Potential predictability of suspended sediment concentration in the data constrained regions of the Mahanadi River basin, Eastern India

ABSTRACT

The study proposes an efficient method to evaluate the suspended sediment concentration (SSC) relative to the traditional sediment rating curves (SRC) for gauged stations and subsequently to predict the SSC in ungauged stations of a major river basin. Multiple environmental control parameters were collected from 16 stations along the Mahanadi River basin (MRB) during the monsoon season. The hysteresis behaviour of SSC is assessed and therefore considered for modelling SSC using linear mixed-effects modelling (LMM). A basin-scale rating model is proposed using principal component analysis and stepwise multiple linear regression for estimating the unmeasured SSC. The findings show that the MRB acts differently in terms of hysteresis, with distinct dilution and flushing regimes in SRC. LMM outscored SRC by nearly doubling the mean covariance and notably reducing the percent bias between observed and predicted data across stations. However, unlike LMM, SRC could not correctly estimate low and high SSCs of ≤ 0.05 g/l and ≥ 1.5 g/l, respectively. The error metrics of the proposed rating model are within acceptable limits for all ungauged stations. Nevertheless, its efficiency varies due to smaller catchment areas, non-linearity in sediment transport with respect to catchment area, and other sampling issues. As a result, compared to other known models applied on the MRB, this model has the lowest error and seems to be the best in predicting monthly SSC.

KEYWORDS:

• Mahanadi river basin
• sediment rating curve
• linear mixed-effects modelling
• principal component analysis
• multiple linear regression
• ungauged catchments

Acknowledgements

The authors gratefully acknowledge the Ministry of Water Resources, Government of India for funding the research project

Disclosure statement

No potential conflict of interest was reported by the author(s).

Conflicts of interest/ Competing interests

The authors have no conflicts of interest to declare that are relevant to the content of this article.

Availability of data and material

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Code availability

Not Applicable.

Additional information

Funding

This study is supported by the Ministry of Water Resources, Government of India, with Grant No: 28/1/2016-R&D/228-245.