Malaysia is blessed with abundance of rainfall that contributes to an average
of 2000-4000 mm a year. With the exception of extreme events, the annual average
may exceed the above average. The consequences are several areas are inundated
during the monsoon periods (Suhaila and Jemain, 2007).
Seasonal floods normally occur during the North-East Monsoon season between
Novembers to March while Southwest Monsoon occur from May to September. The
two inter-monsoon period, in April and October are generally characterized by
variable wind and thunderstorm in the afternoon (Lawal et
al., 2004). Historically, the frequencies of serious flood events reoccur
every three years.
The cause of flooding in Malaysia is the incidences of heavy rainfall and large
concentration of runoffs. Various flood forecasting and warning systems using
advanced hydraulic and hydrological models were used in Malaysia, but were proved
to be inadequate in terms of their ability to predict impending floods (Chan,
1997). In recent years, impacts of extreme events in Malaysia have been
very much highlighted. For example, in December 2006, some parts of Malaysia
were badly hit by flooding which caused most of the areas under water. Flooding
is the most commonly occurring form of natural disaster and it includes both
river flooding and coastal flooding. Floods often cause tremendous damage to
agricultural land and infrastructure such as roads, bridges and buildings.
The flood estimation that involves the development of hydrologic models is
one of the non-structural measures that may help to reduce the amount of damages
incurred. Hydrologists are continuously improving the capability of hydrologic
models to predict accurately the frequency of flood events in a changing climate
(Pamela, 1992; Lawal et al.,
2004; Knebl et al., 2005; Yener
et al., 2006; Yonatan et al., 2009).
In view of the above and severity of the damages caused by extreme events, it is therefore necessary to establish a hydrologic model to simulate flood levels. This is very much necessary for the identification of possible inundated areas, so that a timely warning can be issued to the people in the affected areas. Therefore, it is timely to have more comprehensive scientific understanding of the effects of this ecosystem on the environment, particularly the hydrological regimes. Such information is crucial for the effective and improved management of water and other catchment resources.
As a means of evaluating this approach, a feasibility study has been completed
on the Johor River at Kota Tinggi watershed in Johor, Malaysia. HEC-HMS was
run with the historical rainfall data in order to provide a flood level evaluation
entering a catchment on the Johor river. The results of this study are presented
in this study, which starts with an overview of the methodology used in HEC-HMS
runoff studies. After describing the computer models HEC-HMS that are used in
the study, a description of the Johor river watershed used in the case study
is presented, including its representation in HEC-HMS. Results of the study
are then presented and discussed. The study presents the flood level characteristics
and results of hydrograph modeling for a Kota Tinggi catchment.
MATERIALS AND METHODS
Kota Tinggi catchment in Johor, Malaysia is the largest district with an area
of approximately 3,490 km2. Three rivers namely Sungai Johor, Sungai
Semangar and Sungai Lebak have been selected to be the study site. Sungai Johor
has a drainage length of 122.7 km that covers an area of 2,636 km2.
It originates from Mount Gemuruh that flows through the South-Eastern part of
Johor and finally into the Straits of Johor. The major tributaries are Sayong,
Linggiu, Tiram and Lebam rivers. About 60% of the catchment is undulating highland
rising to a height of 366 m while the remainder is lowland and swampy. The highland
in the north is mainly jungle. In the south a major portion had been cleared
and planted with oil palm and rubber. Reference is made to the Soil Map of Malaya,
for the rate of infiltration and a range of 0.30 to 0.45 in/h were used (Department
of Irrigation and Drainage, 2000). The catchment receives an average annual
precipitation of 2,470 mm and the temperature in the basin ranges from 21 to
32°C. Figure 1 shows a part of Kota Tinggi watershed.
The circled area in Fig. 1a shows the state of Johor which
is located in the Southern part of Peninsular Malaysia and the circle area in
Fig. 1b shows the district of Kota Tinggi, Johor. Figure.
1c shows the Kota Tinggi watershed area where this study was carried out.
