scholarly journals Effects of reservoir operation and climate change on thermal stratification of a canyon-shaped reservoir, in northwest China

2017 ◽  
Vol 18 (2) ◽  
pp. 418-429 ◽  
Author(s):  
Yang Li ◽  
Ting-lin Huang ◽  
Zi-zhen Zhou ◽  
Sheng-hai Long ◽  
Hai-han Zhang
Keyword(s):  
Climate Change ◽  
Surface Water ◽  
Water Temperature ◽  
Water Column ◽  
Air Temperature ◽  
Thermal Regime ◽  
Reservoir Operation ◽  
Thermal Stratification ◽  
Surface Water Temperature ◽  
Water Column Stability

Abstract Thermal stratification has a significant impact on water quality and ecological characteristics. Reservoir operation and climate change have an effect on the thermal regime. The Jinpen Reservoir is a large canyon-shaped reservoir located in Shaanxi Province with a strong thermal stratification, which resulted in an anaerobic condition in the hypolimnion. We used a hydrodynamic module based on MIKE 3 to simulate the thermal structure of the Jinpen Reservoir and study the relationship between the thermal regime, reservoir operation and climate change. Based on the daily hydrological and climatic data from 2004 to 2013, we made 13 hypothetical simulated conditions that included extreme change of inflow volume, water level, air temperature, radiation, inflow water temperature and selective withdrawal to explore the effect of different factors on the thermal regime. The results showed that the period of thermal stratification, water column stability and surface water temperature were influenced by these factors. With the increase of air temperature, the simulation results indicated a stronger thermal stratification and a higher surface water temperature, which could cause water safety problems. Deep withdrawal could decrease water column stability and prompt water column mixing early, which could be used by reservoir managers to optimize the reservoir operation.

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.

Changing Climatic Conditions Affect Surface Water Quality in Southwestern Louisiana in the United States

2021 ◽  
Author(s):  
Katherine Eddings ◽  
Durga D Poudel ◽  
Timothy W. Duex ◽  
Robert Miller ◽  
J. Calvin Berry
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Surface Water ◽  
Water Temperature ◽  
Air Temperature ◽  
Quality Parameters ◽  
Climatic Conditions ◽  
Water Quality Parameters ◽  
Surface Water Temperature ◽  
Temperature And Precipitation

Climate change impacts on rising temperatures, changes on rainfall patterns, drought, flooding, sea level rise, glacier melts, and incidence of diseases and parasites are reported worldwide in recent decades. This study investigates the effects of changing climatic conditions – particularly air temperature and precipitation, on surface water temperatures and other water quality parameters, such as the conductivity, dissolved oxygen (DO), pH, and turbidity. A statistical analysis was performed on air temperature and precipitation data from 1980 to 2005 to determine the changing climatic conditions. The water quality data for four waterbodies in southwestern Louisiana was also analyzed to examine trends between the air temperature and surface water temperatures, precipitation and surface water temperatures, and precipitation and water quality parameters. There was an unexpected increase in surface water temperature with an increase in precipitation. As the precipitation and air temperature increased, so did the surface water temperature. This increase in surface water temperature was correlated with decrease in DO levels. The increase in precipitation also correlated with an increase in pH and turbidity in Bayou Plaquemine Brule. This study’s findings could be utilized in a dynamic climate modeling system to provide more accurate predictions of climate change in southwestern Louisiana.

scholarly journals On Recent Trends in Atmospheric and Limnological Variables in Lake Ontario

2012 ◽  
Vol 25 (17) ◽  
pp. 5807-5816 ◽  
Author(s):  
Anning Huang ◽  
Yerubandi R. Rao ◽  
Weitao Zhang
Keyword(s):  
Surface Water ◽  
Water Temperature ◽  
Air Temperature ◽  
Surface Wind ◽  
Lake Ontario ◽  
Surface Wind Speed ◽  
Surface Mixed Layer ◽  
Surface Water Temperature ◽  
Recent Trends ◽  
Annual Time

