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Macrozoobentos Distribution as a Bioindicator of Water Quality in the Upstream of the Citarum River

Chazanah Nurul, Muntalif Barti Setiani, Rahmayani Rijki Aulia, Sudjono Priana

Journal of Ecological Engineering

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2020

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Vol. 21, nr 3

10--17

EN

This study aims to prove the type and abundance of macrozoobenthos are affected by the physico-chemical condition of the habitat so that it can be used as a bioindicator in assessing river water quality with a case study in the Upstream of Citarum River. The method used in this study consists of two stages, namely determining the status of river quality with pollution index and determining the components to see the relationship of the water quality parameters to the abundance of macrozoobenthos with principal component analysis. On the basis of these studies, the results were that at the location of the study status of the river quality is slightly polluted and mildly polluted. For the slightly polluted status Corbicula sp. was used as the dominant macrozoobenthos parameter with the parameters of dissolved oxygen, organic carbon and N-O in the clay-dominated sediments. In turn, for the river areas with mild pollution, Enallagma sp., Tubifex sp., and Chironomous sp. were used as bioindicators and they have a relationship with the parameters of nitrate, TSS, and P-total.

2

Wpływ zrzutu wód kopalnianych z odkrywki węgla brunatnego na jakość wód rzecznych

Staniszewski R., Jusik S.

Rocznik Ochrona Środowiska

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2013

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Tom 15, cz. 3

2652--2665

EN

Open cast mines can cause several modification of environment, as like decrease of groundwater level, soil modifications, noise, changes of river discharge and others. The year 2009 was the last year of mine waters discharge from Lubstów mine (Wielkopolska province) to Noteć River, which caused increase of river discharge for approximately 17%. The paper presents results of two years of studies on impact of mine waters from brown coal open-pit mine on lowland river. Most important water quality parameters like pH reaction, conductivity, sulphates and nutrients were analysed in all sites. Biological indication methods (MTR, IBMR, RI and others) based on aquatic plants (macrophytes, algae, mosses, liverworts) were used in studies to evaluate possible water quality changes below mine water discharge. Additionally, indices describing biological diversity (Shannon-Wiener W, Simpson D, uniformity J) were calculated using data from standard Mean Trophic Rank survey. In all three sites domination of several aquatic taxa was observed. Most frequent taxa were Elodea canadensis and Berula erecta. Other taxa often present in Noteć River were Spirodela plyrhiza, Sparganium emersum, Sparganium erectum, Mentha aquatica and Symphytum officinale. Results of studies were used for statistical analyses of Friedman ANOVA. Obtained data showed, that according to analysed water quality parameters as like, pH reaction, conductivity, total phosphorus, nitrates and others, changes of water quality were negligible. Results obtained using macrophyte indices for estimation of water trophy and ecological state confirmed results of chemical measurements. According to ANOVA, statistically significant relations were found for macrophyte biological diversity indices among surveyed river sites (χ2 = 8.40; p = 0.015). It was also confirmed by Kendall coefficient W = 0.84. The highest biological diversity was observed in site 1 situated above mine waters discharge and it was decreasing in sites 2 and 3. For the Shannon-Wiener (H’) index average coefficients were respectively 0.29 and 0.23, thus precise interpretation of these relation is difficult and to some extent could depend on other factors, eg. shading. Results of studies showed, that according to measured water quality parameters mine waters discharge from deep seated drainage did not caused significant changes of Noteć river water quality.

3

Using macrophytes as trophic state indicators in upland river waters: a case study of the Czarna Maleniecka River

Kopeć D., Dałkowski R., Urbaniak P.

