i-manager Publications

Statistical Analysis of Stage-Discharge Data for Development of Rating Curve Using Non-Linear Regression Approach

N. Vivekanandan*

Assistant Research Officer, Central Water and Power Research Station, Pune, Maharashtra, India.

Periodicity:February - April'2016
DOI : https://doi.org/10.26634/jfet.11.3.5923

Abstract

Development of Stage-Discharge Rating Curve (SDRC) is of utmost importance for reliable planning, design and management of water resource projects. The SDRC is time dependent and very often exhibits a random phenomenon with fluctuation. For establishing the SDRC, Non-Linear Regression Approach (NLRA) is widely applied to many gauging sites worldwide for many decades. The SDRC is based on power equation that is used to establish a relationship between stage (i.e., water level) and discharge, whose variables can be determined by the method of least squares. In this paper, a study on development of SDRCs for Aamdabad, Nighoje and Wegre gauging sites located in the upper Bhima basin upto Ujjani reservoir is carried out. The performance of the NLRA used for developing the SDRCs is evaluated by correlation coefficient and the mean absolute percentage error. The paper presents the procedures adopted in the development of SDRCs using NLRA and the results obtained thereof.

Keywords

Correlation, Discharge, Mean Absolute Error, Rating Curve, Water Level.

How to Cite this Article?

Vivekanandan, N.(2016). Statistical Analysis of Stage-Discharge Data for Development of Rating Curve Using Non-Linear Regression Approach. i-manager’s Journal on Future Engineering and Technology, 11(3), 25-30. https://doi.org/10.26634/jfet.11.3.5923

References

[1]. Akbarzadeh, R.M., Ghezelsofloo, A.A., Hajibigloo, M., Saeed, R., and Khodashenas, R.S. (2014). “Selecting the most appropriate method of basin sediment estimation by sediment rating curves at hydrometric stations (Case study: Atrak basin)”. International Journal of Emerging Technology and Advanced Engineering, Vol. 4(6), pp. 661-671.

[2]. Arun Goel, (2011). “ANN based approach for predicting rating curve of an Indian River”. ISRN Civil Engineering, Article ID 291370, pp.1-4.

[3]. Clarke, R.T., Mendiondo, E.M., and Brusa, L.C. (2000). “Uncertainties in mean discharges from two large South American rivers due to rating curve variability ”. Hydrological Sciences Journal, Vol. 45 (2), pp. 221 – 236.

[4]. Ghimire Bhola, N.S., and Janga Reddy, M. (2010). “Development of stage-discharge rating curve in river using genetic algorithms and model tree”. International Workshop on Advances in Statistical Hydrology, Taormina, Italy, 23-25 May, pp. 1-11.

[5]. Herschy, R.W. (1999). “Flow Measurements”. Hydrometry: Principles and Practices, 2nd Edition, John Wiley & Sons, England.

[6]. Lang, M., Pobanz, K., Renard, B., Renouf, E., and Sauquet. E. (2010). “Extrapolation of rating curves by hydraulic modelling, with application to flood frequency analysis”. Hydrological Sciences Journal, Vol. 55(6), pp. 883–898.

[7]. Lenzi, M.A., Mao, L., and Comiti, F. (2003). “Inter annual variation of suspended sediment load and sediment yield in an alpine catchment”. Hydrological Sciences Journal, Vol. 48 (6), pp. 899-915.

[8]. Petersen-Overleir, A. (2004). “Accounting for heteroscedasticity in rating curve estimates”. Journal of Hydrology, Vol. 292 (1-4), pp.173–181.

[9]. Petersen-Overleir, A. (2006). “Modelling stagedischarge relation-ships affected by hysteresis using the Jones formula and nonlinear regression”. Hydrological Sciences Journal, Vol. 51 (3), pp. 365–388.

[10]. Petersen-Overleir, A. (2008). “Fitting depthdischarge relationships in rivers with floodplains”. Hydrology Research, Vol. 39 (5-6), pp. 369–384.

[11]. Vivekanandan, N. (2015). “Comparison of BPN and RBF Neural Networks for Prediction of Wind Speed”. International Journal of Computer and Modern Technology, Vol. 3 (1), pp 111-123.

[12]. WMO, (1986). “Level and discharge measurements under difficult conditions”. Operational Hydrology Report No. 24, WMO Manual No. 650, World Meteorological Organization, Geneva.

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Pdf	35	35	200	20
Online	35	35	200	15
Pdf & Online	35	35	400	25

Statistical Analysis of Stage-Discharge Data for Development of Rating Curve Using Non-Linear Regression Approach

Abstract

Keywords

How to Cite this Article?

References

If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Options for accessing this content: