scholarly journals Ribeira da Lage, a Stream to Protect

2020 ◽  
Vol 3 ◽  
Author(s):  
M. Tomaz ◽  
S. Vidal ◽  
A. Lopes ◽  
A. Espinha ◽  
C. Barata ◽  
...  
Keyword(s):  
Water Quality ◽  
Biological Monitoring ◽  
Research Work ◽  
Working Party ◽  
Sources Of Pollution ◽  
Subsequent Determination

The students started by identifying the most vulnerable ecosystems in the vicinity of the school. The stream Ribeira da Lage was identified and this ecosystem was characterized and the possible sources of pollution were surveyed. Macroinvertebrates were analyzed for subsequent determination of the BMWP (Biological Monitoring Working Party) index to assess water quality. After the research work, several contacts began with local entities and institutions (CMO, ITQB; Parish Council) to raise awareness and create measures to protect the assessed and monitored ecosystem.

scholarly journals Ribeira da Lage, a Stream to Protect

2020 ◽  
Vol 3 ◽  
Author(s):  
M. Tomaz ◽  
S. Vidal ◽  
A. Lopes ◽  
A. Espinha ◽  
C. Barata ◽  
...  
Keyword(s):  
Water Quality ◽  
Biological Monitoring ◽  
Research Work ◽  
Working Party ◽  
Sources Of Pollution ◽  
Subsequent Determination

The students started by identifying the most vulnerable ecosystems in the vicinity of the school. The stream Ribeira da Lage was identified and this ecosystem was characterized and the possible sources of pollution were surveyed. Macroinvertebrates were analyzed for subsequent determination of the BMWP (Biological Monitoring Working Party) index to assess water quality. After the research work, several contacts began with local entities and institutions (CMO, ITQB; Parish Council) to raise awareness and create measures to protect the assessed and monitored ecosystem.

scholarly journals PENETAPAN DAYA TAMPUNG BEBAN PENCEMARAN SUNGAI BADUNG DI DESA PEMOGAN

2016 ◽  
Vol 10 (2) ◽  
pp. 142
Author(s):  
Made Santiari ◽  
I Wayan Nuarsa ◽  
I Wayan Budiarsa Suyasa
Keyword(s):  
Water Quality ◽  
Point Source ◽  
Carrying Capacity ◽  
Load Capacity ◽  
Data Entry ◽  
Pollution Load ◽  
Sources Of Pollution ◽  
Pollutant Source

The water quality of Badung River in Pemogan village has exceeded the threshold limits.Therefore, It is needed to determinate the carrying capacity of Badung River. The determination of carrying capacity is very useful to control the disposal of waste into the Badung River. The objective of this study were to determine the sources of pollution, pollutant load and load capacity of Badung river at Pemogan village. Determination of pollutant source done with looked for land use and types of activities along the Badung river Pemogan village followed by field inspections. The pollution load was determined by multiplying the concentration of water quality and flow rate, while the carrying capacity was determined with the help of the program Qual2Kw ver 5.1. Determination of load capacity with Qualk2Kw ver 5.1 has several step such as data collect, the data entry process, calibration, verification and simulation according to the scenario. The result of this study showed sources of pollution that cause a decrease the water quality of Badung river in Pemogan village were non point source (agriculture and settlements) and point source (flow from upstream). The pollution load that flow into the Badung river in Pemogan village for BOD, COD and TSS respectively 419,97 kg/ day; 865,66 kg/day dan 160,70 kg/day. Load capacity of Badung river for COD and TSS were 1686.53 kg/day dan 4743.36 kg / day, Meanwhile, the load capacity of Badung River for BOD has overlimits.

scholarly journals Biological Monitoring Using Macroinvertebrates as Bioindicators of Water Quality of Maroaga Stream in the Maroaga Cave System, Presidente Figueiredo, Amazon, Brazil

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Christiane Brito Uherek ◽  
Fernando Bernardo Pinto Gouveia
Keyword(s):  
Water Quality ◽  
Biological Monitoring ◽  
Anthropogenic Activities ◽  
Working Party ◽  
Order Stream ◽  
Score System ◽  
Cave System ◽  
Environmental Protection Area ◽  
Chemical Conditions ◽  
Physical And Chemical

