Abstract
A method for reaching longitudinal dispersion coefficient accounting sinuosity effects is suggested. The proposed
method was verified using 43 sets of measured field data from previous study were collected from 30 streams and these
data were chosen depends on characteristics availability (flow parameters, fluid properties and Sinuosity). Statistical
programs namely MINITAB and SPSS were used to derive the relationship between measured longitudinal dispersion
coefficient and geometric parameters were used. The new predicted formulas of the longitudinal dispersion coefficient,
were correlated with a high coefficient compared to the measured data (i.e. R2 = 0.92 and 0.94) excluding and including
sinuosity in the calculations respectively. Comparisons made among 16 other studies of over long period of measured,
experimental, and predicted longitudinal dispersion coefficient from different cross-sectional areas (e.g. triangle,
rectangular, full and half full circular pipe, parabolic, narrow and deep and, wide and shallow).
The correlation coefficients increased when including irregularities (Sinuosity) term of the natural streams of different
cross section in the calculations. Also, the second equation which including sinuosity is more precisely describing the
longitudinal dispersion in the rivers and streams. Thus, we strongly prefer and recommend using the second equation for
better result than the one not including sinuosity especially for mixing in the case of brine and wastewater discharge.
The two results were compared for RMSE (30.1, 24.0, 51.0, 48.9, 90.6, and 70.0) to previous studies e.g. Kashefipour
and Falconer (2002), Deng et al. (2001), Seo and Cheong (1998), and Iwasa and Aya (1991) respectively.
method was verified using 43 sets of measured field data from previous study were collected from 30 streams and these
data were chosen depends on characteristics availability (flow parameters, fluid properties and Sinuosity). Statistical
programs namely MINITAB and SPSS were used to derive the relationship between measured longitudinal dispersion
coefficient and geometric parameters were used. The new predicted formulas of the longitudinal dispersion coefficient,
were correlated with a high coefficient compared to the measured data (i.e. R2 = 0.92 and 0.94) excluding and including
sinuosity in the calculations respectively. Comparisons made among 16 other studies of over long period of measured,
experimental, and predicted longitudinal dispersion coefficient from different cross-sectional areas (e.g. triangle,
rectangular, full and half full circular pipe, parabolic, narrow and deep and, wide and shallow).
The correlation coefficients increased when including irregularities (Sinuosity) term of the natural streams of different
cross section in the calculations. Also, the second equation which including sinuosity is more precisely describing the
longitudinal dispersion in the rivers and streams. Thus, we strongly prefer and recommend using the second equation for
better result than the one not including sinuosity especially for mixing in the case of brine and wastewater discharge.
The two results were compared for RMSE (30.1, 24.0, 51.0, 48.9, 90.6, and 70.0) to previous studies e.g. Kashefipour
and Falconer (2002), Deng et al. (2001), Seo and Cheong (1998), and Iwasa and Aya (1991) respectively.
| Original language | English |
|---|---|
| Pages (from-to) | 77-84 |
| Number of pages | 8 |
| Journal | International Journal of Sustainable Water and Environmental Systems |
| Volume | 2 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2011 |
Subject classification (UKÄ)
- Water Engineering
- Other Social Sciences
Free keywords
- Statistical Analysis.
- SPSS
- MINITAB
- Sinuosity
- Fluid properties
- Flow parameters
- Longitudinal dispersion coefficient