scholarly journals Assessment of Water Quality and Thermal Stress for an Artificial Fish Shelter in an Urban Small Pond during Early Summer

Water ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 139
Author(s):  
Chang Hyuk Ahn ◽  
Saeromi Lee ◽  
Ho Myeon Song ◽  
Jae Roh Park ◽  
Jin Chul Joo
Keyword(s):  
Water Quality ◽  
Thermal Stress ◽  
Water Temperature ◽  
Open Space ◽  
Phenomenological Study ◽  
Quality Parameters ◽  
Early Summer ◽  
Freshwater Ecosystem ◽  
Artificial Wetlands ◽  
Forced Circulation

: This study evaluated water quality variations in an artificial deep pool (ADP), which is an underground artificial structure built in a shallow pond as a fish shelter. The water temperature, pH, dissolved oxygen (DO), and electrical conductivity (EC) were measured on an hourly basis in the open space and inside the ADP, and a phenomenological study was performed, dividing seasons into normal and rainy seasons and environments into stagnant and circulating conditions. The results showed that the water quality parameters inside the ADP exhibit lower fluctuations and diurnal variations compared with the open space. On average, the water temperature inside the ADP is lower than outside it by 1.7–3.7 °C in stagnant conditions, and by 0.6–0.7 °C in circulating conditions during early summer. Thermal stratification occurs inside the ADP but is temporarily disturbed due to the mixing from the forced circulation and the rainwater input through rainfall events. The ADP provided a constant and optimal water temperature for living and spawning for bitterling (i.e., 15.0–21.0 °C), which dominated in experimental pond during spring to summer. Most importantly, the ADP was able to significantly reduce the thermal stress of the fish in the study site, and as a result, the bitterling, a cool water fish species, could successfully become dominant. Finally, the deployment of the ADP appears to provide a practical alternative for effective fishery resources management to improve species diversity and fish communities in an artificial freshwater ecosystem (garden pond, park pond, other artificial wetlands, etc.).

scholarly journals Research and Design of Distributed IoT Water Environment Monitoring System Based on LoRa

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Wei Chen ◽  
Xiao Hao ◽  
JianRong Lu ◽  
Kui Yan ◽  
Jin Liu ◽  
...  
Keyword(s):  
Water Quality ◽  
Water Temperature ◽  
Real Time ◽  
Monitoring System ◽  
Water Environment ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Environment Monitoring ◽  
Long Distance ◽  
Internet Of Things Technology

In order to solve the problems of high labor cost, long detection period, and low degree of information in current water environment monitoring, this paper proposes a lake water environment monitoring system based on LoRa and Internet of Things technology. The system realizes remote collection, data storage, dynamic monitoring, and pollution alarm for the distributed deployment of multisensor node information (water temperature, pH, turbidity, conductivity, and other water quality parameters). Moreover, the system uses STM32L151C8T6 microprocessor and multiple types of water quality sensors to collect water quality parameters in real time, and the data is packaged and sent to the LoRa gateway remotely by LoRa technology. Then, the gateway completes the bridging of LoRa link to IP link and forwards the water quality information to the Alibaba Cloud server. Finally, end users can realize the water quality control of monitored water area by monitoring management platform. The experimental results show that the system has a good performance in terms of real-time data acquisition accuracy, data transmission reliability, and pollution alarm success rate. The average relative errors of water temperature, pH, turbidity, and conductivity are 0.31%, 0.28%, 3.96%, and 0.71%, respectively. In addition, the signal reception strength of the system within 2 km is better than -81 dBm, and the average packet loss rate is only 94%. In short, the system’s high accuracy, high reliability, and long distance characteristics meet the needs of large area water quality monitoring.

scholarly journals Study on physico-chemical features of water in Tarahara Fish Farm, Sunsari, Nepal

