Modelling of dissolved oxygen and biochemical oxygen demand in river water using a detailed and a simplified model

Radwan, Mona; Willems, Patrick; El‐Sadek, Alaa; Berlamont, Jean

doi:10.1080/15715124.2003.9635196

Cited by 94 publications

(51 citation statements)

References 3 publications

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“…The solubility of DO in winter would increase due to the lower temperature and higher atmospheric pressure [33,34]. The DO content in river water is influenced by many factors, such as hydrodynamic conditions, phytoplankton photosynthesis, and degradation of organic matter [35][36][37][38]. Most DO contents of river water in our research were more than 10 mg/L [33].…”

Section: Cluster Analysis and Spatio-temporal Similaritymentioning

confidence: 99%

Spatio-Temporal Variation and Controlling Factors of Water Quality in Yongding River Replenished by Reclaimed Water in Beijing, North China

Zheng

et al. 2017

Water

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Reclaimed water is useful for replenishing dried up rivers in North China, although changes in water quality could be an issue. Therefore, it is essential to understand the spatio-temporal variation and the controlling factors of water quality. Samples of Yongding River water were collected seasonally, and 24 water quality parameters were analyzed in 2015. All waters were alkaline, and nitrate-nitrogen was the main form of nitrogen, while phosphorus was mostly below detection level. The water quality parameters varied in time and space. Cluster analysis showed a distinct difference between winter and the other seasons and between the natural river section and the section with reclaimed water. Based on the analysis of Gibbs plots, principal component analysis, and ionic relationships, the water chemistry was controlled by dissolution of rocks in natural river section, the quality of replenished water, the effects of dilution, and the reaction of aqueous chemistry in the reclaimed water section. The positive oxidation environment in most of the river water was conducive to the formation of nitrate-nitrogen by nitrification, and not conducive to denitrification.

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Section: Cluster Analysis and Spatio-temporal Similaritymentioning

confidence: 99%

Spatio-Temporal Variation and Controlling Factors of Water Quality in Yongding River Replenished by Reclaimed Water in Beijing, North China

Zheng

et al. 2017

Water

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“…Adrian & Alshawabkeh (1997) developed an analytical solution for BOD and DO in a river for the case when BOD-and DOloading concentrations both vary sinusoidally. Radwan et al (2003) developed BOD and DO dynamics in a river in Flanders: BOD sources from agricultural leaching and domestic point sources were considered. Advection and dispersion were taken into consideration, together with the most important biological and chemical processes.…”

Section: Literature Reviewmentioning

confidence: 99%

Critical appraisal of BOD and DO models applied to a highly polluted river in India

Jha¹,

Ojha

Bhatia³

2007

Hydrological Sciences Journal

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Most commonly used biochemical oxygen demand (BOD) and dissolved oxygen (DO) models have been tested for their applicability in the River Kali, which is one of the most polluted rivers in India. A total of 732 field data sets were generated during field survey from March 1999 to February 2000. The modelling of BOD and DO in the River Kali involves derivation and solution of the governing equations that describe concentration change with time and space brought on by advective, decay, settling and loading functions. However, due to continuous discharges (e.g. from wastewater treatment plants) and steady-state flow conditions in the River Kali, the dispersion effects are found to be insignificant. In the analysis, the model parameters used in BOD-DO models were optimized using the Newton-Raphson technique and the performance of different models was evaluated using correlation statistics (r 2 ) and error estimation, viz. standard error (SE) and mean multiplicative error (MME). The results indicate that the BOD-DO models developed after Camp (1963) yielded the best agreement with the observed values as compared with several other approaches. Mots clefs demande biochimique en oxygène (DBO

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“…The formulation of water quality management strategies requires the inter-disciplinary analysis of various potential causes of water quality degradation and corresponding solutions [14,15]. Mathematical models are widely used to simulate the pollution of water bodies for likely wastewater production and treatment scenarios [16][17][18]. These models may be based on physical data or a simplified conceptual or empirical approach.…”

Section: Introduction and Research Backgroundmentioning

confidence: 99%

Current Assessment and Future Outlook for Water Resources Considering Climate Change and a Population Burst: A Case Study of Ciliwung River, Jakarta City, Indonesia

Kumar

Masago

Mishra

et al. 2017

Water

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Abstract:Modeling insecurity under future climate change and socio-economic development is indispensable for adaptive planning and sustainable management of water resources. This case study strives to assess the water quality and quantity status for both the present and the near future in the Ciliwung River basin inside the Jakarta Province under different scenarios using population growth with planned additional wastewater management infrastructure by 2030 as mentioned in the local master plan, and comparing the above conditions with the addition of the effects of climate change. Biochemical oxygen demand (BOD), chemical oxygen demand (COD) and nitrate (NO 3 ), the three important indicators of aquatic ecosystem health, were simulated to assess river pollution. Simulation results suggest that water quality in year 2030 will further deteriorate compared to the base year 2000 due to population growth and climate change, even considering the planned wastewater management infrastructure. The magnitude of impact from population growth is far greater than that from climate change. Simulated values of NO 3 , BOD and COD ranged from 6.07 to 13.34 mg/L, 7.65 to 11.41 mg/L, and 20.16 to 51.01 mg/L, respectively. Almost all of the water quality parameters exceeded the safe limit suitable for a healthy aquatic system, especially for the year 2030. The situation of water quality is worse for the downstream sampling location because of the cumulative effect of transport of untreated pollutants coming from upstream, as well as local dumping. This result will be useful for local policy makers and stakeholders involved in the water sector to formulate strategic and adaptive policies and plan for the future. One of the potential policy interventions is to implement a national integrated sewerage and septage management program on a priority basis, considering various factors like population density and growth, and global changes for both short-and long-term measures.

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Modelling of dissolved oxygen and biochemical oxygen demand in river water using a detailed and a simplified model

Cited by 94 publications

References 3 publications

Spatio-Temporal Variation and Controlling Factors of Water Quality in Yongding River Replenished by Reclaimed Water in Beijing, North China

Spatio-Temporal Variation and Controlling Factors of Water Quality in Yongding River Replenished by Reclaimed Water in Beijing, North China

Critical appraisal of BOD and DO models applied to a highly polluted river in India

Current Assessment and Future Outlook for Water Resources Considering Climate Change and a Population Burst: A Case Study of Ciliwung River, Jakarta City, Indonesia

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