Rainfall and runoff of 10 year period from 1997 to 2006 at Rantau Panjang streamflow gauging station and Ladang Pekan in Kota Tinggi rainfall station which is located in the upstream of Johor River are obtained from Department of Irrigation and Drainage, Malaysia (DID). Rainfall was measured by a manual tipping bucket rain gauge which records daily rainfall. The water level was measured continuously using automatic streamflow recorder. Table 1 shows the name and station number.
|| Streamflow and rainfall stations in Kota Tinggi area
|| (a-c) Kota Tinggi watershed area map
In this study, the river gauging station at Rantau Panjang, Kota Tinggi and
the rainfall station at Ladang Pekan are used in the analysis to derive the
observed unit hydrographs of Kota Tinggi watershed. Streamflow records and daily
rainfall are used to analyze the unit hydrographs.
Total watershed area for Kota Tinggi is about 1130 km2. However,
an area of 272 km2 only was taken into analysis. About 58% of the
catchment consists of plantation area which is on hills and patches of log over
forest towards the north of the watershed. The hydrological soil group for this
catchment is group A based on soil composition. The land use of the catchment
is mainly palm oil and rubber plantations, the Runoff Curve Number for this
catchment are estimated based on weighted Curved Number. For constructing curve-number
map (CN), two types of maps, land-use and soil, were used (Noorbakhsh
et al, 2005). The land is mainly plantations for the rural areas
and primary forest.
For the purpose of derivation of the peak flowrate in the observed 3 h unit
hydrographs, tp is calculated first to determine the S value upon
obtaining from the topographic maps. The value of CNw can be calculated using
Eq. 1-4 with CN values obtained from the
standard runoff curve number tables (Bedient and Huber, 1992).
The Qpeak value and tR can then be read out from the 3
h unit hydrographs.
||Adjusted Curve Number based on local catchment condition
||Correction coefficient for Curve Number
||Curve Number, based on soil groups and land cover
||The length of time for the excess rainfall, (hour)
||Peak Attenuation Factor
||Catchment Area (km2 at acre)
||Rainfall excess (mm at inch)
||Discharge value for the event (m3 sec-1, at cfs)
where, tR are shown in Eq. 3:
where, D is duration of excess rainfall, (3 h).
From the SCS Method, the time to peak tp was shown in Eq. 4:
||SCS Lag Time (min)
||Length to divide, feet (m)
||Potential Maximum retention after runoff begins, inches (mm)
||Average catchments slope (%)
Therefore, from the observed unit hydrographs, a master 3 h unit hydrograph
is obtained and the value of tp, tR and QPeak can
be obtained and the corresponding correction coefficient k and CN can
be calculated for the particular catchment. Once the correction coefficient
cfn are determined then the estimation of runoff for different land use can
be estimated. By using SCS Unit Hydrograph method and the convolution matrix
procedure the required synthetic flood hydrographs are calculated.
PROGRESS AND DEVELOPMENT OF HYDROLOGICAL MODEL: HEC-HMS
The Hydrologic Modeling System (HEC-HMS) is designed to simulate the precipitation-runoff
processes of watershed systems. It is designed to be applicable in a wide range
of geographic areas to solve the widest possible range of problems. This includes
large river basin, water supply and flood hydrology and small urban or natural
watershed runoff. In this model, interception, evaporation and infiltration
processes in a catchment are determined from loss components while runoff processes
are computed as the pure surface routing using transform component (Yusop
et al., 2007). The initial and constant methods correspond to the
interception and depression storages with an initial loss. All other losses
were assumed to follow a constant loss rate.
Hydrographs produced by the program are used directly or in conjunction with
other software for studies of water availability, urban drainage, flow forecasting,
future urbanization impact, reservoir spillway design, flood damage reduction,
floodplain regulation and systems operation. Knebl et
al. (2005) integrated different model to forecast flood on a regional
scale. The model consists of a rainfall-runoff model (HEC-HMS) that converts
precipitation excess to overland flow and channel runoff, as well as a hydraulic
model (HEC-RAS) that models unsteady state flow through the river channel network
based on the HEC-HMS-derived hydrographs.
