scholarly journals KETAHANAN IKAN TAMBAKAN (Helostoma temminkii) TERHADAP BEBERAPA PARAMETER KUALITAS AIR DALAM LINGKUNGAN BUDIDAYA

2018 ◽  
Vol 12 (3) ◽  
pp. 241
Author(s):  
Otong Zenal Arifin ◽  
Vitas Atmadi Prakoso ◽  
Brata Pantjara
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Growth And Survival ◽  
2Nd Generation ◽  
Freshwater Aquaculture ◽  
Experimental Fish ◽  
Negative Effect ◽  
Range Of Values

Ikan tambakan (Helostoma temminkii) adalah satu dari beberapa jenis spesies ikan air tawar yang ekonomis di Indonesia. Komoditas ini cukup digemari di beberapa wilayah Jawa, Sumatera, dan Kalimantan. Oleh karena itu, prospek pengembangan budidaya ikan tambakan merupakan hal yang penting. Tulisan ini bertujuan untuk mengetahui respons ketahanan ikan tambakan terhadap paparan beberapa parameter kualitas air. Seluruh kegiatan pengujian dilakukan di Balai Riset Perikanan Budidaya Air Tawar dan Penyuluhan Perikanan, Bogor. Ikan yang digunakan pada percobaan ini adalah ikan tambakan generasi kedua hasil domestikasi (panjang standar: 7,5 ± 0,28 cm; bobot: 15,2 ± 2,11 g). Uji toleransi yang dilakukan meliputi ketahanan terhadap salinitas, pH, suhu, dan oksigen terlarut. Jumlah ikan yang diuji untuk masing-masing parameter kualitas air yaitu 30 ekor pada perlakuan salinitas, pH, dan suhu, serta 40 ekor untuk pengujian toleransi terhadap oksigen terlarut dengan tiga kali ulangan pada masing-masing perlakuan. Berdasarkan data penelitian, ikan tambakan dapat bertahan hidup dan beraktivitas secara normal pada kisaran salinitas £ 10 ppt, pH 5-9, suhu 20-35oC, dan kandungan oksigen terlarut > 3 mg/L. Kisaran nilai pada parameter kualitas air di luar batas toleransi dapat berpengaruh negatif pada pertumbuhan dan sintasan ikan tambakan.Kissing gouramy (Helostoma temminkii) is one of valued freshwater fish in Indonesia. This species is quite popular in some areas of Java, Sumatra, and Kalimantan. Therefore, the development of aquaculture for this species is essential. This paper was intended to determine the response of fish resistance to the exposure of several water quality parameters. All of the experiments were carried out at the Institute for Freshwater Aquaculture Research and Fisheries Extension, Bogor. The experimental fish used in the experiment were domesticated kissing gouramy (2nd generation) with standard length of 7.5 ± 0.28 cm and total weight of 15.2 ± 2.11 g. The tests, on the resistance to salinity, pH, temperature, and dissolved oxygen. For each treatment, 30 fish were challenged with salinity, pH, and temperature treatments, and 40 fish for oxygen tolerance treatment. All treatments were conducted with three replications. Based on the results, kissing gouramy could survive and behave normally in the range of £ 10 ppt salinity, pH 5-9, temperature 20-35°C, and dissolved oxygen content of more than 3 mg/L. The range of values on water quality parameters which exceeded the tolerance limit could result in the negative effect on the growth and survival of kissing gouramy.

scholarly journals Cladoceran abundance in relation to water quality parameters of Chakki Talab, Bodhan, Telangana

2018 ◽  
Vol 8 (01) ◽  
Author(s):  
Vasudha Lingampally ◽  
V.R. Solanki ◽  
D. L. Anuradha ◽  
Sabita Raja
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Oxygen Demand ◽  
Total Dissolved Solids ◽  
Quality Parameters ◽  
Biological Oxygen Demand ◽  
Water Quality Parameters ◽  
Total Alkalinity ◽  
Total Hardness ◽  
One Year

In the present study an attempt has been made to evaluate water quality and related density of Cladocerans for a period of one year, October 2015 to September 2016. Water quality parameters such as temperature, PH, total dissolved solids, dissolved oxygen, biological oxygen demand, total alkalinity, total hardness, chlorides, phosphates, and nitrates are presented here to relate with the abundance of Cladocerans. The Cladoceran abundance reflects the eutrophic nature of the Chakki talab.

