Projecting turbidity levels in future river flow: a mathematical modeling approach

Wickramaarachchi, T. N.; Ishidaira, Hiroshi; Magome, Jun; Wijayaratna, Nimal

doi:10.4038/engineer.v48i1.6849

Cited by 1 publication

(1 citation statement)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hydrologic models have been widely used for decades as a tool applied in hydrological assessments, including impact assessments on water resources due to human activities and climate change [1], [2], [3], [4], [5], [6]. In distributed hydrologic modelling, the spatial variability of catchment characteristics is taken into account; however, distributed hydrologic models require huge amount of data and identification of considerable number of model parameters which possibly limit their applicability for operational purposes.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Single and Multi-Objective Calibration in Rainfall-Runoff Modelling

Wickramaarachchi

Rathnayake²

2021

Engineer

Self Cite

View full text Add to dashboard Cite

Hydrologic modelling is widely used as a tool for making decisions and predictions in planning and managing water resources. Successful application of a hydrologic model depends upon careful calibration and validation using appropriate performance measures in satisfying corresponding performance evaluation criteria. Performance of MIKE 11 NAM rainfall runoff model was assessed using four calibration objectives and their different combinations, as applied to upper Gin catchment, Sri Lanka. The four calibration objectives measured different aspects of hydrograph: good water balance, good overall agreement of the shape of the hydrograph, good agreement for peak flows, and good agreement for low flows. Their numerical performance was measured using four objective functions from which fifteen calibration schemes were formed (four single objective schemes and eleven multi-objective schemes). Using aggregated distance measure, equal weights were assigned to the four objective functions. Shuffled complex evolution algorithm was used to solve the multiple calibration objective problems. Model performance was evaluated using three criteria: Nash-Sutcliffe coefficient (NSE), percent bias (PBIAS) and coefficient of determination (R 2 ). Results revealed significant trade-offs between the objective functions, highlighting that no single calibration objective was able to depict all the aspects of the hydrograph simultaneously. However, multi-objective calibration yielded more accurate and consistent simulations covering different aspects of the hydrograph, simultaneously with overall best performance shown for combination of the four objective functions satisfying all the performance evaluation criteria (NSE=0.56, R 2 = 0.56, PBIAS=17%), compared to the single-objective calibration. Instead of using R 2 alone, use of the corresponding regression slope as a weighing factor of R 2 was recommended following further analysis of simulation results.

show abstract