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.

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).

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

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.

scholarly journals A simple water quality model as a tool for the evaluation of alternative river basin management plans

2013 ◽  
Vol 16 (1) ◽  
pp. 1-8
Keyword(s):  
Water Quality ◽  
River Basin ◽  
River Basin Management ◽  
Water Quality Model ◽  
Point Sources ◽  
Water Bodies ◽  
Quality Model ◽  
Basin Management ◽  
River Basin District ◽  
Management Plans

<p>A key component in the implementation of Water Framework Directive is the development of a river basin management plan for each river basin district. Water quality models are important tools to test the effectiveness of alternative management plans on the water quality of the respective water bodies. The main objective of the present study was to develop and demonstrate the use of a rather simple water quality model as a tool for the evaluation of alternative water management scenarios for the river basin district of Evrotas. Furthermore an extension of the water quality model based on Monte Carlo simulation to provide for uncertainty identification is also exhibited. The model is based on the basic principles of the Streeter-Phelps model. A hierarchical approach was developed in order to delineate a complex hydrographic network into a series of water bodies being connected by convective terms. The pollution loads which were used as input data were related both to point sources and non-point sources. Based on the results a substantial removal of organic carbon load originating from the industrial activities is needed in order to achieve high dissolved oxygen concentrations throughout the entire hydrosystem even at the dry period.</p>

Approaches to Evaluate Water Quality Model Parameter Uncertainty for Adaptive TMDL Implementation1

2007 ◽  
Vol 43 (6) ◽  
pp. 1499-1507 ◽  
Author(s):  
Craig A. Stow ◽  
Kenneth H. Reckhow ◽  
Song S. Qian ◽  
Estel Conrad Lamon ◽  
George B. Arhonditsis ◽  
...  
Keyword(s):  
Water Quality ◽  
Parameter Uncertainty ◽  
Water Quality Model ◽  
Quality Model ◽  
Model Parameter ◽  
Model Parameter Uncertainty

scholarly journals Parameter uncertainty and sensitivity analysis of water quality model in Lake Taihu, China

2018 ◽  
Vol 375 ◽  
pp. 1-12 ◽  
Author(s):  
Long Jiang ◽  
Yiping Li ◽  
Xu Zhao ◽  
Martin R. Tillotson ◽  
Wencai Wang ◽  
...  
Keyword(s):  
Water Quality ◽  
Sensitivity Analysis ◽  
Parameter Uncertainty ◽  
Lake Taihu ◽  
Water Quality Model ◽  
Quality Model ◽  
Uncertainty And Sensitivity Analysis

Point Sources of Toxic Organics to the Upper St. Clair River

1986 ◽  
Vol 21 (3) ◽  
pp. 433-446 ◽  
Author(s):  
Lawrence King ◽  
Griff Sherbin
Keyword(s):  
Water Quality ◽  
Point Sources ◽  
The Other ◽  
Industrial Property ◽  
Trace Organics ◽  
Near Shore ◽  
Toxic Organics ◽  
The Impact ◽  
Intake Water ◽  
Screening Survey

Abstract A one-day effluent screening survey was conducted in the Sarnia area to characterize point sources and to determine possible sources of the so called "toxic blob" found on the bottom of the St. Clair River. Two of Dow Chemical's 1st Street sewers were shown to contain the same spectrum of compounds found in these perchloroethylene puddles and were the principle sources of perchloroethylene, carbon tetrachloride, hexachlorobenzene, hexachloroethane and hexachlorobutadiene. Other effluents did not contain the same fingerprint or mixture of trace organics. Additional sources of toxic organics were: the Polysar 72″ sewer, the Dow Chemical 3rd and 4th Street sewers and 1st Street 54″ sluice and the Township Ditch which drains industrial property and a number of waste disposal sites in the area. The Dow Chemical Landfill on Scott Rd. (periodic discharge) was a source of volatile organics, trichlorobenzene, hexachlorobutadiene and the chlorophenoxy acid 2,4-D. Esso Petroleum, Esso Chemical, the Sarnia WPCP and Suncor were minor sources of trace contaminants. The impact of upstream discharges on near-shore water quality was evident at Suncor which is located downstream of the other point sources and which had the most contaminated intake water.

Propagation of uncertainty in diffuse pollution into water quality predictions: application to the River Dender in Flanders, Belgium

2005 ◽  
Vol 51 (3-4) ◽  
pp. 347-354 ◽  
Author(s):  
V. Vandenberghe ◽  
A. van Griensven ◽  
W. Bauwens ◽  
P.A. Vanrolleghem
Keyword(s):  
Water Quality ◽  
Uncertainty Analysis ◽  
Management Practices ◽  
Stream Water ◽  
Latin Hypercube Sampling ◽  
Diffuse Pollution ◽  
Nitrate Content ◽  
Stream Water Quality ◽  
Quality Model ◽  
Propagation Of Uncertainty

The uncertainty of water quality predictions caused by uncertainty in the inputs related to emissions of diffuse pollution is analysed. An uncertainty analysis of the effects of diffuse pollution is essential to compare the cost and benefits of measures to lower those emissions. We focus on diffuse nitrate pollution due to fertiliser use. Using an efficient Monte Carlo method and Latin Hypercube sampling, the contribution to the overall uncertainty by each of the inputs is calculated. The modelling environment is ESWAT, an extension of SWAT, which allows for integral modelling of the water quantity and quality processes in river basins. The diffuse pollution sources are assessed by considering crop and soil processes. The crop simulations include growth, uptake of water and nutrients and several land management practices. The in-stream water quality model is based on QUAL2E. The spatial variability of the terrain strongly affects the non-point source pollution processes. The methodology is applied to the Dender basin in Belgium. Eight inputs have significant influence on the time that the nitrate content in the river is higher than 3 mg/l. The uncertainty analysis indicated wide uncertainty bounds (95% percentile bounds differ up to ±50% from the average NO3 predictions).

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