Pre-treating algae-laden raw water by silver carp during Microcystis-dominated and non-Microcystis-dominated periods

2012 ◽  
Vol 65 (8) ◽  
pp. 1448-1453 ◽  
Author(s):  
Hua Ma ◽  
Fuyi Cui ◽  
Zhiquan Liu ◽  
Zhiwei Zhao
Keyword(s):  
Chlorophyll A ◽  
Green Algae ◽  
Total Phosphorus ◽  
Phytoplankton Community ◽  
Phosphorus Content ◽  
Silver Carp ◽  
Nutrient Level ◽  
Species Structure ◽  
Raw Water ◽  
Filter Feeding

Performance of pre-treating algae-laden raw water by silver carp during a non-Microcystis-dominated period (period I) and a Microcystis-dominated period (period II) was investigated in terms of algae cell concentration, total phosphorus content, chlorophyll a and phytoplankton species structure. During period I the ineffective filter-feeding for small green algae resulted in the increase of small single algae, which led to the negative removal of chlorophyll a, and when the biomass was higher, the negative was more significant. However, due to the effective filter-feeding of silver carp for Microcystis flos-aquae, the average removal efficiency exceeded 50% at all stocking biomass levels (20–120 g/m3) used in experiments during period II. Total phosphorus removal efficiencies could exceed 50% at silver carp biomass stocking levels of 60–80 g/m3 during both period I and period II. The experimental results indicated that silver carp stocking contributed to the removal of colony-forming cyanobacteria, but led to the increase of single-cell algae (mainly green algae and diatoms) during both period I and period II. The initial phytoplankton community structure and the control of nutrient level were important factors in the choice of silver carp stocking biomass when used to purify algae-loaded water.

scholarly journals Synergistic effects between omnivorous filter-feeding fish and nutrient enrichment on algal biomass

2015 ◽  
Vol 27 (2) ◽  
pp. 223-227 ◽  
Author(s):  
Leonardo Henrique Teixeira ◽  
José Luiz Attayde
Keyword(s):  
Chlorophyll A ◽  
Total Nitrogen ◽  
Total Phosphorus ◽  
Nutrient Enrichment ◽  
Phytoplankton Biomass ◽  
Nile Tilapia ◽  
Nutrient Addition ◽  
Northeastern Brazil ◽  
Filter Feeding ◽  
Positive Effect

Aim: The Nile tilapia - Oreochromis niloticus(Linnaeus 1758) - is an exotic omnivorous filter-feeding fish that has been stocked for three decades in man-made lakes of Northeastern Brazil. Most experiments manipulating omnivorous filter-feeding fish in eutrophic lakes and reservoirs shows that their presence tends to increase phytoplankton biomass and primary production. In this study, we tested the hypothesis that tilapia interact synergistically with nutrient enrichment so that the effects of omnivorous fish on phytoplankton biomass becomes more intense with increasing nutrient concentration.MethodsA field experiment with a 2×3 factorial design was performed during four weeks in twenty-four mesocosms (0.25 m3) to which six treatments were randomly allocated: fingerling addition (F), juvenile tilapia addition (J), nutrient addition (NP), nutrient and fingerling addition (NPF), nutrient and juvenile tilapia addition (NPJ) and a control treatment with no tilapia or nutrients addition (C). A two-way repeated measures ANOVA was done to test for time (t), tilapia and nutrients effects and their interaction on total phosphorus, total nitrogen and chlorophyll-a concentrations.ResultsThe results showed a positive effect of nutrient addition on total phosphorus, total nitrogen and chlorophyll-a concentrations and a positive effect of tilapia on the concentration of chlorophyll-a. As expected, we found a synergistic interaction between the positive effect of Nile tilapia and nutrient enrichment on phytoplankton biomass.ConclusionsThe above results suggest that controlling tilapia abundance through fisheries management is a potential tool to improve water quality and mitigate the effects of lake and reservoir eutrophication.

scholarly journals KONDISI PERAIRAN SUNGAI MOROSARI DEMAK PADA LOKASI YANG BERBEDA DITINJAU DARI KANDUNGAN KLOROFIL-a, NITRAT, FOSFAT, DAN FITOPLANKTON

2016 ◽  
Vol 5 (4) ◽  
pp. 233-241 ◽  
Author(s):  
Rina Mariana ◽  
Siti Rudiyanti ◽  
Boedi Hendrarto
Keyword(s):  
Chlorophyll A ◽  
Industrial Waste ◽  
Phytoplankton Community ◽  
Phosphorus Content ◽  
Nitrate Content ◽  
Residential Areas ◽  
Phytoplankton Diversity ◽  
River Waters ◽  
Fishing Boat ◽  
Significant Difference

