Flood prediction using parameters calibrated on limited discharge data and uncertain rainfall scenarios

Content Provider	Scilit
Author	Reynolds, J. E. Halldin, S. Seibert, J. Xu, Chong-Yu Grabs, T.
Copyright Year	2020
Description	Discharge observations and reliable rainfall forecasts are essential for flood prediction but their availability and accuracy are often limited. However, even scarce data may still allow adequate flood forecasts to be made. Here, we explored how far using limited discharge calibration data and uncertain forcing data would affect the performance of a bucket-type hydrological model for simulating floods in a tropical basin. Three events above thresholds with a high and a low frequency of occurrence were used in calibration and 81 rainfall scenarios with different degrees of uncertainty were used as input to assess their effects on flood predictions. Relatively similar model performance was found when using calibrated parameters based on a few events above different thresholds. Flood predictions were sensitive to rainfall errors, but those related to volume had a larger impact. The results of this study indicate that a limited number of events can be useful for predicting floods given uncertain rainfall forecasts.
Related Links	https://www.tandfonline.com/doi/pdf/10.1080/02626667.2020.1747619?needAccess=true
Ending Page	1524
Page Count	13
Starting Page	1512
ISSN	02626667
e-ISSN	21503435
DOI	10.1080/02626667.2020.1747619
Journal	Hydrological Sciences Journal
Issue Number	9
Volume Number	65
Language	English
Publisher	Informa UK Limited
Publisher Date	2020-07-03
Access Restriction	Open
Subject Keyword	Journal: Hydrological Sciences Journal Water Science and Technology Floods Rainfall Forecasts Rainfall–runoff Modelling Event-based Calibration Ungauged Basins Value of Information
Content Type	Text
Resource Type	Article
Subject	Water Science and Technology