Nutrient modeling of an urban lake using best subset method

Bera, Bireshwar; Chanda, R.; Sarkar, Santosh Kumar; Majumdar, Jayjit; Majumder, Santanu; Hazra, Saumen

doi:10.1007/s13762-017-1540-7

Cited by 9 publications

(10 citation statements)

References 40 publications

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“…To formulate deserving sustainable management strategies, a good understanding of nutrient transformation using a dynamic ecological model is considered necessary. Dynamic ecological models developed and applied have been demonstrated to be powerful tools for simulation of nutrient transformation and removal from lakes and wetland ecosystems (Van Dam et al 2007;Tang et al 2016;Biswas et al 2018;Mayo et al 2018;Radbourne et al 2019). Nevertheless, no significant efforts have been made to model the processes that govern nutrient transformation and removal processes in small freshwater lakes like Lake Bunyonyi which suffer pollution from diffuse sources.…”

Section: Introductionmentioning

confidence: 99%

Modelling nitrogen transformation in the Lake Bunyonyi ecosystem, South-Western Uganda

et al. 2022

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Lake Bunyonyi is one of the major resources of social-economic potential in the districts of Rubanda and Kabale, South-Western Uganda. The lake’s sub-catchment faces environmental problems because of intensive agriculture, settlement, business and tourism activities, which consequently cause pollution of water in the lake’s system. This study, therefore, intended to determine the processes that govern nitrogen dynamism using a numerical model that takes into account various processes in the system using STELLA® 8.1.1 software. From the model simulation, it was found that mineralization, microbial uptake and nitrification were the major processes governing nitrogen transformation in the water phase, accounting for 47.8% (0.49 g/d m−2), 44.2% (0.45 g/d m−2), and 7.8% (0.05 g/d m−2), respectively. The developed model predicted reasonably well the behaviour of the lake evidenced by the validation results of observed and simulated data that showed good linear regression coefficients (R2) of organic nitrogen (0.48), ammonia–nitrogen (0.68), and nitrate–nitrogen (0.61). The model has proven suitable for application on lakes with characteristics similar to that of Lake Bunyonyi. The study recommended that a compressive investigation that puts into consideration all the possible sources of nutrient and water inflow into the lake system be done on Lake Bunyonyi.

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Section: Introductionmentioning

confidence: 99%

Modelling nitrogen transformation in the Lake Bunyonyi ecosystem, South-Western Uganda

et al. 2022

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“…[63,64] High organic loading consumed DO to reduce it considerably, with a concomitant increase in free CO 2 concentration culminating in a semi-anoxic to almost anoxic condition. [65] Among the ten physicochemical parameters of water, seasonal variation was observed only for five parameters (temperature, TDS, turbidity, DO, and free CO 2 ) in RP. In both the sampling spots (PR-1 and PR-2) of the river Saraswati, seasonal variation was more prominent in the mean value of temperature, EC, TDS, and turbidity, while the variation was less prominent in the mean concentration of DO, free CO 2 , BOD, and COD.…”

Section: Discussionmentioning

confidence: 92%

“…[ 63,64 ] High organic loading consumed DO to reduce it considerably, with a concomitant increase in free CO 2 concentration culminating in a semi‐anoxic to almost anoxic condition. [ 65 ]…”

Section: Discussionmentioning

confidence: 99%

Assessment of the Present State and Future Fate of River Saraswati, India: Water Quality Indices and Forecast Models as Diagnostic and Management Tools

Pramanik

Kaviraj

Saha

2023

CLEAN Soil Air Water

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Water quality assessment is key to the conservation and management of rivers. River Saraswati, a distributary of the river Ganga, serves as a lifeline to many villages in the district Hooghly in West Bengal, India. As the river is gradually dying due to diverse man‐made pollution, ten water quality parameters in two sampling spots (PR‐1 and PR‐2) in the river are monitored month‐wise from March 2017 to February 2020, and these are compared with those from a reference pond. The water quality index (WQI) is determined for the two riverine spots and the reference pond based on the Canadian Council of Ministers of Environment WQI (CCMEWQI) and weighted arithmetic WQI, respectively. In addition to actual observations, three different forecasting methods, exponential smoothing, autoregressive integrated moving average, and artificial neural network, are used to predict WQI for the next two years. This study indicates that free CO2, dissolved oxygen, and turbidity are the key parameters to evaluate this river's anthropogenic stress and health. The actual and forecasted results reflect the precipitous degradation of CCMEWQI in PR‐2. Therefore, the immediate intervention of all stakeholders is required to adopt an integrated and comprehensive river management plan to save the river from utter obliteration.

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“…It should be noted that in the case of nitrogen, the TIN/ON ratio may also have significant importance (Vaiopoulou and Aivasidis 2008 ; Zhou et al 2018 ). A high TIN/ON ratio in treated wastewater can directly trigger eutrophication acceleration (Li and Brett 2012 ) as well as effluents characterized by a low TIN/ON ratio which can also cause acceleration of eutrophication in sensitive estuaries and inland waters (Schindler 2006 ; Huang et al 2017 ; Biswas et al 2018 ).…”

Section: Resultsmentioning

confidence: 99%

Mitigation of eutrophication caused by wastewater discharge: A simulation-based approach

Preisner

Neverova-Dziopak

Kowalewski

2020

Ambio

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Mitigation of eutrophication, intensified by excessive nutrient load discharge in wastewaters regulated by restrictive legal requirements, remains one of today’s most important global problems. Despite implementation of the Water Framework Directive, the Urban Wastewater Directive and the HELCOM recommendations, the actual condition of surface water is still not satisfactory. In response to the above, the study presents an alternative approach for surface water protection against eutrophication based on the selection of appropriate nutrient removal technologies. An activated sludge model simulation was used to enable the identification of environmentally justified nutrient removal systems with lowest eutrophication potential of treated wastewater conditioned by bioavailable nutrient forms content. Based on the outcome of the study, the 3-stage Bardenpho system was identified as the most efficient for bioavailable phosphorus removal, while the Johannesburg system proved to have the highest efficiency for bioavailable nitrogen removal. The proposed eutrophication mitigation approach underlines the need for a reconsideration of current legal regulations which ignore nutrient bioavailability and key eutrophication limiting factors.

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Nutrient modeling of an urban lake using best subset method

Cited by 9 publications

References 40 publications

Modelling nitrogen transformation in the Lake Bunyonyi ecosystem, South-Western Uganda

Modelling nitrogen transformation in the Lake Bunyonyi ecosystem, South-Western Uganda

Assessment of the Present State and Future Fate of River Saraswati, India: Water Quality Indices and Forecast Models as Diagnostic and Management Tools

Mitigation of eutrophication caused by wastewater discharge: A simulation-based approach

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