The Early-Warning System to Predict Sediment Flux in the Mountain Basin During Typhoon Events
Part Of
Lecture Notes in Mechanical Engineering
Start Page
731
End Page
741
ISSN
21954356
ISBN (of the container)
9789819760084
ISBN
9789819760084
Date Issued
2024
Author(s)
DOI
10.1007/978-981-97-6009-1_66
Abstract
The watershed sedimentation could be determined as the severe natural disaster source. The differences between the sediment yield estimation and the real situation are large due to the inadequacy of on-site measurement data. A robust early-warning approach that encloses both the physical mechanism and statistical analysis was proposed to predict the sedimentation and improve the deficit on the current methods. This three-phase early-warning system includes, Phase I (data collection), Phase II (data generation), and Phase III (AI prediction). In Phase I, HEC-HMS was applied to transform the measured precipitation data to the flow discharge from different sub-catchments. The empirical formulas of landslide volume and soil erosion were then adopted to provide reasonable boundary conditions to Phase II. A 2D model, SRH-2D, was verified with on-site data and conducted to obtain simulated data for the temporal variation of the sediment flux with different storm events. The simulated data can be the input for Phase III to train and test the artificial neural networks. Three prediction models presented a good performance from 1-h to 6-h lead time comparing to the observation. Even though the relatively poor performance was shown in the higher sediment discharge and the difference was gradually increasing with the longer forecast lead time, the prediction models still provide the proper prediction trend, especially the forecast lead time from 1-h to 3-h. This approach shows a significant improvement on the sediment prediction due to the sufficient simulated data, and can be well-applied to better manage sediment problems in advance.
Event(s)
23rd International Association for Hydraulic Environmental Engineering and Research-Asia Pacific Division, physical conference, IAHRAPD 2022, 14 December 2022 - 17 December 2022, Chennai
Subjects
ANNs
Early-warning system
Multi-phase approach
Sediment flux
Typhoon events
Publisher
Springer Science and Business Media Deutschland GmbH
Type
conference paper