scholarly journals Budidaya ikan mas (Cyprinus carpio) sistem akuaponik dengan padat penebaran berbeda

2019 ◽  
Vol 7 (2) ◽  
Author(s):  
Darwis Darwis ◽  
Joppy D. Mudeng ◽  
Sammy N.J. Londong
Keyword(s):  
Water Quality ◽  
Cyprinus Carpio ◽  
Stocking Density ◽  
Quality Parameters ◽  
Water Volume ◽  
Daily Growth ◽  
Growth And Survival ◽  
Experimental Fish ◽  
The Difference

This research aimed to determine the stocking density that support the best growth and survival rate of carp cultivated in aquaponic systems, and to study the water quality of carp culture with different stocking densities in aquaponic systems. The study used 12 aquaria measuring 40x40x40 cm each (water volume of 50 liters). The experimental fish are carp (Cyprinus carpio) weighing in average of 3.5 g/individual.  The fish were cultivated with different stocking densities as treatment, including A = 4; B = 7; C = 10 and D = 13 individuals/aquarium.  The fish were fed with pellet at 5%/body weight/day with a feeding frequency of two times a day. The study was conducted for 4 weeks. Data consisting of daily growth, survival and water quality parameters (temperature, pH, dissolved oxygen, ammonia, nitrite and nitrate) were measured once a week. The data obtained were analyzed by ANOVA. The results of the study showed that the difference in stocking density had no significant effect on the growth and survival of carp.  Water quality was in a reasonable range to support the growth and survival of carp cultivated with aquaponic systems.Keywords: cultivation, carp, aquaponics, stocking density, growth

scholarly journals Potensi budidaya ikan di Waduk Embung Klamalu Kabupaten Sorong Provinsi Papua Barat: Kajian kualitas fisika kimia air

2013 ◽  
Vol 1 (3) ◽  
Author(s):  
Agustina Frasawi ◽  
Robert J Rompas ◽  
Juliaan Ch. Watung
Keyword(s):  
Carbon Dioxide ◽  
Water Quality ◽  
Dissolved Oxygen ◽  
Good Condition ◽  
Fish Farming ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Total Alkalinity ◽  
Physical Chemical ◽  
Papua Barat

The objective of this research was to measure and analyze the water quality parameters including temperature, brightness, pH, dissolved oxygen, total alkalinity, carbon dioxide and BOD in reservoir Embung Klamalu Sorong regency, and to know the factors that affected the water quality of Embung Klamalu. Measurement of water quality parameters was done in situ for temperature, brightness, pH and in laboratory for dissolved oxygen, total alkalinity, carbon dioxide, and BOD. The results showed the temperature at the five observation stations ranged from 26.2 to 29.8 0C, brightness 38 to 46 cm, pH 7.20 to 8.48 mg /L, dissolved oxygen from 7.20 to 8.48 mg / L, alkalinity 100 to 150 mg /L, carbon dioxide from 25.90 to 28.95 mg / L, BOD from 0.20 to 0.38. Refers to the standards of water quality according to the PP. 82, 2001, it could be concluded that water physical-chemical qualities in fish farming locations in the Village Klamalu were still in good condition. Keywords: Water physical-chemical quality, aquaculture, waduk Embung Klamalu

scholarly journals Use of Artificial Neural Networks and Multiple Linear Regression Model for the Prediction of Dissolved Oxygen in Rivers: Case Study of Hydrographic Basin of River Nyando, Kenya

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-23 ◽  
Author(s):  
Yashon O. Ouma ◽  
Clinton O. Okuku ◽  
Evalyne N. Njau
Keyword(s):  
Water Quality ◽  
Linear Regression ◽  
Dissolved Oxygen ◽  
Multiple Linear Regression ◽  
Pearson Correlation ◽  
Multiple Linear Regression Model ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Monitoring

