Critical appraisal of water quality model parameters for an urban city in lower Ganga basin during pre- and post-COVID19 Lockdown in India

A new method is proposed based on the finite difference method (FDM), differential evolution algorithm and Markov Chain Monte Carlo (MCMC) simulation to identify water quality model parameters of an open channel in a long distance water transfer project. Firstly, this parameter identification problem is considered as a Bayesian estimation problem and the forward numerical model is solved by FDM, and the posterior probability density function of the parameters is deduced. Then these parameters are estimated using a sampling method with differential evolution algorithm and MCMC simulation. Finally this proposed method is compared with FDM–MCMC by a twin experiment. The results show that the proposed method can be used to identify water quality model parameters of an open channel in a long distance water transfer project under different scenarios better with fewer iterations, higher reliability and anti-noise capability compared with FDM–MCMC. Therefore, it provides a new idea and method to solve the traceability problem in sudden water pollution accidents.

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Improved dynamic simulation technique for hydrodynamics and water quality of river-connected lakes

Water Science & Technology Water Supply ◽

10.2166/ws.2020.125 ◽

2020 ◽

Vol 20 (8) ◽

pp. 3752-3767

Author(s):

Bojun Liu ◽

Jun Xia ◽

Libin Yang ◽

Changyong Cui ◽

Linwei Wang ◽

...

Keyword(s):

Water Quality ◽

Latin Hypercube Sampling ◽

Resistance Coefficient ◽

Water Quality Model ◽

Roughness Coefficient ◽

Model Parameters ◽

State Variables ◽

Quality Model ◽

Rank Regression ◽

Hongze Lake

Abstract In this study, a two-dimensional hydrodynamic water-quality model is proposed for river-connected lakes in an effort to improve calibration accuracy and reduce computational burden. To achieve this, the sensitivity of parameters involved in the hydrodynamic model is analyzed using stepwise rank regression and Latin hypercube sampling (LHS), and the roughness coefficient, wind drag coefficient and wind resistance coefficient are identified as the most important parameters affecting the hydrodynamics of the Hongze Lake. Then, the ensemble Kalman filter (EnKF) is used to assimilate observations to the proposed hydrodynamic and water quality model. It is found that assimilation of both state variables and model parameters results in a significant improvement of the simulation of the water level, flow velocity and pollutant concentration in the Hongze Lake.

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Extension of the River Water Quality Model No. 1 with the fate of pesticides

Journal of Hydroinformatics ◽

10.2166/hydro.2011.028 ◽

2011 ◽

Vol 14 (1) ◽

pp. 48-64 ◽

Cited By ~ 2

Author(s):

Veerle C. J. De Schepper ◽

Katrijn M. A. Holvoet ◽

Lorenzo Benedetti ◽

Piet Seuntjens ◽

Peter A. Vanrolleghem

Keyword(s):

Water Quality ◽

Water Column ◽

River Water ◽

Bulk Water ◽

Transport Processes ◽

Water Quality Model ◽

River Water Quality ◽

Model Parameters ◽

Quality Model ◽

Run Off

The existing River Water Quality Model No. 1 (RWQM1) was extended with processes determining the fate of non-volatile pesticides in the water phase and sediments. The exchange of pesticides between the water column and the sediment is described by three transport processes: diffusion, sedimentation and resuspension. Burial of sediments is also included. The modified model was used to simulate the concentrations of diuron and chloridazon in the river Nil. A good agreement was found between the simulated pesticide concentrations and measured values resulting from a four-month intensive monitoring campaign. The simulation results indicate that pesticide concentrations in the bulk water are not sensitive to the selected biochemical model parameters. It seems that these concentrations are mainly determined by the imposed upstream concentrations, run-off and direct losses. The high concentrations in the bulk water were not observed in the sediment pore water due to a limited exchange between the water column and the sediment. According to a sensitivity analysis, the observed pesticide concentrations are highly sensitive to the diffusion and sorption coefficients. Therefore, model users should determine these parameters with accuracy in order to reduce the degree of uncertainty in their results.