ABSTRAK Sungai Morosari berada di Kecamatan Sayung, Kabupaten Demak. Perairan ini digunakan untuk pembuangan limbah domestik maupun industri, jalur lalu lintas perahu nelayan, kawasan wisata, dan kegiatan perikanan. Hal ini diduga mempengaruhi kualitas perairan. Penelitian dilakukan pada bulan April-Mei 2014, bertujuan untuk mengetahui kondisi perairan Sungai Morosari berdasarkan kandungan klorofil-a, nitrat, fosfat, dan struktur komunitas fitoplankton. Variabel pendukung penelitian antara lain temperatur, arus, kedalaman, kecerahan,  pH, salinitas, dan oksigen terlarut. Pengambilan sampel pada penelitian ini ditentukan empat stasiun dengan tiga kali pengulangan. Analisis data yang digunakan untuk menggunakan analisis kluster dan analisis non parametrik Kruskal-Wallis. Hasil penelitian menunjukkan terdapat perbedaan yang nyata pada kandungan klorofil-a dan fosfat tiap stasiun, sedangkan pada kandungan nitrat tidak terdapat perbedaan yang nyata.  Kemiripan tertinggi berdasarkan komunitas fitoplankton terletak pada daerah yang didominasi pemukiman penduduk  dan daerah lalu lintas perahu nelayan, sedangkan kemiripan terendah yaitu pada daerah pertemuan pembuangan limbah industri. Kelimpahan fitoplankton termasuk dalam kategori kelimpahan yang sedang, indeks keanekaragaman dan indeks keseragaman fitoplankton rendah. Berdasarkan kandungan klorofil-a dan nitrat perairan Sungai Morosari termasuk ke dalam perairan oligotrofik, sedangkan berdasarkan kandungan fosfat termasuk ke dalam perairan mesotrofik dan eutrofik. Kata Kunci : Klorofil-a; Nitrat; Fosfat; Fitoplankton; Sungai Morosari ABSTRACT Morosari river located in District Sayung, Demak is used for the disposal of domestic and industrial waste, traffic, fishing boats, tourist areas and fisheries activities. And may affect the water quality. The study was conducted in April-May 2014, aimed to determine the condition of the river by chlorophyll-a, nitrate, phosphate, and phytoplankton community structure at different locations. Other variables included temperature, currents, depth, transparency, pH, salinity, and dissolved oxygen. This study used four stations with three replications. Analysis of the data used cluster analysis and the Kruskal-Wallis non parametric analysis. The results showed a significant difference in the content of chlorophyll-a and phosphate each station, while the nitrate content there was no significant difference. The highest similarity based on the phytoplankton community was between  residential areas and traffic areas fishing boat, while the lowest is similarity was in industrial waste disposal area. The abundance of phytoplankton included in the category of moderate abundance, phytoplankton diversity and evenness index were low. Based on the content of chlorophyll-a and nitrate Morosari river waters belong to the oligotrophic waters, while based on the phosphorus content included into the mesotrophic waters. Keywords : Chlorophyll-a; Nitrate; Phosphate; Phytoplankton; Morosari River

Relationship between Water Quality and Phytoplankton Biomass in Microcystis-Laden Raw Water under Silver Carp Filter-Feeding

2012 ◽  
Vol 518-523 ◽  
pp. 3727-3730
Author(s):  
Hua Ma ◽  
Fu Yi Cui ◽  
Zhi Wei Zhao ◽  
Zhi Quan Liu ◽  
Dong Mei Liu
Keyword(s):  
Water Quality ◽  
Green Algae ◽  
Linear Regression Analysis ◽  
Silver Carp ◽  
Raw Water ◽  
Algae Biomass ◽  
Microcystis Blooms ◽  
Phytoplankton Communities ◽  
Positive Correlations ◽  
Two Parameters

Silver carp were stocked in a pre-sedimentation pond in front of conventional water treatment processes in order to control Microcystis blooms in raw water. Silver carp effectively reduced the Microcystis flos-aquae concentrations, but green algae concentrations increased due to the ineffective filtration of silver carp for them. Water quality variations based on the effect of silver carp stocking on the two major phytoplankton communities (Microcystis and green algae) were evaluated by to investigate the relationship between water quality and phytoplankton cell concentrations in influent and effluent during Microcystis blooms period. Linear regression analysis indicated that the dominant species Microcystis governed the variation of turbidity and CODMn, and its concentration showed positive correlations with the two parameters. Meanwhile, the increase of green algae biomass led to the increase of pH and Chlorophyll a content, and showed obvious positive correlations with the two parameters in effluent.