The HEC-HMS program is a generalized modeling system capable of representing
many different watersheds. A model of the watershed is constructed by separating
the hydrologic cycle into manageable pieces and constructing boundaries around
the watershed. Any mass or energy flux in the cycle can then be presented with
a mathematical model. In most cases, several model choices are available for
representing each flux. Zorkeflee et al. (2009)
analyzed the impact of land use change to hydrologic behavior of Sungai Kurau
Basin and by using the Geographical Information System (GIS) and HEC-HMS model
for catchments management. Each mathematical model included in the program is
suitable in different environments and under different conditions. Making the
correct choice requires knowledge of the watershed, the goals of the hydrologic
study and engineering judgment (USACE-HEC, 2006). For
example, (Yener et al., 2006) use HEC-HMS in event
base hourly simulations and runoff scenarios using intensity duration frequency
curves for modeling studies in Yuvacik Basin, Turkiye. In this study, Yuvacýk
Basin is selected as the study area and basin parameters (infiltration and baseflow)
are calibrated using the rainfall-runoff data of the basin that are collected
by 8 rainfall and 3 runoff stations for 2001-2005 period.
In some of the application case, the capabilities of the HEC-HMS for rainfall
simulation have been exploited to describe single events on which the rating
curves to be estimated were tested. Thus continuous simulation are not performed
and modeling is limited to single events (Pistocchi and Mazzoli,
2002). Anderson et al. (2002) used the mesoscale
model, MM5, to transfer the Eta forecast data down to the appropriate space
and time scales are required to link the Eta model precipitation forecast results
to the watershed model, HEC-HMS, for runoff prediction. A number of flood related
studies have shown that these models provide accurate and useful results. Kristina
and Terri (2008) evaluated the HEC-HMS' ability to simulate discharge in
prefire and postfire conditions in a semi arid watershed and the necessary parameterizations
for modeling hydrologic response during the immediate and subsequent recovery,
period after a wildfire.
In HEC-HMS model, some parameters are required as inputs to simulate the runoff
hydrographs. Some of the parameters can be estimated through observation and
measurements of stream and basin characteristics (Yener et
al., 2006). The method generally uses either an empirically-derived
unit hydrograph or some standard shape defined by one or two parameters, such
as the time to peak (Pamela, 1992).
After HEC-HMS is applied, the results must be checked to confirm that they
are reasonable and consistent with what to be expected. The model parameters
are calibrated until the results are favourable with close proximity of the
observed and the simulated hydrographs. Calibration is a process to determine
the properties or parameters of a system. Some parameters such as initial abstraction,
curve number, impervious, lag time, initial discharge, recession constant and
ratio are determined through the calibration process where the parameters are
adjusted until the observed and simulated hydrographs are close fit. Some parameters
such as slope, Manning, n, bottom width, shape and length of river are obtained
from topographic map (Zorkeflee et al., 2009).
The model parameters obtained will be validated using different sets of events.
In this study, the HEC-HMS model is used to model runoff for Sungai Johor watershed. Data required for the simulation process are present and future landuse, hydrologic soil group, hydrological records, topography map, landuse maps and rainfall data.
RESULTS AND DISCUSSION
Tahir and Ali (2007) reported that the main reason of
flooding in Kota Tinggi town is intense rainfall from 17 December to 20 December
2006. Table 2 shows a collection of rainfall in Kota Tinggi
catchment on December 2006.
Initial loss, curve number, impervious area, lag time, initial discharge are
determined through calibration process where the parameters are adjusted until
the observed and simulated hydrographs are close fit. By using soil hydrologic
type classifications with soil maps and land use type classification tables
with land-use maps, the Curve Number (CN) map was constructed.
|| Rainfall in Kota Tinggi catchment for December 2006
|| Curve No. value at the Kota Tinggi watershed, Johor, Malaysia.
|| Parameters used in calibration process
Based on the land use and soil cover of the catchment, the curve number is
shown in Table 3. From Table 3, it was observed
that the adjusted curve number, CNw varies between 0.78 and 35.96 for the potential
storage in the catchment.
From Yusop et al. (2007) studies, rainfall and
runoff data in two storm event were used to calibrate and validate the HEC-HMS.
The shape of the modeled hydrograph generally follows the observed hydrographs.
However, the simulated peakflow during calibration and the time to peak during
validation were quite different from the observed values.
