Abstract:
This study addresses the issues arising in
hydrological modelling due to the gaps in hydrological and
meteorological data in the Maduru Oya River Basin in
Sri Lanka by investigating the correlation between the
Welikanda streamflow data of the Maduru Oya with the
neighbouring Batticaloa rainfall data using Pearson and
Spearman’s statistical tests. The relatively strong correlation
coefficients (i.e., Pearson: 0.74, Spearman: 0.61) indicated a
reliable relationship between rainfall and streamflow,
confirming a statistically significant correlation. These results
were supported by significant t-statistics (19.4, 13.6) and very
low p-values (~0), providing strong evidence against random
occurrences of hydrological events. The coefficient of
determination analysis demonstrated that changes in rainfall
could explain 55% of the variation in streamflow. Both datasets
from Welikanda and Batticaloa gauging stations were used to
develop an event-based HEC-HMS model, which demonstrated
very good performance both in calibration (NSE: 0.96, RSR:
0.20, PBIAS: 5.17, R2: 0.96) and validation (NSE: 0.86, RSR:
0.37, PBIAS: -4.23, R2: 0.87). These findings have significant
implications for water and flood management in the Maduru
Oya River Basin, providing insights to overcome data scarcity
in similar studies while emphasizing the importance of focused
analysis in hydrological simulations in data-poor regions.
Citation:
A. W. Nab, H. Ratnasooriya, J. Bamunawala and L. Rajapakse, "Bridging the Gap: Advancing Hydrological Modelling for the Maduru Oya River Basin," 2023 Moratuwa Engineering Research Conference (MERCon), Moratuwa, Sri Lanka, 2023, pp. 207-212, doi: 10.1109/MERCon60487.2023.10355405.