Nitrate and biochemical oxygen demand change in a typical Midwest stream in the past two decades

Alam, Shahin; Han, Bangshuai; Gregg, Amy; Pichtel, John

doi:10.2166/h2oj.2020.054

Cited by 5 publications

(3 citation statements)

References 19 publications

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“…The conformity denotes little influence from anthropogenic activities in the study area. High nitrate is known to increase the growth of plants and algae in the water body and this contributes to high BOD and the depletion of oxygen (Poulsen et al, 2018;Alam et al, 2021). The low nitrate values recorded in this study corresponds with the low BOD observed.…”

Section: Discussionsupporting

confidence: 74%

Profiling the surface water around Odeama Community of the Niger Delta area of Nigeria

Okoro¹,

Lily²

2022

J. Environ. Chem. Ecotoxicol.

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Surface water quality in Niger Delta has been impaired over the years as a result of oil exploration and exploitation carried out in the region. This study investigates the anthropogenic influence on the water quality of Odeama creek. Water samples were collected during the wet and dry season from 20 sampling points and four control points and analyzed following standard methods and procedures. No statistical difference (p> 0.005) at 95% confidence interval was observed between sampling points except for nitrate values in the dry season. Some of the results observed in this study are: pH range of 7.1 -8.0 and 7.12 -8.3; dissolved oxygen, 4.8 -5.4 and 2.12 -3.69 mg/L; chemical oxygen demand, 4.8 -5.4L and 2.12 -3.69 mg/L; polynuclear aromatic hydrocarbons, 0.01 -0.17 and 0.05 -1.06 mg/L for wet and dry season, respectively. Values observed from dissolved oxygen, chemical oxygen demand, polynuclear aromatic hydrocarbons, and heavy metals except copper indicated human influence on the water quality that may be due to domestic and industrial waste, illegal bunkering activities, and corrosion of abandoned vessels in the water-way. Regular monitoring of the physicochemical parameters and standard measures should be put in place to evaluate and control anthropogenic influence on the water quality.

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Section: Discussionsupporting

confidence: 74%

Profiling the surface water around Odeama Community of the Niger Delta area of Nigeria

Okoro¹,

Lily²

2022

J. Environ. Chem. Ecotoxicol.

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“…Microbes use dissolved oxygen to decompose the organic matter in a water sample. The amount of oxygen used is directly related to the amount of organic matter present, as assessed by the BOD test (Alam et al, 2021). If persistently high BOD and low DO values are allowed, it can disrupt the stability of aquatic biota, ultimately leading to their demise.…”

Section: Parameters Of Chemicalmentioning

confidence: 99%

Assessment of Changes in Water Quality of Enim River, Muara Enim, South Sumatera, Indonesia to Determine Environmental Designations

Sinaga,

Ibrahim,

Hadiah

2024

indones. j. env. man. sus.

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Enim river flows within several sub-districts in Muara Enim Regency, including Semendo Darat Laut, Semendo Darat Tengah, Semendo Darat Ulu, Tanjung Agung, Lawang Kidul, and Muara Enim. This study examines changes in the water quality of the Enim River due to domestic wastewater discharges and the presence of the coal mining industry and household industries. Water samples were taken from 4 sampling stations along the Enim River in 2018 and 2023. Data consisted of results of physical, chemical, and microbiological parameters. The status of river water quality was assessed from the pollution index. The results of Enim River surface water quality measurements showed that the parameters of total suspended solids, Dissolved Oxygen, iron (Fe), copper (Cu), oil, and grease concentrations had breached the criteria set for Class II water quality, referring to Government Regulation of the Republic of Indonesia Number 82 of 2001. The results showed that there has been a change in the water quality status of Enim River from 2018 to 2023. The river water pollution index was (1.43-2.47) in 2018 and (1.49-3.85) in 2023 (lightly polluted). Comprehensive water treatment and preventive measures are necessary to manage and mitigate additional pollution in the Enim River.

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“…Ravansalar & Rajaee (2015) obtained an R 2 value of 0.949 using wavelet-based ANNs against a value of 0.381 using ANNs in the prediction of electrical conductivity for Asi River, Turkey. Alam et al (2021) have used Weighted Regression on Time, Discharge and Seasons (WRTDS) to analyze the long-term trends of water quality especially that of BOD, DO, and nitrate-nitrite (NN), and found the influences of wastewater treatment plants (WWTPs), combined sewage outflows (CSOs), and agricultural runoff in increase of pollution levels for White River at Muncie, IN, USA. However, the current study is limited to the temporal prediction of WQPs from climate and land use parameters and has not considered the influences of discharge and seasons separately.…”

Section: Matlab Simulations Using the Levenberg-marquardt Algorithm R...mentioning

confidence: 99%

Prediction of stream water quality in Godavari River Basin, India using statistical and artificial neural network models

et al. 2022

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The successful prediction of the stream or river water quality is gaining the attention of various governmental agencies, and pollution control boards worldwide due to its useful applications in determining watershed health, biodiversity, ecology, and suitability of potable water needs of the river basin. The physically based computational water quality models would require large spatial and temporal information databases of climatic, hydrologic, and environmental variables and solutions of nonlinear, partial differential equations at each grid point in a river basin. These models suffer from estimability, convergence, stability, approximation, dispersion, and consistency issues. In such a problematic modeling scenario, an artificial neural network (ANN) modeling of 22 stream water quality parameters (SWQPs) is performed from easily measurable data of precipitation, temperature, and novel land use parameters obtained from Geographic Information System (GIS) analysis for the Godavari River Basin, India. The ANN models are compared with the more traditional, statistical linear, and nonlinear regression models for accuracy and performance statistics. This study obtains regression coefficients of 0.93, 0.78, 0.83, and 0.74 for electrical conductivity, dissolved oxygen, biochemical oxygen demand, and nitrate in testing using feedforward ANNs compared with a maximum of 0.45 using linear and nonlinear regressions. Principal component analysis (PCA) is performed to reduce the input data dimension. The subsequent modeling using radial basis function and ANNs is found to improve the overall regression coefficients slightly for the chosen four water quality parameters (WQPs). A closed form equation for electrical conductivity has been derived from MATLAB simulations. The successful modeling results indicate the effectiveness and potential of ANNs over the statistical regression approaches for estimating the highly nonlinear problem of stream water quality distributions.

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Nitrate and biochemical oxygen demand change in a typical Midwest stream in the past two decades

Cited by 5 publications

References 19 publications

Profiling the surface water around Odeama Community of the Niger Delta area of Nigeria

Profiling the surface water around Odeama Community of the Niger Delta area of Nigeria

Assessment of Changes in Water Quality of Enim River, Muara Enim, South Sumatera, Indonesia to Determine Environmental Designations

Prediction of stream water quality in Godavari River Basin, India using statistical and artificial neural network models

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