According in a GIS and translated into MIKE21. In

According to past studies, the
simulation of runoff events with high hydraulic risk has posed many challenges
for policymakers, environmentalists and engineers around the world. Using 1-D
modelling to predict flood risk from different return period events or multiple
land use and climate change scenarios are common(Horritt & Bates, 2002).

It is noticeable that the use of the Digital Elevation
Model (DEM) in the creation of flood models have reached an important role of
the topographic and hydrological analysis of basin data, since it represents a
series of elevations in the basin at regularly spaced intervals. This removes
the assumption that the basin or area is a flat surface without contours(Heimhuber et al., 2015).

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In case study on flood
risk and flood prediction using GIS and the model of hydrodynamic presented the
possibility of using DEM controlled in a GIS and translated into MIKE21. In the
study, different scenarios were checked out, and results were translated into
the GIS environment for flood visualization and analysis during a 100-year
flood return period(Ntajal et al., 2017). However, Jagadish
Prasad Patraa, Rakesh Kumara and Pankaj Manib pointed out that there was no
real way to calibrate the simulations from the modelling output, as flood and
stage data for the floods were rarely recorded and compared between the MIKE21
and MIKE1 results, the first being an improvement of the last one(Prasad, Kumar, & Mani, 2016).

In a research
conducted by Sarawut Jamrussri and Yuji Toda on the hydraulic models and GIS
for the study of the Mae Klong River in Thailand. Flow frequency analysis was
used in the creation of a flood risk map. The study also showed that the
simulation results were correctly presented in GIS and DTM format, using
contour and height data from the river point. Sarawut Jamrussri and Yuji Toda conclude
their study by suggesting that more studies be done in large basins, dividing
them into sub-basins and introducing the network link to integrate them to have
a general view of the basin. Runoff from floodplains, fluvial canals and
artificial structures are important factors in the study of the prediction of
runoff flow patterns, the researchers added. rainwater in upstream areas and
not stable(Jamrussri
& Toda, 2017).

 

2.1 Analysing methods

HMS uses a project name as the identifier for a
hydrological model. A HMS project must have the following components before it
can be executed: a basin model, a climate model and control specifications. The
characteristics of the basin model and basin were created as a lower map file
imported into the HMS from the data derived from HEC-HMS for model simulation(Oleyiblo & Li, 2010). The observed
rainfall and discharge data were used to create the climate model using the
User Indicator Weight Method (UIWM), and then the control specification
template was created(Moya Quiroga, Kure, Udo, & Mano, 2016). The control
specifications determine the time model for the simulation; its characteristics
are: a start date and time, a date and time of completion, and a calculation
time step(Kawasaki et al., 2017). To operate the
system, the basin model, the climate model and the control specifications were
combined. The historical data observed from precipitation stations representing
each sub-basin and one measuring station in the river basin and precipitation
stations representing each sub-basin and one measuring station in the basin
were used to calibrate the model. check. One-time step per hour was used for
the simulation according to the time interval of the observed data(Hashemyan et al., 2015).

Figure
1. Model representation of the Ravine Lan Couline watershed in HEC-HMS.

 

The HEC-HMS model for flood simulation
uses a graphical interface to build the semi-distributed basin model. For each
sub-basin of the main basin, the hydrological model is forced using a unit hydrograph(Bates & Roo, 2000). First, using the kriging method, spatial rainfall distributions
were generated from the time values recorded in the rain gauge station located
at the top of the river. Then, for each sub-basin, rainfall series per hour
were calculated. The Soil Conservation Service curve number (SCS-CN)  method was used to calculate the runoff
volumes in the precipitation-runoff model(Hashemyan et al., 2015). Calculation of weighted curve number (WCN) is shown by

Where, WCN is weighted curve number, Ai
is area for ith land use type and CNi is curve number for ith land use type(Plate, 2002).

The HEC-RAS model was implemented using the cross
sections to provide channel width and bed elevations. These sections were
extended on both sides of the channel using DEM derived from LiDAR to provide a
floodplain topography(Mancusi & Abbate, 2017). The section was
then described by 5-10 points on each side of the canal coinciding with
significant topographic features such as slope failures. The elevation profile
of the bed and examples of cross sections used in the HEC-RAS model are given
in following figure(Heimhuber et al., 2015).

Figure 2. Cross-sectional profiles of the river and
its flood plains