APLIKASI CITRA LANDSAT 8 OLI UNTUK IDENTIFIKASI STATUS TROFIK WADUK GAJAH MUNGKUR WONOGIRI, JAWA TENGAH

2017 ◽  
Vol 19 (2) ◽  
pp. 113
Author(s):  
Kusuma Wardani Laksitaningrum ◽  
Wirastuti Widyatmanti
Keyword(s):  
Chlorophyll A ◽  
Total Phosphorus ◽  
Trophic State ◽  
Water Clarity ◽  
Coefficient Of Determination ◽  
Physical Factors ◽  
Landsat 8 ◽  
Trophic State Index ◽  
Landsat 8 Oli ◽  
State Index

<p align="center"><strong>ABSTRAK</strong></p><p class="abstrak">Waduk Gajah Mungkur (WGM) adalah bendungan buatan yang memiliki luas genangan maksimum 8800 ha, terletak di Desa Pokoh Kidul, Kecamatan Wonogiri, Kabupaten Wonogiri. Kondisi perairan WGM dipengaruhi oleh faktor klimatologis, fisik, dan aktivitas manusia yang dapat menyumbang nutrisi sehingga mempengaruhi status trofiknya. Tujuan dari penelitian ini adalah mengkaji kemampuan citra Landsat 8 OLI untuk memperoleh parameter-parameter yang digunakan untuk menilai status trofik, menentukan dan memetakan status trofik yang diperoleh dari citra Landsat 8 OLI, dan mengevaluasi hasil pemetaan dan manfaat citra penginderaan jauh untuk identifikasi status trofik WGM. Identifikasi status trofik dilakukan berdasarkan metode <em>Trophic State Index</em> (TSI) Carlson (1997) menggunakan tiga parameter yaitu kejernihan air, total fosfor, dan klorofil-a. Model yang diperoleh berdasar pada rumus empiris dari hasil uji regresi antara pengukuran di lapangan dan nilai piksel di citra Landsat 8 OLI. Model dipilih berdasarkan nilai koefisien determinasi (R<sup>2</sup>) tertinggi. Hasil penelitian merepresentasikan bahwa nilai R<sup>2</sup> kejernihan air sebesar 0,813, total fosfor sebesar 0,268, dan klorofil-a sebesar 0,584. Apabila nilai R<sup>2 </sup>mendekati 1, maka semakin baik model regresi dapat menjelaskan suatu parameter status trofik. Berdasarkan hasil kalkulasi diperoleh distribusi yang terdiri dari kelas eutrofik ringan, eutrofik sedang, dan eutrofik berat yaitu pada rentang nilai indeks 50,051 – 80,180. Distribusi terbesar adalah eutrofik sedang. Hal tersebut menunjukkan tingkat kesuburan perairan yang tinggi dan dapat membahayakan makhluk hidup lain.</p><p><strong>Kata kunci: </strong>Waduk Gajah Mungkur, citra Landsat 8 OLI, regresi, TSI, status trofik</p><p class="judulABS"><strong>ABSTRACT</strong></p><p class="Abstrakeng">Gajah Mungkur Reservoir is an artificial dam that has a maximum inundated areas of 8800 ha, located in Pokoh Kidul Village, Wonogiri Regency. The reservoir’s water conditions are affected by climatological and physical factors, as well as human activities that can contribute to nutrients that affect its trophic state. This study aimed to assess the Landsat 8 OLI capabilities to obtain parameters that are used to determine its trophic state, identifying and mapping the trophic state based on parameters derived from Landsat 8 OLI, and evaluating the results of the mapping and the benefits of remote sensing imagery for identification of its trophic state. Identification of trophic state is based on Trophic State Index (TSI) Carlson (1997), which uses three parameters there are water clarity, total phosphorus, and chlorophyll-a. The model is based on an empirical formula of regression between measurements in the field and the pixel values in Landsat 8 OLI. Model is selected on the highest value towards coefficient of determination (R<sup>2</sup>). The results represented that R<sup>2</sup> of water clarity is 0.813, total phosphorus is 0.268, and chlorophyll-a is 0.584. If R<sup>2</sup> close to 1, regression model will describe the parameters of the trophic state better. Based on the calculation the distribution consists of mild eutrophic, moderate eutrophic, and heavy eutrophic that has index values from 50.051 to 80.18. The most distribution is moderate eutrophication, and it showed the high level of trophic state and may harm other living beings.</p><p><strong><em>Keywords: </em></strong><em>Gajah Mungkur Reservoir, </em><em>L</em><em>andsat 8 OLI satellite imagery, regression, TSI, trophic state</em></p>

scholarly journals Effect of red algal bloom on growth and production of carps

Our Nature ◽  
2018 ◽  
Vol 16 (1) ◽  
pp. 48-54
Author(s):  
Ram Bhajan Mandal ◽  
Sunila Rai ◽  
Madhav Kumar Shrestha ◽  
Dilip Kumar Jha ◽  
Narayan Prasad Pandit
Keyword(s):  
Water Quality ◽  
Body Weight ◽  
Chlorophyll A ◽  
Total Nitrogen ◽  
Total Phosphorus ◽  
Algal Bloom ◽  
Total Dissolved Solids ◽  
Dissolved Solids ◽  
Aquaculture Farm ◽  
Red Algal