2017 ◽  
Vol 7 (1) ◽  
pp. 47-57
Author(s):  
Ganesh Bahadur Thapa ◽  
Joydeb Pal
Keyword(s):  
Water Quality ◽  
Water Temperature ◽  
Air Temperature ◽  
Physicochemical Parameters ◽  
Quality Parameters ◽  
Fish Farm ◽  
Fish Growth ◽  
Chemical Parameters ◽  
Physico Chemical ◽  
Peripheral Areas

Tarahara Fish Farm includes 37 large ponds as a fish super zone. Physicochemical parameters viz., air and water temperature, pH, DO, BOD, CO2, Cl-, TA and TH of these ponds were studied for two years (Nov. 2008 to Oct. 2010). The air temperature had positive and significant correlation with water temperature (r=0.893, P<0.01) but inverse and significant correlation with DO (r = - 0.669 P<0.05) and TH (r = - 0.673, P<0.05). Both air and water temperature showed a decreasing trend during the winter months of November to January and again September to October in both years. Similarly, positive and significant correlation showed by pH with DO (r =0.660, P<0.05) and BOD (r =0.846, P<0.05); by free CO2 with DO (r=0.854, P<0.01), chloride (r=0.648, P<0.05) and TA (r=0.616, P<0.05); by DO with TA (r =0.715, P<0.01) and chloride (r =0.625, P<0.05) and by TH with TA (r= 0.592, P<0.05) but inverse and significant correlation showed by pH with water temperature (r =-0.671, P<0.05); by free CO2 with BOD (r=-0.627, P<0.05) and by DO with BOD (r = -0.810, P <0.01). The water quality parameters were within suitable range for the fish growth and breeding with small fluctuations in different months during the first and second years. Physico-chemical parameters significantly (P<0.01; 0.05) differed between different months. However, no mass mortality of fish was recorded from this site. So, the area selected as fish super zone is fruitful to meet the expected production level of fishes and fish seeds in peripheral areas.

Influence of Seasonal Temperature Variation on pH, Dissolved Oxygen and Biological Oxygen Demand in Tamdil Lake, Mizoram, India

2018 ◽  
Vol 6 (2) ◽  
pp. 59-63
Author(s):  
Lalzahawmi Chenkual ◽  
◽  
B.P Mishra ◽  
Laltan puia ◽  
Mary Lalthansangi ◽  
...  
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Water Temperature ◽  
Significant Relationship ◽  
Water Samples ◽  
Oxygen Demand ◽  
Ecological Factors ◽  
Quality Parameters ◽  
Biological Oxygen Demand ◽  
Seasonal Temperature

Temperature is one of the most important ecological factors which play a significant role on the earth, and all the living organisms have evolved various methods to meet extremes of temperature. Seasonal temperature variations are quite significant in freshwater lakes and ponds. The present study deals with the effect of seasonal variations of water temperature on different water quality parameters of Tamdil lake, Mizoram, India, for a period of two years, i.e., from March, 2014 to February, 2016. The water samples were collected from five sampling sites, and the average reading was calculated for each of the water quality attributes namely, temperature, pH, Dissolved Oxygen (DO) and Biological Oxygen Demand (BOD). The water samples were analyzed monthly, and the results are computed on seasonal basis, i.e., pre-monsoon, monsoon, post- monsoon and winter seasons. Statistically, there was a positive and significant relationship between water temperature and pH, and negative significant relationship between temperature and DO. A negative correlation was observed between temperature and BOD. The result shows that there is a significant seasonal variation in physico-chemical parameters. The lake has not reached the polluted stage yet.

