Sensitivity analysis of non-point sources in a water quality model applied to a dammed low-flow-reach river

2008 ◽  
Vol 57 (8) ◽  
pp. 1295-1300
Author(s):  
Nayana G. M. Silva ◽  
Marcos von Sperling
Keyword(s):  
Water Quality ◽  
Sensitivity Analysis ◽  
Initial Conditions ◽  
Quality Parameters ◽  
Water Quality Model ◽  
Point Sources ◽  
Low Flow ◽  
Treated Wastewater ◽  
Quality Model ◽  
River Bed

Downstream of Capim Branco I hydroelectric dam (Minas Gerais state, Brazil), there is the need of keeping a minimum flow of 7 m3/s. This low flow reach (LFR) has a length of 9 km. In order to raise the water level in the low flow reach, the construction of intermediate dikes along the river bed was decided. The LFR has a tributary that receives the discharge of treated wastewater. As part of this study, water quality of the low-flow reach was modelled, in order to gain insight into its possible behaviour under different scenarios (without and with intermediate dikes). QUAL2E equations were implemented in FORTRAN code. The model takes into account point-source pollution and diffuse pollution. Uncertainty analysis was performed, presenting probabilistic results and allowing identification of the more important coefficients in the LFR water-quality model. The simulated results indicate, in general, very good conditions for most of the water quality parameters The variables of more influence found in the sensitivity analysis were the conversion coefficients (without and with dikes), the initial conditions in the reach (without dikes), the non-point incremental contributions (without dikes) and the hydraulic characteristics of the reach (with dikes).

Developing a Cloud-based Toolbox for Sensitivity Analysis of a Water Quality Model

2021 ◽  
pp. 105068
Author(s):  
Soobin Kim ◽  
Yong Sung Kwon ◽  
JongChel Pyo ◽  
Mayzonee Ligaray ◽  
Joong-Hyuk Min ◽  
...  
Keyword(s):  
Water Quality ◽  
Sensitivity Analysis ◽  
Water Quality Model ◽  
Quality Model

Impact of Further Impoundments on the Oxygen Balance and Water Quality of the Danube in Germany

1990 ◽  
Vol 22 (5) ◽  
pp. 69-78 ◽  
Author(s):  
D. Müller ◽  
V. Kirchesch
Keyword(s):  
Water Quality ◽  
Quality Parameters ◽  
Nitrifying Bacteria ◽  
Oxygen Balance ◽  
Quality Model ◽  
Model Calculations ◽  
River Bed ◽  
The Impact ◽  
The Mathematical Model

The construction of two or three impounding dams in the remaining freely flowing reach (73 km) of the Danube is under discussion. The purpose of these impoundments is to guarantee a minimum navigable depth of 3 m needed for modern cargo ships and to produce electric power. The impact of these developments is discussed on the basis of experience with similar impoundments further upstream and of the results from water quality model calculations. The mathematical model used is of the deterministic type, calculating the growth of slowly-growing organisms (nitrifying bacteria, algae and zooplanktons) according to MONOD and MICHAELIS-MENTEN. Compared with impoundments on other German rivers or the Iron Gate impoundments on the Danube, the effect of the impoundments under discussion on water quality parameters is likely to be fairly small, reflecting the slight changes in morphology which would be necessary for attaining the water depth required. Therefore, the more important effects of these developments would be the changes in the ecologic situation at the river bed and near the banks of the river.

scholarly journals The influence of artificial cutoff on a monitoring system and the water quality of the Keelung River

2002 ◽  
Vol 46 (11-12) ◽  
pp. 231-236 ◽  
Author(s):  
S.L. Lo ◽  
J.T. Kuo ◽  
S.M. Wang
Keyword(s):  
Water Quality ◽  
Monitoring Network ◽  
Water Quality Monitoring ◽  
Water Quality Model ◽  
Quality Monitoring ◽  
Low Flow ◽  
Quality Model ◽  
Significance Level ◽  
Water Quality Monitoring Network ◽  
State Water

The purpose of this study was to design a water quality monitoring network for the Keelung River in order to evaluate the effects of artificial cutoff across two bend channels. A steady-state water quality model was used to simulate the BOD and DO curves. The Kriging theory was applied to select the optimal locations for a water quality monitoring network. The sampling frequency was determined by the coefficients of variation of water quality and by considering the significance level and confidence interval. After calibration and verification of the water quality model, the model was applied and the simulation results indicated that the values of DO in the new channel would be higher than those of the old channel reaches. The critical point of the oxygen sag curve would shift to the mouth of river under Q75 low-flow conditions, and the BOD values in the new channel would also slightly increase. The results further indicated that more monitoring stations would be needed in the downstream reaches.

Effect of input uncertainties upon scenario predictions for the river vecht

1996 ◽  
Vol 33 (2) ◽  
pp. 107-118 ◽  
Author(s):  
R. H. Aalderink ◽  
A. Zoeteman ◽  
R. Jovin
Keyword(s):  
Water Quality ◽  
Parameter Uncertainty ◽  
Initial Conditions ◽  
Latin Hypercube Sampling ◽  
Point Sources ◽  
The Other ◽  
Quality Model ◽  
Relative Contribution ◽  
Input Variables ◽  
Input Uncertainties

Within the restoration plan for the river Vecht, the linked flow-water quality model DUFLOW has been applied to describe the behaviour of heavy metals. The model has been used to predict the effects of a number of scenarios for improvement of water quality. In this paper an analysis of the input uncertainty and the effect upon the resulting uncertainty in the output is presented. Both the influence of parameter uncertainty and the uncertainty in the other input variables as: boundary conditions, loading from point and non-point sources, and initial conditions, has been studied. From reported ranges in literature an estimate of the parameter uncertainty has been made. The uncertainty within the other input variables has been assessed from available data. Through Monte Carlo simulation, using Latin Hypercube sampling the resulting uncertainty in the model predictions has been determined. From the uncertainty analysis it appeared that it was not possible to discriminate between the predicted impacts of some of the scenarios. Both the uncertainty in the parameters and in the loading of the system contributed to the overall model uncertainty, although their relative contribution differed going from south to north in the system.

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