An experiment was carried to assess the effect of red algal bloom on growth and production of carp, water quality and profit from carp for 120 days at Aquaculture Farm of Agriculture and Forestry University, Chitwan. The experiment included two treatments: carp polyculture in non-red pond and carp polyculture in red pond with algal bloom each with three replicates. Carp fingerlings were stocked at 1 fish/m2 and fed with pellet containing 24% CP at 3% body weight. Net yield of rohu was found significantly higher (p<0.05) in non-red ponds (0.38±0.01 t ha-1) than red ponds (0.24±0.05 t ha-1). Survival of rohu (84.9±1.4%), bighead (95.2±2.0%) and mrigal (88.1±14.4%) were also significantly higher (p<0.05) in non-red ponds than red ponds. Red algal bloom affected DO, nitrate and chlorophyll-a, nitrite, total nitrogen, total phosphorus, total dissolved solids and conductivity. However, overall carp production and profit from carp remained unaffected.

Differences between Nearshore and Offshore Phytoplankton Communities in Lake Ontario

1987 ◽  
Vol 44 (12) ◽  
pp. 2155-2163 ◽  
Author(s):  
I. M. Gray
Keyword(s):  
Chlorophyll A ◽  
Phytoplankton Biomass ◽  
Algal Biomass ◽  
Phytoplankton Community ◽  
Seasonal Pattern ◽  
Principal Component ◽  
Lake Ontario ◽  
Dominant Group ◽  
Phytoplankton Communities ◽  
Eutrophic Species

Differences between nearshore and offshore phytoplankton biomass and composition were evident in Lake Ontario in 1982. Phytoplankton biomass was characterized by multiple peaks which ranged over three orders of magnitude. Perhaps as a consequence of the three times higher current velocities at the northshore station, phytoplankton biomass ranged from 0.09 to 9.00 g∙m−3 compared with 0.10 to 2.40 g∙m−3 for the midlake station. Bacillariophyceae was the dominant group at the northshore station until September when Cyanophyta contributed most to the biomass (83%). Although Bacillariophyceae was the principal component of the spring phytoplankton community at the midlake station, phytoflagellates (49%) and Chlorophyceae (25%) were responsible for summer biomass, with the Chlorophyceae expanding to 80% in the fall. The seasonal pattern of epilimnetic chlorophyll a correlated with temperature. While chlorophyll a concentrations were similar to values from 1970 and 1972, algal biomass had declined and a number of eutrophic species (Melosira binderana, Stephanodiscus tenuis, S. hantzschii var. pusilla, and S. alpinus) previously found were absent in 1982.

scholarly journals Hyperspectral Data and Machine Learning for Estimating CDOM, Chlorophyll a, Diatoms, Green Algae and Turbidity

2018 ◽  
Vol 15 (9) ◽  
pp. 1881 ◽  
Author(s):  
Sina Keller ◽  
Philipp Maier ◽  
Felix Riese ◽  
Stefan Norra ◽  
Andreas Holbach ◽  
...  
Keyword(s):  
Machine Learning ◽  
Water Quality ◽  
Chlorophyll A ◽  
Green Algae ◽  
Hyperspectral Data ◽  
Coefficient Of Determination ◽  
Inland Waters ◽  
Learning Approaches ◽  
River Elbe ◽  
Regression Framework

Inland waters are of great importance for scientists as well as authorities since they are essential ecosystems and well known for their biodiversity. When monitoring their respective water quality, in situ measurements of water quality parameters are spatially limited, costly and time-consuming. In this paper, we propose a combination of hyperspectral data and machine learning methods to estimate and therefore to monitor different parameters for water quality. In contrast to commonly-applied techniques such as band ratios, this approach is data-driven and does not rely on any domain knowledge. We focus on CDOM, chlorophyll a and turbidity as well as the concentrations of the two algae types, diatoms and green algae. In order to investigate the potential of our proposal, we rely on measured data, which we sampled with three different sensors on the river Elbe in Germany from 24 June–12 July 2017. The measurement setup with two probe sensors and a hyperspectral sensor is described in detail. To estimate the five mentioned variables, we present an appropriate regression framework involving ten machine learning models and two preprocessing methods. This allows the regression performance of each model and variable to be evaluated. The best performing model for each variable results in a coefficient of determination R 2 in the range of 89.9% to 94.6%. That clearly reveals the potential of the machine learning approaches with hyperspectral data. In further investigations, we focus on the generalization of the regression framework to prepare its application to different types of inland waters.

Sign in / Sign up

Export Citation Format

Share Document