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Light environment and photosynthesis in the south basin of Lake Biwa: Calibration of water quality model parameters

SIL Proceedings 1922-2010 ◽

10.1080/03680770.1992.11900256 ◽

1993 ◽

Vol 25 (2) ◽

pp. 811-816

Author(s):

A. Hirayama ◽

M. Nakanishi ◽

T. Miyajima ◽

S. Nakano ◽

M. Kumagai

Keyword(s):

Water Quality ◽

Lake Biwa ◽

Water Quality Model ◽

Light Environment ◽

Model Parameters ◽

The South ◽

Quality Model ◽

South Basin

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Development and identification of a multi-species water quality model for reclaimed water distribution systems

Journal of Water Reuse and Desalination ◽

10.2166/wrd.2015.115 ◽

2015 ◽

Vol 5 (3) ◽

pp. 360-371

Author(s):

Shun Li ◽

Fu Sun ◽

Siyu Zeng ◽

Xin Dong ◽

Pengfei Du

Keyword(s):

Water Quality ◽

Distribution Systems ◽

Water Distribution ◽

Reclaimed Water ◽

Water Distribution Systems ◽

Water Quality Model ◽

Bulk Liquid ◽

Model Parameters ◽

Quality Model ◽

Long Distance

With the rapid development of a centralized wastewater reuse scheme in China, water quality concerns arise considering the long-distance transport of reclaimed water in distribution systems from wastewater treatment plants to points of use. To this end, a multi-species water quality model for reclaimed water distribution systems (RWDSs) was developed and validated against the data from part of a full-scale RWDS in Beijing. The model could simulate organics, ammonia nitrogen, residual chlorine, inert particles, and six microbial species, i.e. fecal coliforms, Enterococcus spp., Salmonella spp., Mycobacterium spp., and other heterotrophic and autotrophic bacteria, in both the bulk liquid and the biofilm. Altogether, 56 reaction processes were involved, and 37 model parameters and seven initial values were identified. Despite the limited monitoring data and the associated gross uncertainty, the model could simulate the reclaimed water quality in the RWDS with acceptable accuracy. Regional sensitivity analysis suggested that the model had a balanced structure with a large proportion of sensitive parameters, and the sensitivity of model parameters could be reasonably interpreted by current knowledge or observation. Furthermore, the most sensitive model parameters could generally be well identified with uncertainties significantly reduced, which also favored the trustworthiness of the model. Finally, future plans to improve and apply the model were also discussed.

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Sequential calibration of a water quality model using reach-specific parameter estimates

Hydrology Research ◽

10.2166/nh.2017.246 ◽

2017 ◽

Vol 49 (4) ◽

pp. 1042-1055 ◽

Cited By ~ 7

Author(s):

Shushobhit Chaudhary ◽

C. T. Dhanya ◽

Arun Kumar

Keyword(s):

Water Quality ◽

Oxygen Demand ◽

Weighted Average ◽

Sequential Estimation ◽

Water Quality Model ◽

Parameter Estimates ◽

Model Parameters ◽

Quality Model ◽

Study Region ◽

River Stretch

Abstract Calibration is the most critical phase in any water quality modelling process. This study proposes a sequential calibration methodology for any water quality model using reach-specific estimates of model parameters, which would aid in the improved prediction of river water quality characteristics. The proposed methodology accounts for the heterogeneity of river reaches, i.e., diverse characteristics of different reaches on the river stretch. The water quality model, QUAL2K, is coupled with MATLAB, a computing platform, to facilitate sequential estimation of reach-wise model parameters using a grid-based weighted average optimization. The Delhi segment of the Yamuna River is selected as study river stretch. Observations of water quality variables, dissolved oxygen and biochemical oxygen demand are used to calibrate and validate QUAL2K. Desirable performance measures are obtained during the calibration and the validation period. The methodology proves superior to the existing calibration methodologies applied over the study region. The proposed technique also captures the system behaviour effectively, through a systematic, efficient and user-friendly way. The proposed approach is expected to aid decision-makers in formulating better reach-wise management decisions and treatment policies by providing a simpler and efficient way to simulate water quality parameters.

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