Aquatic environments are being modified by anthropogenic activities regarding their biological, physical, and chemical conditions; even pristine aquatic ecosystems can be threatened. This study focused on the biological monitoring of Maroaga Stream—a first order stream located in an Environmental Protection Area in the Amazon using the Biological Monitoring Working Party (BMWP) Score System. The BMWP Score System revealed that the Maroaga Stream was a Class I stream (score of 138 points), indicating clean or not significantly altered water quality. The results suggest the adequate environmental conditions and ecological responses of the Maroaga Stream.

scholarly journals ‘River Water DO Mechanics & New DO-Sag Equation’

2019 ◽  
Vol 8 (3) ◽  
pp. 8805-8809
Keyword(s):  
Water Quality ◽  
River Water ◽  
Exponential Function ◽  
Research Work ◽  
Water Quality Assessment ◽  
Field Work ◽  
Quality Model ◽  
New Equation ◽  
River Velocity

DO modeling by Streeter Phelps equation [1] is most popular method to determine the water quality of a River. To compute DO by Streeter Phelps equation River coefficients k1 and k2 (de-oxidation and re-oxygenation) are required. Determination of these coefficients is tedious because it requires field observation of river velocity and depth over a long period of time at river site. To avoid maximum field work in calculating DO of River water DO Modeling approach is developed by combining Lab analysis of water samples DO with field data, e.g. river velocity and depth. Streeter Phelps (1925) developed the 1st important water quality model describing the BOD-DO relationship in a stream. In their pioneering work the simplest system was considered, in which biodegradable waste is discharged to the stream and consumes oxygen, atmospheric reaeration being the only source of oxygen. The model is based on complicated solution of differential equation for above process. The equation is derived assuming River coefficients k1 and k2 as exponential function of time variation. The authors have simplified the derivation of DO-Sag equation [4] by replacing the exponential function with a quadratic polynomial. To explain the use of new equation, authors have defined the geometry of DO curve known as ‘River Water DO Mechanics’. Also in this paper, new equation is applied to make ‘Shivnath River water DO Model’ with data taken by the author as part of his Ph. D. research work. The results justify the acceptance of new modified equation for River Water Quality Assessment.

scholarly journals Comparing two biological indexes using benthic macroinvertebrates: positive and negative aspects of water quality assessment

2016 ◽  
Vol 28 (0) ◽  
Author(s):  
Vinicius Moraes Rodrigues ◽  
Eliane Pintor de Arruda ◽  
André Cordeiro Alves dos Santos ◽  
Monica Jones Costa
Keyword(s):  
Water Quality ◽  
Benthic Macroinvertebrates ◽  
Working Party ◽  
Water Quality Assessment ◽  
Winter Period ◽  
Advantages And Disadvantages ◽  
Quality Of Water ◽  
P Index ◽  
Sample Points

Abstract: Aim The aim of the present study, was to apply two biological indexes based on benthic macroinvertebrates (BMWP and ICB RES-P) using as model the Itupararanga Reservoir to know what the advantages and disadvantages of the application of each index in that environment. Methods The methodology consisted on three stages: 1) macroinvertebrates sampling and determination of limnological variables in situ, and sorting of the organisms in laboratory, 2) taxonomic identification of organisms and 3) determination of the saprobic degree for the collection sites and effectiveness of the application of the BMWP (Biological Monitoring Working Party score system) index and the Benthic Community Index created by CETESB (Environmental Sanitary Company of State of São Paulo) for deep regions (ICB RES-P index). Results The study was performed over two periods (spring/summer and autumn/winter), and 8,841 organisms were sampled and divided in 17 families. The Chaoboridae (genus Chaoborus), Chironomidae (subfamilies Chironominae and Tanypodinae) and Tubificidae families had the most abundant taxa. The saprobic degree of the Itupararanga reservoir region resulted in the general classification of the reservoir as β-α mesasaprobic (βms- αms), considered critical due to its organic charge content. The BMWP index was adapted to the sample points and the scores subsequently obtained ranked the reservoir as category V, representing very poor water quality. The ICB RES-P index classified the sample points in the spring/summer period as having regular water quality, and the autumn/winter period as having good water quality. Conclusions From previous findings, it can be concluded that further study and refinement of the components of both indexes are required in order to effectively assess the quality of water in reservoirs.

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