Literature DB >> 21544505

Sensitivity analysis of water quality for Delhi stretch of the River Yamuna, India.

D L Parmar1, Ashok K Keshari.   

Abstract

Simulation models are used to aid the decision makers about water pollution control and management in river systems. However, uncertainty of model parameters affects the model predictions and hence the pollution control decision. Therefore, it often is necessary to identify the model parameters that significantly affect the model output uncertainty prior to or as a supplement to model application to water pollution control and planning problems. In this study, sensitivity analysis, as a tool for uncertainty analysis was carried out to assess the sensitivity of water quality to (a) model parameters (b) pollution abatement measures such as wastewater treatment, waste discharge and flow augmentation from upstream reservoir. In addition, sensitivity analysis for the "best practical solution" was carried out to help the decision makers in choosing an appropriate option. The Delhi stretch of the river Yamuna was considered as a case study. The QUAL2E model is used for water quality simulation. The results obtained indicate that parameters K(1) (deoxygenation constant) and K(3) (settling oxygen demand), which is the rate of biochemical decomposition of organic matter and rate of BOD removal by settling, respectively, are the most sensitive parameters for the considered river stretch. Different combinations of variations in K(1) and K(2) also revealed similar results for better understanding of inter-dependability of K(1) and K(2). Also, among the pollution abatement methods, the change (perturbation) in wastewater treatment level at primary, secondary, tertiary, and advanced has the greatest effect on the uncertainty of the simulated dissolved oxygen and biochemical oxygen demand concentrations.

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Year:  2011        PMID: 21544505     DOI: 10.1007/s10661-011-2055-1

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  5 in total

1.  Risk assessment approach for untreated wastewater using the QUAL2E water quality model.

Authors:  D C McAvoy; P Masscheleyn; C Peng; S W Morrall; A B Casilla; J M U Lim; E G Gregorio
Journal:  Chemosphere       Date:  2003-07       Impact factor: 7.086

2.  SOME REAERATION STUDIES IN STREAMS.

Authors:  M OWENS; R W EDWARDS; J W GIBBS
Journal:  Air Water Pollut       Date:  1964-09

3.  The evaluation of uncertainty propagation into river water quality predictions to guide future monitoring campaigns.

Authors:  V Vandenberghe; W Bauwens; P A Vanrolleghem
Journal:  Commun Agric Appl Biol Sci       Date:  2004

4.  Water quality modelling of the river Yamuna (India) using QUAL2E-UNCAS.

Authors:  Ritu Paliwal; Prateek Sharma; Arun Kansal
Journal:  J Environ Manage       Date:  2006-05-11       Impact factor: 6.789

5.  Water quality modeling to determine minimum instream flow for fish survival in tidal rivers.

Authors:  Wen-Cheng Liu; Shin-Yi Liu; Ming-Hsi Hsu; Albert Y Kuo
Journal:  J Environ Manage       Date:  2005-09       Impact factor: 6.789

  5 in total
  4 in total

1.  Comprehensive evaluation of water quality status for entire stretch of Yamuna River, India.

Authors:  Maneesh Jaiswal; Jakir Hussain; Sanjay Kumar Gupta; Mahmoud Nasr; Arvind Kumar Nema
Journal:  Environ Monit Assess       Date:  2019-03-07       Impact factor: 2.513

2.  Estimation of environmental flow incorporating water quality and hypothetical climate change scenarios.

Authors:  Bendangtola Walling; Shushobhit Chaudhary; C T Dhanya; Arun Kumar
Journal:  Environ Monit Assess       Date:  2017-04-21       Impact factor: 2.513

3.  Pollution risk assessment based on QUAL2E-UNCAS simulations of a tropical river in Northern India.

Authors:  Richa Babbar
Journal:  Environ Monit Assess       Date:  2014-07-03       Impact factor: 2.513

4.  Assessment of Water Quality Profile Using Numerical Modeling Approach in Major Climate Classes of Asia.

Authors:  Muhammad Mazhar Iqbal; Muhammad Shoaib; Hafiz Umar Farid; Jung Lyul Lee
Journal:  Int J Environ Res Public Health       Date:  2018-10-15       Impact factor: 3.390

  4 in total

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