scholarly journals Sub-Daily Temperature Heterogeneity in a Side Channel and the Influence on Habitat Suitability of Freshwater Fish

2019 ◽  
Vol 11 (20) ◽  
pp. 2367 ◽  
Author(s):  
Frank P.L. Collas ◽  
Wimala K. van Iersel ◽  
Menno W. Straatsma ◽  
Anthonie D. Buijse ◽  
Rob S.E.W. Leuven
Keyword(s):  
Climate Change ◽  
Surface Water ◽  
Water Temperature ◽  
Freshwater Fish ◽  
Habitat Suitability ◽  
Wave Radiation ◽  
Side Channel ◽  
Thermal Imagery ◽  
Riverine Ecosystems ◽  
Alien Fish

Rising surface water temperatures in fluvial systems increasingly affect biodiversity negatively in riverine ecosystems, and a more frequent exceedance of thermal tolerance levels of species is expected to impoverish local species assemblages. Reliable prediction of the effect of increasing water temperature on habitat suitability requires detailed temperature measurements over time. We assessed (1) the accuracy of high-resolution images of water temperature of a side channel in a river floodplain acquired using a consumer-grade thermal camera mounted on an unmanned airborne vehicle (UAV), and (2) the associated habitat suitability for native and alien fish assemblages. Water surface temperatures were mapped four times throughout a hot summer day and calibrated with 24 in-situ temperature loggers in the water at 0.1 m below the surface using linear regression. The calibrated thermal imagery was used to calculate the potentially occurring fraction (POF) of freshwater fish using species sensitivity distributions. We found high temperatures (25–30 °C) in the side channel during mid-day resulting in reduced habitat suitability. The accuracy of water temperature estimates based on the RMSE was 0.53 °C over all flights (R2 = 0.94). Average daily POF was 0.51 and 0.64 for native and alien fish species in the side channel. The error of the POF estimates is 76% lower when water temperature is estimated with thermal UAV imagery compared to temperatures measured at an upstream gauging station. Accurately quantifying water temperature and the heterogeneity thereof is a critical step in adaptation of riverine ecosystems to climate change. Our results show that measurements of surface water temperature can be made accurately and easily using thermal imagery from UAVs allowing for an improved habitat management, but coincident collection of long wave radiation is needed for a more physically-based prediction of water temperature. Because of climate change, management of riverine ecosystems should consider thermal pollution control and facilitate cold water refugia and connectivity between waterbodies in floodplains and the cooler main channel for fish migration during extremely hot summer periods.

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 The Impact of Local Climate Change on Drinking Water Quality in a Distribution System

2018 ◽  
Author(s):  
David Eugene Kimbrough
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Drinking Water ◽  
Surface Water ◽  
Water Temperature ◽  
Distribution System ◽  
Local Climate ◽  
Air Temperatures ◽  
Local Climate Change ◽  
The Impact

In this study, air temperatures were collected between 1985 and 2016 and compared to water temperatures in four locations in the distribution system of Pasadena Water & Power (PWP) that received imported surface water between 2001 and 2016 and from the purveyor of imported water.  The concentration of chloramine residual and nitrite concentrations were collected between 2001 and 2016 these five locations.  The results indicate that the median nighttime temperature of the period 2009 - 2016 was 1.6 oC warmer than the period of 1985 - 2000 and 0.5 oC warmer than the period 2001 - 2008.  The median water temperature in the four distribution system samples increased by 0.8 oC to 1.4 oC depending on the location over the study period (p<0.001).  The median chloramine concentration fell significantly (p<0.001) at three distribution system locations and the nitrite concentrations increased significantly at all four distribution system locations. 

Factors influencing peak summer surface water temperature in Canada’s large lakes

2018 ◽  
Vol 75 (7) ◽  
pp. 1005-1018 ◽  
Author(s):  
Charles K. Minns ◽  
Brian J. Shuter ◽  
Andrew Davidson ◽  
Shusen Wang
Keyword(s):  
Climate Change ◽  
Surface Water ◽  
Water Temperature ◽  
Secchi Depth ◽  
Open Water ◽  
Mean Annual Precipitation ◽  
Temperature Cycle ◽  
Large Lakes ◽  
Positive Effects ◽  
Annual Peak

Seasonal water temperature data from 388 large Canadian lakes (area ≥ 100 km2) were used to develop improved empirical tools for forecasting the impacts of climate change on the magnitude (TP) and time of occurrence (JP) of annual peak surface water temperatures. Analyses of remotely sensed open-water temperatures with sinusoidal models produced estimates of TP and JP predominately better than other models. Those estimates were analyzed for lake and climate patterns. Linear mixed effects regression produced a significant model of TP with fixed positive effects for mean July and annual air temperatures and lake perimeter, but negative effects with mean July and annual percent cloud cover, mean annual precipitation, range of monthly mean global clear sky radiation, area, and elevation. Subsets of the estimates with mean, maximum, or Secchi depth values produced similarly significant models with negative depth coefficients. JP was relatively invariant but small, significant lake and climate effects were detected. The best models identified in our analyses will be useful tools for forecasting how climate change will alter aspects of the limnetic seasonal water temperature cycle that strongly influences the species composition and productivity of their fisheries.

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.

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.

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