Abstract The surface air and water temperatures increased at all seasonal and annual time scales during the last 40 yr in Lake Ontario. The annual mean air and surface water temperatures have increased by 1.43° ±0.39° and 1.26° ±0.32°C, respectively, over 1970–2009. The air temperature increased at a faster rate than the surface water temperature in winter and autumn, whereas in spring and summer the surface water temperature warmed faster than the air temperature. The length of summer stratified season has increased by 12 ± 2 days since the early 1970s due to the increase in water temperature. The decline of surface wind speed over Lake Ontario resulted in a shallower surface mixed layer and enhanced the summer thermal stratification, which increased the summer surface water temperature more rapidly than the air temperature.

Aspects of the biology of Mysis mixta (Lilljeborg 1852) (Crustacea, Mysidacea) in New Hampshire coastal waters

1982 ◽  
Vol 60 (6) ◽  
pp. 1275-1281 ◽  
Author(s):  
Stephen A. Grabe ◽  
Elizabeth R. Hatch
Keyword(s):  
Surface Water ◽  
Water Temperature ◽  
New Hampshire ◽  
Coastal Waters ◽  
Thermal Stratification ◽  
Juvenile Growth ◽  
Surface Water Temperature ◽  
Spawning Period ◽  
Mysis Mixta ◽  
Inshore Waters

Mysis mixta spawned from December to April in coastal New Hampshire waters. Females outnumbered males throughout all but the earliest dates of the spawning period. Average clutch size was 60 eggs or larvae. Juveniles were hyperbenthic during the day and migrated into the water column at night. Juveniles remained in inshore waters until surface water temperature s exceeded 12 °C, corresponding with the onset of thermal stratification. Juvenile growth was slow through mid-April then increased sharply from late April through June. Less than 5% of the population appeared to live longer than 1 year.

scholarly journals Seasonal lake surface water temperature trends reflected by heterocyst glycolipid based molecular thermometers

2015 ◽  
Vol 12 (1) ◽  
pp. 751-778
Author(s):  
T. Bauersachs ◽  
J. Rochelmeier ◽  
L. Schwark
Keyword(s):  
Surface Water ◽  
Water Temperature ◽  
Water Column ◽  
Environmental Parameters ◽  
Relative Distribution ◽  
Surface Water Temperature ◽  
Heterocystous Cyanobacteria ◽  
Molecular Thermometers ◽  
Linear Correlations ◽  
Oxygen Concentrations

Abstract. It has been demonstrated that the relative distribution of heterocyst glycolipids (HGs) in cultures of N2-fixing heterocystous cyanobacteria is largely controlled by growth temperature, suggesting a potential use of these components in paleoenvironmental studies. Here, we investigated the effect of environmental parameters (e.g. surface water temperatures, oxygen concentrations and pH) on the distribution of HGs in a natural system using water column filtrates collected from Lake Schreventeich (Kiel, Germany) from late July to the end of October 2013. HPLC-ESI/MS analysis revealed a dominance of 1-(O-hexose)-3,25-hexacosanediols (HG26 diols) and 1-(O-hexose)-3-keto-25-hexacosanol (HG26 keto-ol) in the solvent extracted water column filtrates, which were accompanied by minor abundances of 1-(O-hexose)-3,27-octacosanediol (HG28 diol) and 1-(O-hexose)-3-keto-27-octacosanol (HG28 keto-ol) as well as 1-(O-hexose)-3,25,27-octacosanetriol (HG28 triol) and 1-(O-hexose)-3-keto-25,27-octacosanediol (HG28 keto-diol). Fractional abundances of alcoholic and ketonic HGs generally showed strong linear correlations with surface water temperatures and no or only weak linear correlations with both oxygen concentrations and pH. Changes in the distribution of the most abundant diol and keto-ol (e.g., HG26 diol and HG26 keto-ol) were quantitatively expressed as the HDI26 (heterocyst diol index of 26carbon atoms) with values of this index ranging from 0.89 in mid-August to 0.66 in mid-October. An average HDI26 value of 0.79, which translates into a calculated surface water temperature of 15.8 ± 0.3 °C, was obtained from surface sediments collected from Lake Schreventeich. This temperature – and temperatures obtained from other HG indices (e.g., HDI28 and HTI28) – is similar to the one measured during maximum cyanobacterial productivity in early to mid-September and suggests that HGs preserved in Lake Schreventeich sediments record summer surface water temperatures. As N2-fixing heterocystous cyanobacteria are widespread in present-day freshwater and brackish environments, we conclude that the distribution of HGs in sediments may allow the reconstruction of surface water temperatures of modern and potentially ancient lacustrine settings.