Establishment of the Lakes and Reservoirs’ Model

2012 ◽  
Vol 610-613 ◽  
pp. 1962-1966
Author(s):  
Xing Guan Ma ◽  
Jun Ping Sun ◽  
Zhe Pei ◽  
Yu Nan Gao ◽  
Jing Tang ◽  
...  
Keyword(s):  
Water Quality ◽  
Water Temperature ◽  
Simulation Method ◽  
Quality Parameters ◽  
Ecosystem Dynamics ◽  
Model Classification ◽  
Lakes And Reservoirs ◽  
Basic Equations ◽  
The Relationship

This article describes the simulation method of water temperature and the model classification of water quality in lakes and reservoirs, and classic model of ecosystem dynamics of lakes and reservoirs - BA model from the water quality parameters of the relationship between two aspects of the basic equations are introduced. On this basis, establish the eutrophication of ecological models of lakes and reservoirs.

scholarly journals Assessment of Quality Parameters of a Pond Water: A Limnological Case Study in Bareilly District

2021 ◽  
Vol 07 (08) ◽  
Author(s):  
Vikas Jain ◽  
Keyword(s):  
Water Quality ◽  
Water Temperature ◽  
Pond Water ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Total Hardness ◽  
Standard Procedures ◽  
Calcium And Magnesium

The manuscript herewith presents the assessment of water quality parameters in the samples drawn in year 2014-15 from Akshar Vihar pond, located centrally in district Bareilly (U.P.), India. Analysis of check parameters chosen, was performed by employing standard procedures laid down in APHA. The minimum to maximum values recorded in each month of the experimental year for pH, total hardness, DO, BOD, COD, calcium and magnesium were 7.2-8.8, 380 - 486mg/L, 4.2-10.6 mg/L, 1.0-1.6 mg/L, 3.8-8.4 mg/L, 52.97-74.84 mg/L and 56.74-72.98 mg/L respectively. Significant correlation was observed for COD with pH (0.816), carbonate (0.875) and bicarbonate (0.927); that of total hardness with magnesium (0.954) as well as of DO inversely with water temperature (-0.821).

Investigation into the Trichoptera fauna of the Opa Stream in Ile-Ife, southwestern Nigeria

Zoosymposia ◽  
2016 ◽  
Vol 10 (1) ◽  
pp. 85-90
Author(s):  
BABATUNDE AMUSAN ◽  
SYLVESTER OGBOGU
Keyword(s):  
Water Quality ◽  
Species Composition ◽  
Water Temperature ◽  
Negative Relationship ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Southwestern Nigeria ◽  
Dry Seasons ◽  
Wet And Dry Seasons

The species composition and abundance of caddisflies in association with some water quality parameters (pH, water temperature and conductivity) in Opa Stream in Ile-Ife, Nigeria were investigated during October 2009–August 2010. One hundred and ninety adult caddisflies collected from the stream represent six species in six genera and three families. Hydropsychidae had three species, which is more than were found in other families. The caddisflies showed a relative mean abundance of 62% and 38.9% in the wet and dry seasons, respectively. Caddisfly abundance was positively correlated with pH and conductivity but there was a negative relationship between water temperature and the abundance of caddisflies in the stream.

scholarly journals Assessing the Effect of Changing Ambient Air Temperature on Water Temperature and Quality in Drinking Water Distribution Systems

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1916
Author(s):  
Yuchuan Lai ◽  
David A. Dzombak
Keyword(s):  
Water Quality ◽  
Water Temperature ◽  
Air Temperature ◽  
Distribution Systems ◽  
Water Distribution ◽  
Ambient Air ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Temperature Changes ◽  
Drinking Water Distribution Systems

Drinking water distribution systems (DWDS) are affected by climate change and this work aimed to assess the effect of changing ambient air temperature on the water temperature and various water quality parameters in DWDS. A water temperature estimation model was identified and evaluated at seven specific locations in the U.S. and water quality parameters were assessed with a case study for Washington D.C. Preliminary estimation of changes in water temperature and two temperature-related parameters (the chlorine decay rate and bacterial activity) were developed for 91 U.S. cities using local air temperature observations and projections. Estimated water temperature changes in DWDS are generally equivalent to air temperature changes on an annual average basis, suggesting modest changes for the assessed historical periods and possibly more intensified changes in the future with greater increase in air temperature. As higher water age can amplify the temperature effect and the effects of temperature on some water quality parameters can be inter-related, yielding an aggregated effect, evaluation of extreme cases for DWDS will be of importance. In responding to changing climate conditions, assessments of DWDS water temperature changes and resulting impacts on water quality merit more attention to ensure appropriate adaptation of DWDS design and management.

