Analysis of Carrying Capacity and Water Pollution in the Simporo Strait Area After the Flash Flood

Walukow, Auldry F.; Sukarta, I Nyoman

doi:10.12912/27197050/135528

Cited by 4 publications

(3 citation statements)

References 6 publications

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“…TSS consists of organic materials such as the debris part of an organism and inorganic materials in the form of fne sands and mud. Previous research studies show that a high level of TSS in Semporo Strait (Papua, Indonesia) is caused by factors such as erosion, land use, shifting, agriculture, inhabitant settlement, and sand mining [25].…”

Section: Resultsmentioning

confidence: 99%

Evaluation of the Water Quality Status and Pollution Load Carrying Capacity of Way Umpu River, Way Kanan District, Lampung Province, Indonesia, Based on Land Use

Tugiyono

Setiawan

Suharso

et al. 2023

International Journal of Ecology

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This research aims to evaluate the water quality status and pollution load-carrying capacity of the Way Umpu River based on land use. This was carried out using the survey method by directly measuring the river water debit, pH, temperature, and dissolved oxygen (DO) on-site, taking the water sample to analyze the parameters of water quality such as total dissolved solid (TDS), total suspended solid (TSS), water color, turbidity, salinity, biochemical oxygen demand (BOD), chemical oxygen demand (COD), fecal coli, total coliform, and plankton in the lab, and monitoring the land use. The results showed that the use of land for illegal mining and the settlement of inhabitants in station-4 (ST-4) caused water pollution. Furthermore, based on Class III water use, the parameters in ST-4 exceeded the standards for TSS, color, and BOD, while other stations such as ST-1, ST-2, ST-3, ST-5, and ST-6 showed clean and good water quality statuses. It was also found that the pollution load-carrying capacity of the Way Umpu River has not yet been exceeded for Class III and the quality of the water may be improved when the river water debit increases. In addition, the plankton community structure on ST-1, ST-2, and ST-3 showed the number of species and individuals, and the diversity index was relatively high compared to ST-4, ST-5, and ST-6. It was concluded that the integrated evaluation was based on water quality status, plankton community structure, and pollution load analyses. The land use for illegal mining will decrease the water quality and the plankton community structure compared to other land uses.

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Section: Resultsmentioning

confidence: 99%

Evaluation of the Water Quality Status and Pollution Load Carrying Capacity of Way Umpu River, Way Kanan District, Lampung Province, Indonesia, Based on Land Use

Tugiyono

Setiawan

Suharso

et al. 2023

International Journal of Ecology

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“…Beberapa penelitian tentang beban pencemaran sungai -sungai yang masuk ke Danau Sentani menyimpulkan bahwa beban pencemaran Cu di sungai Jembatan dua meningkat dari 0,01 ton/bulan menjadi 0,08 ton/bulan sejak tahun 2012 sampai 2014 (Walukow, 2016(Walukow, , 2021a, beban pencemaran TDS meningkat dari 263,09 ton/bulan menjadi 287,70 ton/bulan (Walukow, 2008(Walukow, , 2021b. Begitu pula beban pencemaran Fosfat di Sungai Flafouw meningkat dari 0,26 ton/bulan menjadi 1,71 ton/bulan pada tahun 2005 sampai 2007 (Walukow, 2010a(Walukow, , 2010b.…”

Section: Pendahuluanunclassified

Kendala Pengendalian Pencemaran Total Suspended Solid dan Phosphat di Sub Das Tlaga Ria Sentani Pasca Banjir Bandang

Walukow

Triwiyono

Lumbu

2021

DLI

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The problem that occurs in Lake Sentani is that it has been contaminated by parameters of TSS, BOD, Pb, Cu, and DO respectively with valuesof 76 mg / L, 4.63 mg / L, 0.035 mg / L, 0.03 mg / L, and 5.72 mg / L because these parameters have exceeded the quality standard according to environmental regulations. This study aims to determine the assimilation capacity of TSS and PO4 parameters and analyze pollution control models in the Tlaga Ria sub-watershed. The research method used to determine the assimilation capacity is a linear regression equation and in analyzing the pollution control model the interpretative structural modeling method is used. The results showed that the TSS assimilation capacity value in Lake Sentani was -12,700 tons/month. The value of water quality in Lake Sentani is above the value of the assimilation capacity, this shows that Lake Sentani has been polluted by TSS parameters. Meanwhile, the value of PO4 parameter assimilation capacity is 44.36 tons/month and since 2016 Lake Sentani has been unable to conduct self purification. The key elements of the Sentani Lake pollution control constraints in the Tlaga Ria watershed are weak implementation of environmental regulations, differences in objectives among stakeholders, differences in objectives between administrative areas, weak support of business owners, conflict of interests, and weak enforcement of regulations.

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“…Flooding water will reduce the salinity [7]. These floods or drainage will contain mud or sewage [8], making the fish knock out of the water or die [9]. Furthermore, increasing atmospheric carbon dioxide is dissolved in seawater.…”

Section: Introductionmentioning

confidence: 99%

Improving the Water Quality Classification Model for Various Farms Using Features Based on Artificial Neural Network

Nuanmeesri,

Poomhiran,

Kadmateekarun

et al. 2023

TEM Journal

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Measuring and classifying the water quality is necessary to manage the appropriate water quality for various farms near the coast or affected by seawater. This research aimed to improve the water quality classification model for various farms using Multi-Layer Perceptron Neural Network-based multi-class Support Vector Machine. It also implements the Random Forest Feature Importance Selection to increase model accuracy. The class reduction technique decreases the probability of co-occurrence classes for various farms in overlapping water ecosystems. The result has shown that the dataset that applied the class reduction helped increase the model’s efficiency more than the feature selection technique. The models that applied the multi-class Support Vector Machine classifier are more accurate than the Softmax activation function classifier. The findings indicate that the model using Multi-Layer Perceptron Neural Network-based One-versus-One Support Vector Machine combined with the Random Forest Feature Importance Selection and the class reduction has the highest efficiency and improves the water quality classification model in various farms.

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Analysis of Carrying Capacity and Water Pollution in the Simporo Strait Area After the Flash Flood

Cited by 4 publications

References 6 publications

Evaluation of the Water Quality Status and Pollution Load Carrying Capacity of Way Umpu River, Way Kanan District, Lampung Province, Indonesia, Based on Land Use

Evaluation of the Water Quality Status and Pollution Load Carrying Capacity of Way Umpu River, Way Kanan District, Lampung Province, Indonesia, Based on Land Use

Kendala Pengendalian Pencemaran Total Suspended Solid dan Phosphat di Sub Das Tlaga Ria Sentani Pasca Banjir Bandang

Improving the Water Quality Classification Model for Various Farms Using Features Based on Artificial Neural Network

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