Oceanological and Hydrobiological Studies

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2010

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Vol. 39, No.1

119-126

EN

The study was conducted on the upper reach of the Czarna Maleniecka River from Furmanów to the ford at Piekło. Nine sampling sites were selected along this 20-km section. Detailed studies of flora and the physicochemical water parameters were performed in the 2004- 2006 period. Data on macrophytes were collected with the Mean Trophic Rank (MTR) method. The results of physicochemical measurements were analyzed in reference to the water quality classification of the Polish Ministry of the Environment. Based on the results of these studies, the authors recommend adding two species, Utricularia intermedia and Glyceria fluitans, to the list of bioindicators.

4

Application of a fuzzy neural network for river water quality prediction

Skowrońska K. T., Skowroński Z. G., Biziuk M. K.

Chemia Analityczna

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2006

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Vol. 51, No. 3

365-375

EN

Monitoring and modelling of river water quality is one of the key elements in the global environmental monitoring policy and management. The control of complex and nonlinear systems, like rivers, is not an easy task. Usually, mathematical models are used for this purpose; however, sometimes these models require so much data that the response time is too long. An application of artificial intelligence (AI) helps to avoid disadvantages of mathematical models. This paper presents an application of the fuzzy neural network to the prediction of river water quality parameters. As an example, Cu concentration has been predicted.

PL

Monitoring i modelowanie zmian w jakości wód powierzchniowych stanowią jeden z kluczowych elementów monitoringu i zarządzania ochroną środowiska na skale globalną. Kontrolowanie tak złożonych i nieliniowych w swojej charakterystyce obiektów, jakimi są rzeki, jest trudnym zadaniem. Zazwyczaj do tego celu wykorzystuje się modele matematyczne, jednak czasem wymagają one bardzo dużej ilości danych lub czas oczekiwania na odpowiedź (uzyskania danych wyjściowych) jest zbyt długi. Zastosowanie technik sztucznej inteligencji pomaga uniknąć części wad modeli matematycznych. Ta praca przedstawia zastosowanie rozmytych sieci neuronowych do przewidywania parametrów charakteryzujących jakość wody rzecznej na przykładzie przewidywania stężenia miedzi.

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Environmetric Study of the Seasonal Patterns (1989-1998) in the Water Quality of the Struma River Basin, Bulgaria

Nikolov N., Mihailov G., Simeonov V., Mirinchev G.

Chemia i Inżynieria Ekologiczna

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2003

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Vol. 10, nr 8

763-771

EN

By the application of time-series analysis an estimation of the long-term water quality of the Struma river basin is performed. Several typical patterns of seasonal behaviour could be found reflecting the location of rural, urban, tributary and background sampling sites. Although it is quite difficult to specify a strict seasonal pattern along the Stroma river stream, some stable seasonality for the chemical indicators is obtained for the various sites like summer maximums caused probably by the lower water level for most of the sites, winter maximums for anthropogenic species at urban sites or at tributary sites due probably to the effect of waste waters, maximums due to agriculture activity etc. In this way a summary of the long-term water quality monitoring is obtained.

PL

Dokonano długoterminowego oznaczenia jakości wody w dorzeczu rzeki Struma poprzez zastosowanie analizy serii czasowych. Można znaleźć kilka typowych sezonowych zachowań odzwierciedlających lokalizacje miejsc pobierania próbek: na terenach wiejskich, miejskich, w pobliżu ujść dopływów oraz charakterystycznych dla tła. Mimo że dość trudne jest określenie ściśle sezonowych prawidłowości tych zmian wzdłuż biegu rzeki Struma, jednak udało się wykryć sezonowość wartości indykatorów chemicznych w różnych miejscach. Są to takie zmiany sezonowe, jak letnie maksima spowodowane prawdopodobnie niskim poziomem wody dla większości miejsc pobierania próbek, zimowe maksima o charakterze antropogennym charakterystycznym dla obszarów miejskich lub w pobliżu ujść dopływów będące wynikiem zrzutu wód ściekowych, maksima wynikające z działalności rolniczej itd. Otrzymano w ten sposób długoterminowe prawidłowości dotyczące danych monitoringu jakości wód.