scholarly journals Browning‐Related Decreases in Water Transparency Lead to Long‐Term Increases in Surface Water Temperature and Thermal Stratification in Two Small Lakes

2018 ◽  
Vol 123 (5) ◽  
pp. 1651-1665 ◽  
Author(s):  
Rachel M. Pilla ◽  
Craig E. Williamson ◽  
Jing Zhang ◽  
Robyn L. Smyth ◽  
John D. Lenters ◽  
...  
Keyword(s):  
Surface Water ◽  
Water Temperature ◽  
Thermal Stratification ◽  
Water Transparency ◽  
Surface Water Temperature ◽  
Small Lakes

scholarly journals The impact of global warming on lake surface water temperature in Poland - the application of empirical-statistical downscaling, 1971-2100

2018 ◽  
Vol 77 (2) ◽  
Author(s):  
Bartosz Czernecki ◽  
Mariusz Ptak
Keyword(s):  
Surface Water ◽  
Water Resources ◽  
Water Temperature ◽  
Air Temperature ◽  
Statistical Downscaling ◽  
Surface Water Temperature ◽  
Lake Surface ◽  
The Future ◽  
Rcp 8.5 ◽  
The Impact

The paper presents historical (1971-2015) and scenario-based (2006-2100) changes in surface water temperatures in 10 lakes of Poland. The analysis of historical measurement (1971-2015) showed that mean annual lake surface water temperature (LSWT) was characterised by an increasing tendency by 0.37°C∙dec-1 on average, and was higher by 0.01°C∙dec-1 than air temperature in the analogical period. The highest increase in LSWT was recorded in spring months (April, May) and in summer (July). The future changes in LSWT was based on simulations of 33 AOGCMs available in the scope of CMIP5 project for RCPs: 2.6, 4.5, 6.0, and 8.5. The developed empirical-statistical downscaling models (ESD) use the air temperature field as predictors, with consideration of autocorrelation for two preceding months. ESD models are characterised by high quality of reconstruction of water temperatures in the historical period, with correlation from 0.82 (December, February) to 0.93 (July). The future CMIP5 scenarios for the period 2006-2100 assume an increase in air temperature at the end of the 21st century from +1.8°C (RCP 2.6) to +5.1°C (RCP 8.5) in reference to the period 1971-2005. According to the downscaling models, this corresponds to an increase in water temperature in the analysed lakes ranging from +1.4°C (RCP 2.6) to +4.2°C (RCP 8.5) in the years 2081-2100, respectively, with evident variability between the adopted emission paths beginning from the period 2041-2060. At a monthly scale, water temperature will increase the slowest in February (2081-2100: RCP 2.6 = +0.5°C, RCP 8.5 = +1.8°C). The highest increase in temperature will occur from May to August (RCP 8.5 = +6°C in June).Substantial effects of transformations of the thermal regime are already observed today, e,g. in the reduction of the ice season length. According to developed scenarios, a further considerable increase in water temperature will be the primary factor determining the transformation of lake ecosystems. The obtained results provide a theoretical basis for further research conducted in the scope of many disciplines, among others hydrology, hydrobiology, ecology, water management, energy production, etc. In the case of Poland, issues related to low water resources per capita are particularly important. Contemporary studies concerning changes in water resources showed that the natural factor playing the key role in their reduction is temperature increase and therefore it should constitute for the possibly fast development of multidisciplinary concepts of mitigation policy to potential impact of climate change. 

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