A multiple-input single-output model for flow forecasting Academic Article uri icon

abstract

  • A Multiple-input single-output time-invariant, non-linear model, based on a black-box systems approach, was used for flow forecasting during monsoon flood events using daily data. The model consists of a non-linear component representing the immediate and moderately delayed responses and a linear component representing the delayed response of the catchment. It is based on a structure originally proposed by Muftuoglu, R.F. (New models for nonlinear catchment analysis. J. Hydrol. 73 (1984) 335-357; Monthly runoff generation by non-linear models. J. Hydrol. 125 (1991) 277-291). The spatial variation in rainfall amounts is incorporated in the model by treating the rainfall as separate lumped inputs. The model, in its non-parametric form, is first calibrated on various data sets stacked together and then verification tests are performed on different data sets. The results show that the model is capable of forecasting flows with high efficiencies for the data used, indicating that it provides a low cost alternative model for use in sparse-data scenarios and for small-one-off projects.

published proceedings

  • Journal of Hydrology

author list (cited authors)

  • Kothyari, U. C., & Singh, V. P.

citation count

  • 22

complete list of authors

  • Kothyari, UC||Singh, VP

publication date

  • June 1999