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

被引:31
|
作者
Parmar, D. L. [1 ]
Keshari, Ashok K. [2 ]
机构
[1] Harcourt Butler Technol Inst, Dept Civil Engn, Kanpur 208002, Uttar Pradesh, India
[2] Indian Inst Technol Delhi, Dept Civil Engn, New Delhi 110016, India
关键词
Water quality simulation; Sensitivity analysis; Pollution abatement; Model parameters; REAERATION EQUATIONS; MODEL; UNCERTAINTY; STREAMS;
D O I
10.1007/s10661-011-2055-1
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页码:1487 / 1508
页数:22
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