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 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 Assessment of the abundance and species composition of Phytoplankton of Moiur river, Khulna

2015 ◽  
Vol 21 ◽  
pp. 27-34 ◽  
Author(s):  
Md Lifat Rahi ◽  
Sarower E Mahfuj ◽  
Sk Shahinur Islam ◽  
S Saiful Islam ◽  
Wasim Sabbir
Keyword(s):  
Water Quality ◽  
Species Composition ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Polluted Water ◽  
Optimum Level ◽  
Phytoplankton Abundance ◽  
The Family ◽  
Total Phytoplankton ◽  
Positive Correlations

Context: Phytoplanktonic community structure in an aquatic body embodies the energy transfer through this phase and indicates the tropic status. Objectives: The present study was conducted to assess the phytoplankton abundance and species composition of Mouri River, Khulna, Bangladesh. Materials and Methods: Water samples were collected from six different stations once in a week for a period of 6 months (February- July) 2010. Results: In total 48 different species of 23 genus and 4 families were identified. Phytoplankton abundance varied from 805 to 1788 individuals/L in different stations. The highest abundance was observed for the family chlorophyceae that constituted 27-50.56% of the total phytoplankton biomass throughout the river. Highest number of phytoplankton species (22) was also recorded for the family chlorophyceae. The most diverse genus was Navicula (6). Some aspects of the water quality parameters were measured by regression analysis and significant correlations were also observed between water quality parameters and phytoplankton abundance. Water temperature, pH, DO, Free CO2, alkalinity, hardness, calcium and magnesium showed positive correlations with total phytoplankton abundance where as transparency, TDS, TSS, sulfate phosphate and nitrite showed negative correlations. Conclusion: In most of the cases, phytoplankton abundance and water quality parameters showed greater deviation from the optimum level. However, the results of the present experiment confirmed the polluted water of the river. DOI: http://dx.doi.org/10.3329/jbs.v21i0.22516 J. bio-sci. 21: 27-34, 2013

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).

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 An Appraisal of Groundwater Contamination : A Case Study of Shallow Wells In Agbowo Community, Southwestern Nigeria

2019 ◽  
pp. 104-115
Author(s):  
Abudulawal L. ◽  
Apanpa K. A.
Keyword(s):  
Water Quality ◽  
Total Dissolved Solids ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
World Health ◽  
Dissolved Solids ◽  
Southwestern Nigeria ◽  
Permissible Limits ◽  
Physico Chemical ◽  
Shallow Wells

Abundant as it may seem in Nigeria, access to clean and potable water is a great challenge. Hence the reason for determination of the physico-chemical properties of the groundwater in Agbowo community in Ibadan, Oyo state Southwestern Nigeria for domestic uses. Water samples collected from thirty-four (34) shallow wells with varying depths were subjected to chemical analysis. The water quality parameters were analyzed in accordance to standard methods. The groundwater analysis reviewed includes pH, electrical conductivity, total dissolved solids (TDS), others include Ca<sup>2+</sup>, Mg<sup>2+</sup>, K<sup>+</sup> Na<sup>+</sup>, Fe<sup>2+</sup>, NO<sub>3</sub>, Cl<sup>-</sup> SO<sub>4</sub><sup>2-</sup> and HCO<sub>3</sub><sup>- </sup>The results indicated that the parameters analyzed have some falling within the limits and some above the maximum permissible limits in accordance to Nigeria Industrial Standard (NIS) and World Health Organization (WHO) guidelines for drinking water. In general, the data revealed that maxima and minima concentrations of the priority physico-chemical water quality parameters examined in the thirty-four (34) water points were mostly within the Target Water Quality Range (TWQR) for domestic use with little exceptions at some points. However, high nitrate concentrations and Total Dissolved Solids (TDS) above the permissible limits in some of the well water sampled are causes for serious concern. Poor construction, lack of maintenance, proximity to sewage tank and stream, as well as indiscriminate dumping of refuse are suggested as the major causes of this development. The overall implication of this observation call for sustenance and improved water resource management strategy for the area in order to prevent the deterioration of the water sources quality, which may pose associated health risks and environmental hazards.

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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