The process of predicting water quality over a catchment area is complex due to the inherently nonlinear interactions between the water quality parameters and their temporal and spatial variability. The empirical, conceptual, and physical distributed models for the simulation of hydrological interactions may not adequately represent the nonlinear dynamics in the process of water quality prediction, especially in watersheds with scarce water quality monitoring networks. To overcome the lack of data in water quality monitoring and prediction, this paper presents an approach based on the feedforward neural network (FNN) model for the simulation and prediction of dissolved oxygen (DO) in the Nyando River basin in Kenya. To understand the influence of the contributing factors to the DO variations, the model considered the inputs from the available water quality parameters (WQPs) including discharge, electrical conductivity (EC), pH, turbidity, temperature, total phosphates (TPs), and total nitrates (TNs) as the basin land-use and land-cover (LULC) percentages. The performance of the FNN model is compared with the multiple linear regression (MLR) model. For both FNN and MLR models, the use of the eight water quality parameters yielded the best DO prediction results with respective Pearson correlation coefficient R values of 0.8546 and 0.6199. In the model optimization, EC, TP, TN, pH, and temperature were most significant contributing water quality parameters with 85.5% in DO prediction. For both models, LULC gave the best results with successful prediction of DO at nearly 98% degree of accuracy, with the combination of LULC and the water quality parameters presenting the same degree of accuracy for both FNN and MLR models.

scholarly journals Can Decomposition Approaches Always Enhance Soft Computing Models? Predicting the Dissolved Oxygen Concentration in the St. Johns River, Florida

2019 ◽  
Vol 9 (12) ◽  
pp. 2534 ◽  
Author(s):  
Mohammad Zounemat-Kermani ◽  
Youngmin Seo ◽  
Sungwon Kim ◽  
Mohammad Ali Ghorbani ◽  
Saeed Samadianfard ◽  
...  
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Dissolved Oxygen ◽  
Soft Computing ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Performance Criteria ◽  
Input Combination ◽  
Do Concentration ◽  
Computing Models

This study evaluates standalone and hybrid soft computing models for predicting dissolved oxygen (DO) concentration by utilizing different water quality parameters. In the first stage, two standalone soft computing models, including multilayer perceptron (MLP) neural network and cascade correlation neural network (CCNN), were proposed for estimating the DO concentration in the St. Johns River, Florida, USA. The DO concentration and water quality parameters (e.g., chloride (Cl), nitrogen oxides (NOx), total dissolved solid (TDS), potential of hydrogen (pH), and water temperature (WT)) were used for developing the standalone models by defining six combinations of input parameters. Results were evaluated using five performance criteria metrics. Overall results revealed that the CCNN model with input combination III (CCNN-III) provided the most accurate predictions of DO concentration values (root mean square error (RMSE) = 1.261 mg/L, Nash-Sutcliffe coefficient (NSE) = 0.736, Willmott’s index of agreement (WI) = 0.919, R2 = 0.801, and mean absolute error (MAE) = 0.989 mg/L) for the standalone model category. In the second stage, two decomposition approaches, including discrete wavelet transform (DWT) and variational mode decomposition (VMD), were employed to improve the accuracy of DO concentration using the MLP and CCNN models with input combination III (e.g., DWT-MLP-III, DWT-CCNN-III, VMD-MLP-III, and VMD-CCNN-III). From the results, the DWT-MLP-III and VMD-MLP-III models provided better accuracy than the standalone models (e.g., MLP-III and CCNN-III). Comparison of the best hybrid soft computing models showed that the VMD-MLP-III model with 4 intrinsic mode functions (IMFs) and 10 quadratic penalty factor (VMD-MLP-III (K = 4 and α = 10)) model yielded slightly better performance than the DWT-MLP-III with Daubechies-6 (D6) and Symmlet-6 (S6) (DWT-MLP-III (D6 and S6)) models. Unfortunately, the DWT-CCNN-III and VMD-CCNN-III models did not improve the performance of the CCNN-III model. It was found that the CCNN-III model cannot be used to apply the hybrid soft computing modeling for prediction of the DO concentration. Graphical comparisons (e.g., Taylor diagram and violin plot) were also utilized to examine the similarity between the observed and predicted DO concentration values. The DWT-MLP-III and VMD-MLP-III models can be an alternative tool for accurate prediction of the DO concentration values.

scholarly journals Economic evaluation of the impacts of water quality on fishery production in the Estuary Complex of Santos, São Vicente and Bertioga cities, in southeastern coast of Brazil

