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Simulation of flood risk area in Kelantan watershed, Malaysia using numerical model
Karim Ghorbani1, Aimrun Wayayok2, Ahmad Fikri Abdullah3.
Flood events have recently increased and caused extensive damages to the agricultural
area and infrastructures, despite enormous efforts to decrease this hazard. Modeling of
runoff can be a suitable approach to determine the effective factors in flooding, and to
explore reasonable solution and thus to be able reduce hazard on watersheds. The current
work attempted to derive basin and sub-basins, stream network, aspect, slop and all
relevant physiographic parameters of Kelantan watershed in order to estimate depth of
runoff using DEM data , satellite images and field study. In addition, the maximum rainfall
intensity of all the meteorological stations were extracted and the interpolation of the
values obtained, led to derive a contour map as rainfall intensity for the watershed. Soil
Conservation Service (SCS) model was employed to calculate the surface flows, and to
derive the flood hydrograph for all the sub-basins at the return periods of 5,10,25,50,100,
considering to the Curve Number (CN) is a function of land use, soil, and primary moisture
content. HEC-HMs model was calibrated for the study area using observed storm rainfall
and recorded floods at the number of hydrometric stations. A good agreement was
obtained between simulated and observed data with a correlation of 82%. Calibrated
model was used to simulate depth of runoff in different return period that led to derive flood
risk maps for Kelantan watershed. Results obtained revealed that flooding could be
moderated and managed within a number of the sub - basins through implementing a
technical scheme, depending on characteristic of the sub- basin, and its effect on the
flood peak.
Affiliation:
- Universiti Putra Malaysia, Malaysia
- Universiti Putra Malaysia, Malaysia
- Universiti Putra Malaysia, Malaysia
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q3 (Engineering (all)) |
Additional Information |
SJR (0.191) |
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