Evaluation of the Velocity Parameter Estimation Methods in a Geomorphological Instantaneous Unit Hydrograph (GIUH) Model for Simulating Flood Hydrograph in Ungauged Catchments.

Autor: Grum, B., Abebe, B. A., Degu, A. M., Goitom, H., Woldearegay, K., Hessel, R., Ritsema, C. J., Geissen, V.
Předmět:
Zdroj: Water Resources Management; Jan2023, Vol. 37 Issue 1, p157-173, 17p
Abstrakt: Runoff data is crucial for development of water resources. Runoff data is however rarely available for ungauged catchments, especially in developing countries. Geomorphological instantaneous unit hydrographs (GIUH) models can be used for predicting runoff in poorly gauged catchments, but a challenge with these models is estimating the dynamic velocity parameter. In this study, three GIUH models were developed based on estimation of flow velocity using calibration of Manning's n (GIUH-cal), peak discharge (GIUH-pq) and 30-min rain intensity (GIUH-I30). The objectives of this study were to (a) assess suitability of a GIUH model for simulating runoff in Gule catchment, northern Ethiopia and (b) evaluate performance of three velocity parameter estimation methods in simulating runoff using GIUH models. Runoff hydrographs of the GIUH models matched well with observed hygrographs for most rain events. The GIUH-cal model had the best performance, 18 out of 20 rain events resulting in Nash–Sutcliffe model efficiency (NSE) values of 0.53 to 0.95. The GIUH-pq and GIUH-I30 models performed satisfactorily with 12 of the 20 rain events resulting in NSE values greater than 0.50. Overall, the GIUH models underestimated peak discharge compared to observed data. The GIUH models were moderately sensitive to changes in flow velocity. Peak discharge and time to peak discharge were highly sensitive to changes in flow velocity. The developed GIUH models could be used for simulating flood hydrographs of the Gule catchment. Particularly, the GIUH-I30 model will be very useful for estimating direct surface runoff in the absence of streamflow data. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index