scholarly journals Thermomineral water of Nikolicevo Spa (Eastern Serbia)

2007 ◽  
pp. 91-96
Author(s):  
Petar Dokmanovic ◽  
Veselin Dragisic ◽  
Slavko Spadijer
Keyword(s):  
Water Quality ◽  
Chemical Composition ◽  
Water Temperature ◽  
Water Movement ◽  
Wide Spectrum ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Outflow Rate ◽  
Scaling Process ◽  
Water Outflow

New monitoring results (2000-2002) of the thermomineral water outflow and quality regime of the Nikolicevo Spa (eastern Serbia) show that, during 30 years, a scaling process occurred and decreased the well outflow by app. 80%, as a consequence of well deterioration and reservoir depletion. Consequently (slower water movement), the water temperature increased by 1,5-2?C. Stabile values of the outflow and water quality parameters, registered during new monitoring, show an insignificant influence of the annual meteorological cycle on the outflow and quality regime. According to its chemical composition, the water is sodiumbicarbonate- fluoride, oligomineral and isothermal and a wide spectrum of applications is available. The limit for an efficient exploitation and application of the water is the current low outflow rate, so the drilling of new wells is recommended.

Deep learning for water quality prediction: the application of LSTM model to predict water quality in catchment scale

2021 ◽  
Author(s):  
Amir Sahraei ◽  
Lutz Breuer ◽  
Philipp Kraft ◽  
Tobias Houska
Keyword(s):  
Water Quality ◽  
Water Temperature ◽  
Mean Squared Error ◽  
Model Performance ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Bayesian Optimization ◽  
Optimization Approach ◽  
Quality Prediction ◽  
Water Quality Prediction

&lt;p&gt;The prediction of water quality is an efficient way for managing water resources and protecting ecosystems by providing an early warning against water quality deterioration. So far, the classical approach is to predict water quality by the utilization of complex process-based water quality models. However, these models are not easy to set up and require comprehensive input data. The local characteristics, detailed process understandings and eventually data from land users such as farmers are needed, to build up a valid model structure. Such constraints can end up in wrong scientific conclusions ranging from false alarms to unpredicted environmental pollution in practical water monitoring application. Long short-term memory (LSTM) algorithms are known to be able to overcome some of the typical constraints in hydrological model applications. However, their performance in water quality prediction has rarely been explored. In this study, we investigate the ability of a LSTM model to predict the complex, nonlinear behavior of water quality parameters in the Schwingbach Environmental Observatory (SEO), Germany.&amp;#160; We predict weekly nitrogen-nitrate concentrations, weekly stable isotopes of water concentrations (&amp;#948;&lt;sup&gt;18&lt;/sup&gt;O) and daily water temperature in six stream&amp;#8209; and six groundwater sources with different landuse and hillslope conditions. We use meteorological forcing data and catchment attributes as input variables. To ensure an efficient model performance, we employ a Bayesian optimization approach to optimize the hyperparameters of the LSTM. The model performance is evaluated by the Root Mean Squared Error (RMSE). Our LSTM is robust in capturing the dynamics of the water quality parameters over time. The RMSE for the LSTM performance ranges from 0.27 to 3.38 mg/l, from 0.069 to 0.27 &amp;#8240; and from 1.3 to 2.1 &amp;#176;C for nitrogen&amp;#8209;nitrate, &amp;#948;&lt;sup&gt;18&lt;/sup&gt;O and water temperature, respectively. We compare the RMSE with statistical parameters of data. Results confirm that the LSTM is a promising tool for early risk assessment of water quality, particularly in view that only a minimal set of catchment information is needed to gain robust results.&lt;/p&gt;

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