Calibrating pollutant dispersion in 1-D hydraulic models of river networks

Abstract

The objective of this article is to investigate the major issues associated with the calibration of the pollutant dispersion in 1-D hydraulic models applied to river networks, especially large, complex, artificialized ones where ecological and socio-economical threats are important. Such issues are illustrated and discussed using the results of five fluorescent tracer experiments conducted in contrasted open-channel systems, ranging from a simple trapezoidal canal to a more complex river network. Experimental dispersion values were quantified using both the change of moment method and a simple fit-by-eye procedure for eight river reaches with homogeneous hydraulic conditions and an achieved tracer mixing and dispersive equilibrium. Since dispersion coefficient values depend on the assumed dispersion model, ideally they should be calibrated using the same model in which they are to be used, as was done in this study. We also derived concurrent longitudinal dispersion values using the velocity field measured by hydro-acoustic profilers (ADCP), which appears as a promising and cost-efficient technique for documenting dispersion in large river systems. It appears that the formulae for which the fit was mainly based on the cross-sectional aspect ratio are generally more appropriate for field data than those which are sensitive to the velocity to shear velocity ratio. The interpretation of complex dispersion and mixing processes, along with the selection of relevant dispersion coefficient predictors are key to minimizing errors in the numerical simulation of pollution dynamics in river networks.

Spatial and Seasonal Dynamics of Water Environmental Capacity in Mountainous Rivers of the Southeastern Coast, China

“…The rapidly flowing rivers are dominant in mountain areas due to elevation differences that transverse velocity gradient which is much greater than vertical velocity gradient in rivers. Effects of longitudinal dispersion of contaminant are negligible compared to advection (the longitudinal dispersion coefficient E = 0) [ 34 , 35 , 36 ], then the model can be expressed as: where is the concentration of the water quality (mg/L); is the flow velocity (m/s) that can be calculated using the Manning equation; is the time of river water flowing through from the headwater to somewhere (s); is the distance that river water flows through in time (m), , and is the pollutant degradation coefficient ( d −1 ).…”

Water Supply-Water Environmental Capacity Nexus in a Saltwater Intrusion Area under Nonstationary Conditions

“…The water flow in these areas is always simulated based on Saint-Venant equations describing the mathematical translation of the laws of conservation of mass and momentum. The equations can be formulated, as shown in Equations (7) and (8) [52,[66][67][68][69]:…”

Evaluating flow management as a strategy to recover an endangered sturgeon species in the Upper Missouri River, USA

“…The parameter capturing the magnitude of shear dispersion in the HEC-RAS AD model is the longitudinal dispersion coefficient, K. As used in the 1D AD modelling approach, K represents the complex, three-dimensional transport processes that spread passive particles along the transport pathway; accurate estimation of K is therefore critical for accurate results. Three approaches may be used for estimating K: (a) experimental measurement (e.g., tracer studies), (b) empirical relations, and (c) application of theoretical equations (Carr & Rehmann, 2007;Launay et al, 2015). HEC-RAS employs the theoretical approach proposed by Fischer (1973) but permits specification of K values determined by other means.…”