
pp. 5573
Author(s):  
Insung Son ◽  
Sihyun Kim
Keyword(s):  
South Korea ◽  
Stock Price ◽  
Individual Investors ◽  
Trading Patterns ◽  
Market Impacts ◽  
The Us ◽  
Signaling Effect ◽  
Parts Suppliers ◽  
Country Specific

This study analyzed partner volatility (new, old, revocation partners) and country-specific signal effects (United States (US), Taiwan, Japan, and South Korea) for Apple iPhone parts suppliers from 2007 to 2018. Mid- to long-term stock price movements were also analyzed to define trading patterns by investor type. The results using logit regression analysis revealed that new partners and revocation partners each have a signaling effect perceived as positive and negative information in the short term, and the excess returns by country showed a positive signaling effect in the order of the US, Taiwan, South Korea, and Japan. The findings also suggest that the change in the new partners’ stock price after the preannouncement of new products was useful investment information. Moreover, information asymmetry was found between individual investors, institutions, and foreigners. Results indicate that new partner selection in the smartphone market impacts corporate value and serves as useful investment information.

From gradual erosion to revitalization: National Social Dialogue Institutions and policy effectiveness

2021 ◽  
pp. 095968012110183
Author(s):  
Igor Guardiancich ◽  
Oscar Molina
Keyword(s):  
Decision Making ◽  
Problem Solving ◽  
South Korea ◽  
Industrial Relations ◽  
Political Support ◽  
Policy Effectiveness ◽  
Substantial Evidence ◽  
Social Dialogue ◽  
Socioeconomic Issues

We explore the factors behind the long-term erosion of National Social Dialogue Institutions (NSDIs) to provide insights about the conditions for their revitalization. By applying policy analysis insights into the industrial relations field, we argue that limited policy effectiveness goes a long way towards explaining the erosion experienced by many NSDIs worldwide in recent years. Drawing on a global survey and on case studies of NSDIs in Brazil, Italy and South Korea, we show that these institutions’ policy effectiveness crucially depends on combinations of their problem-solving capacity, an encompassing mandate to deal with relevant socioeconomic issues and an enabling environment that grants the inclusion of social dialogue into decision making. With regard to rekindling their role, the article provides substantial evidence that two sub-dimensions of effectiveness are key: enjoying political support and having an ‘effective mandate’ as opposed to relying on just a formal remit to deal with socioeconomic issues of interest.

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