Calibration of a water-quality model for low-flow conditions on the Red River of the North at Fargo, North Dakota, and Moorhead, Minnesota, 2003

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).

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

Water Science & Technology ◽

10.2166/wst.2002.0743 ◽

2002 ◽

Vol 46 (11-12) ◽

pp. 231-236 ◽

Cited By ~ 2

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.

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