Abstract

Northern Vietnam is a region prone to heavy flash flooding events. These often have devastating effects on the environment, cause economic damage and, in the worst case scenario, cost human lives. As their frequency and severity are likely to increase in the future, procedures have to be established to cope with this threat. As the prediction of potential flash floods represents one crucial element in this circumstance, we will present an approach that combines the two models KINEROS2 and HEC-RAS in order to accurately predict their occurrence. We used a documented event on 23 June 2011 in the Nam Khat and the larger adjacent Nam Kim watershed to calibrate the coupled model approach. Afterward, we evaluated the performance of the coupled models in predicting flow velocity (FV), water levels (WL), discharge (Q) and streamflow power (P) during the 3–5 days following the event, using two different precipitation datasets from the global spectral model (GSM) and the high resolution model (HRM). Our results show that the estimated Q and WL closely matched observed data with a Nash–Sutcliffe simulation efficiency coefficient (NSE) of around 0.93 and a coefficient of determination (R2) at above 0.96. The resulting analyses reveal strong relationships between river geometry and FV, WL and P. Although there were some minor errors in forecast results, the model-predicted Q and WL corresponded well to the gauged data.

Highlights

  • Unlike paleoflood, flash floods (FF) occur in small streams [1] and are linked to short, but extreme rainfall events [2]

  • It is important to note that the forecast rainfall by means of the KNIEROS2 model [41,42] will produce the forecast river hydrographs, depth and initial flow, which will be used as inputs for the HEC-RAS and generate the forecast water levels or stages (WLs), flow velocity (FV) and energy curves for the FF

  • To accomplish the study objective of flash flood prediction, the FV, the WLs and the flow energy are considered to be influential with respect to FF occurrence [9,54,55]

Read more

Summary

Introduction

Flash floods (FF) occur in small streams [1] and are linked to short, but extreme rainfall events [2]. Much previous research has suggested approaches to mitigate the impacts of FFs through the early identification of FF occurrences (time and location) or their forecast [7,8,9,10,11,12]. This is crucial information for the local people, as such information will help them to protect themselves from these floods [13]. This work was done by coupling the KINEROS2 (kinematic runoff and erosion) and HEC-RAS

Objectives
Methods
Results
Conclusion

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.