2020 ◽  
Vol 56 (1) ◽  
pp. 99-110
Author(s):  
Victor Carrozza Barcellini ◽  
Ângela Tavares Paes ◽  
Simone Georges El Khouri Miraglia
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Total Phosphorus ◽  
Linear Models ◽  
Quality Parameters ◽  
Sao Paulo ◽  
Water Quality Parameters ◽  
São Paulo ◽  
Fishing Activity ◽  
Monetary Loss

The present study proposes a diagnosis of water quality and fishery production in the Estuarine Complex of Santos, São Vicente, and Bertioga Cities as a requirement for economic valuation of water pollution impacts on fishing production. In the study period (2009–2014), three water quality parameters were identified (dissolved oxygen, total phosphorus, and nitrate), which occurred more frequently in non-conformity with Brazilian water standards, according to reports released by the Environmental Company of São Paulo State (Companhia Ambiental do Estado de São Paulo — CETESB). For data collection of fishery production, data from the monitoring of Institute of Fisheries of Santos City (Instituto de Pesca de Santos) were used, and 15 species were identified with higher occurrence in the study area. The relation between water quality parameters and fishery production was analyzed with mixed linear models, in which significant values for dissolved oxygen parameters, total phosphorus (positive relation), and nitrate (negative relation) were found. Environmental valuation considered only the direct use values (DUV) component of the valuation of fishery production variation in relation to water quality variation. For this purpose, the Marginal Productivity Method (MPM) of the dose-response function was used, which resulted in a range of monetary loss between US$ 24,760,550.22 and US$ 60,635,978.78. The obtained values represent only a portion of the valuation of economic and environmental loss in the fishing activity (part of DUV). Therefore, economic value calculated is conservative, and although it did not reached the total amount corresponding to all the impacts caused by poor water quality, given the limitations of methods and study period, the obtained values represent the minimum environmental monetary loss.

scholarly journals Integrated versus isolated scenario for prediction dissolved oxygen at progression of water quality monitoring stations

2011 ◽  
Vol 15 (8) ◽  
pp. 2693-2708 ◽  
Author(s):  
A. Najah ◽  
A. El-Shafie ◽  
O. A. Karim ◽  
O. Jaafar
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Prediction Model ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Effective Parameters ◽  
Data Set ◽  
Proposed Model ◽  
Input Parameters ◽  
Predicted Values

Abstract. This study examined the potential of Multi-layer Perceptron Neural Network (MLP-NN) in predicting dissolved oxygen (DO) at Johor River Basin. The river water quality parameters were monitored regularly each month at four different stations by the Department of Environment (DOE) over a period of ten years, i.e. from 1998 to 2007. The following five water quality parameters were selected for the proposed MLP-NN modelling, namely; temperature (Temp), water pH, electrical conductivity (COND), nitrate (NO3) and ammonical nitrogen (NH3-NL). In this study, two scenarios were introduced; the first scenario (Scenario 1) was to establish the prediction model for DO at each station based on five input parameters, while the second scenario (Scenario 2) was to establish the prediction model for DO based on the five input parameters and DO predicted at previous station (upstream). The model needs to verify when output results and the observed values are close enough to satisfy the verification criteria. Therefore, in order to investigate the efficiency of the proposed model, the verification of MLP-NN based on collection of field data within duration 2009–2010 is presented. To evaluate the effect of input parameters on the model, the sensitivity analysis was adopted. It was found that the most effective inputs were oxygen-containing (NO3) and oxygen demand (NH3-NL). On the other hand, Temp and pH were found to be the least effective parameters, whereas COND contributed the lowest to the proposed model. In addition, 17 neurons were selected as the best number of neurons in the hidden layer for the MLP-NN architecture. To evaluate the performance of the proposed model, three statistical indexes were used, namely; Coefficient of Efficiency (CE), Mean Square Error (MSE) and Coefficient of Correlation (CC). A relatively low correlation between the observed and predicted values in the testing data set was obtained in Scenario 1. In contrast, high coefficients of correlation were obtained between the observed and predicted values for the test sets of 0.98, 0.96 and 0.97 for all stations after adopting Scenario 2. It appeared that the results for Scenario 2 were more adequate than Scenario 1, with a significant improvement for all stations ranging from 4 % to 8 %.

scholarly journals Tingkat dan laju penurunan kualitas air di DAS Brantas Malang Raya

2019 ◽  
Vol 5 (2) ◽  
pp. 185
Author(s):  
Ima Yudha Perwira
Keyword(s):  
Water Quality ◽  
Electrical Conductivity ◽  
Dissolved Oxygen ◽  
Organic Materials ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Decrease Rate ◽  
Better Than

The decrease level of water quality of Brantas Watershed in Malang Raya was observed in this study. The aim of this study was to observe the decrease level of water quality of Brantas Watershed from Batu to Malang City. This study was carried out in the Brantas Watershed of Malang Raya (8 stations: A, B, C, D, E, F, G, and H) for 18,4 Km. The water quality parameters observed in this study were: CODmn (permanganometry), CODcr (CODmn correlation based analysis), dissolved oxygen (DO) (Winkler iodometry), TDS and electrical conductivity (EC) (EC meter), pH (pH meter), and turbidity (Turbidity meter). The result showed the value of CODmn: 1,8-10,2 mg/L, CODcr: 5,6-31,5 mg/L, DO: 4,0-6,1 mg/L, TDS: 204-289 mg/L, EC: 430-617 µS/cm, pH: 7,1-7,6, and turbidity: 2,02-10,30 NTU. There are 3 stations (A, B, and C) with 1st class water quality, 1 station (D) with the 2nd class water quality, and 4 stations (E, F, G, and H) with 3rd class water quality. The decrease of water quality in the Brantas Watershed from Batu to Malang City was up to 3 times with a decrease rate of 2,3 mg/L-1Km-1. The decomposition of organic materials in the water of Batu City and western part of Malang City is relatively better than that of central parts of Malang City which might be caused by the over capacity of recovery (Self-purification mechanism).

scholarly journals Modeling Water Quality Parameters Using Landsat Multispectral Images: A Case Study of Erlong Lake, Northeast China

2021 ◽  
Vol 13 (9) ◽  
pp. 1603
Author(s):  
Bazel Al-Shaibah ◽  
Xingpeng Liu ◽  
Jiquan Zhang ◽  
Zhijun Tong ◽  
Mingxi Zhang ◽  
...  
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Shallow Water ◽  
Deep Water ◽  
Northeast China ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Multispectral Images ◽  
Landsat Images

Erlong Lake is considered one of the largest lakes in midwest Jilin, China, and one of the drinking water resources in neighboring cities. The present study aims to explore the usage of Landsat TM5, ETM7, and OLI8 images to assess water quality (V-phenol, dissolved oxygen (DO), NH4-N, NO3-N) in Erlong Lake, Jilin province, northeast China. Thirteen multispectral images were used in this study for May, July, August, and September in 2000, 2001, 2002, and October 2020. Radiometric and atmospheric corrections were applied to all images. All in situ water quality parameters were strongly correlated to each other, except DO. The in situ measurements (V-phenol, dissolved oxygen, NH4-N, NO3-N) were statistically correlated with various spectral band combinations (blue, green, red, and NIR) derived from Landsat imagery. Regression analysis reported that there are strong relationships between the estimated and retrieved water quality from the Landsat images. Moreover, in calibrations, the highest value of the coefficient of determination (R2) was ≥0.85 with (RMSE) = 0.038; the lowest value of R2 was >0.30 with RMSE= 0.752. All generated models were validated in different statistical indices; R2 was up to 0.95 for most cases, with RMSE ranging from 1.390 to 0.050. Finally, the empirical algorithms were successfully assessed (V-phenol, dissolved oxygen, NH4-N, NO3-N) in Erlong Lake, using Landsat images with very good accuracy. Both in situ and model retrieved results showed the same trends with non-significant differences. September of 2000, 2001, and 2002 and October of 2020 were selected to assess the spatial distributions of V-phenol, DO, NH4-N, and NO3-N in the lake. V-phenol, NH4-N, and NO3-N were reported low in shallow water but high in deep water, while DO was high in shallow water but low in deep water of the lake. Domestic sewage, agricultural, and urban industrial pollution are the most common sources of pollution in the Erlong Lake.

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