In this study, the HEC-HMS model is calibrated using a 10 year period data
from 1997 to 2006. The model parameter values and the event selected during
calibration are shown in Table 4. The calibration process
was carried out using different sets of data. This is to confirm the suitability
of the assumed values for catchment under study. Figure 2a-f
show the generated hydrographs resulted from the calibration process. From the
result of the calibration on 10 September to 20 September 2006, the maximum
observed flowrate is 192.8 m3 sec-1 and the simulated
flowrate is 173.1m 3 sec-1. The calibration process on
10 October to 23 October 2005 yield maximum observed and simulated flowrates
of 105.3 and 103.3 m3 sec-1 while the maximum observed
and simulated flowrates for the events from 4 November to 13 November 2000 are
52.6 and 52.6 m3 sec-1, respectively.
|| Parameters used in the validation process
|| Parameters used in trial process
The results of calibration hydrographs for 23 January to 6 February 1998 yield
the maximum observed and simulated flow rates of 81.8 and 79.7 m3
sec-1. The maximum observed and simulated flowrates for 13 March
to 24 March 1997 is 95.00 and 83.6 m3 sec-1, respectively.
The last event tested on 14 December to 24 December 1997 yield observed and
simulated flowrates of 70.2 and 70.3 m3 sec-1.
Validation was carried out to test the robustness of the developed model. The generated hydrograph is compared with the observed flow graph. The calibrated model parameters are validated using daily interval event rainfall of 4 different periods; 8 January 2007-20 January 2007; 4 January 2006-17 January 2006; 12 January 2001-25 January 2001 and 26 September 2001, 6 October 2001. Table 5 shows the parameters derived and validated using different sets of hydrological data.
Figure 3a-d show the simulated hydrographs during the validation
process for the discharge station at Ladang Pekan Layang-Layang streamflow gauging
station (1835001). In January 2007, the maximum observed flowrate is 267.2 m3
sec-1 and the simulated flowrate is 260.4 m3 sec-1.
The validation process on 4 January to 17 January 2006 yield maximum observed
and simulated flowrates of 192.8 and 173.1 m3 sec-1 while
the maximum observed and simulated flowrates for the events from 12 January
to 25 January 2001 are 226.1 and 220.0 m3 sec-1, respectively.
The event on 26 September to 6 October was also used to further validate the
model. The observed and simulated flowrates were found to be 39.5 and 39.3 m3
The derived parameters are required for flood level simulation and the generation
of missing data. Table 6 shows the parameters used in the
||Calibration results (a) 10-20 September 2006, (b) 10-23 October
2005, (c) 4-13 November 2000, (d) 23 January-6 February 1998, (e) 13-24
March 1997 and (f) 14-24 December 1997
Figure 4a and b show the simulated hydrographs
for the selected events. Table 7 shows the observed and simulated
flowrates for the various events using the derived parameters. Trial process
was carried out to test the strength of the developed model.
|| Observed and Simulated Flowrates obtained during the trial
||Validation hydrograph result. (a) 8-20 January 2007, (b) 4-17
January 2006, (c) 12-25 January 2001and (d) 26 September-6 October 2001
||Trial result. (a) 16-28 January 2003 and (b) 27 September-10
The flowrate data from the events on 16 January to 28 January 2003 had yielded
maximum observed and simulated flowrate of 141.0 and 140.8 m3 sec-1,
respectively. The last data set from the event of 27 September to 10 October
1999 gave 164.8 and 167.4 m3 sec-1, respectively.
EVALUATION OF THE MODEL THROUGH CORRELATION COEFFICIENT, R2 RESULT
The correlation coefficient indicates the accuracy of a model. The value of one indicates perfect prediction. Graphs of simulated versus observed flows are shown in Fig, 5a-f, 6a-d and 7a, b.
||Graphs of simulated versus observed flows for the following
events, (a) 10-20 September 2006, (b) 10-23 October 2005, (c) 4-13 November
2000, (d) 23 January-6 February 1998, (e) 13-24 March 1997 and (f) 14-24
December 1997 (Calibration stage)
||Graphs of simulated versus observed flows for the following
events, (a) 8-20 January 2007, (b) 4-17 January 2006, (c) 12-25 January
2001 and (d) 26 September-6 October 2001 (Validation stage)
||Graphs of simulated versus observed flow for the following
events, (a) 16-28 January 2003 and (b) 27 September to 10 October 1999 (Trial
||(a) Calibration results of run-off modelling using HEC-HMS
(17-25 Dec 2006), (b) Daily unit hydrograph parameters for different storm
events, (c) Summary of the flood event result and (d) The evaluation result
on the performance using HEC-HMS
The simulated flow was also plotted against the observed flow on a 1:1 scale.
With few exceptions, the points generally fall close to the 1:1 line. HEC-HMS,
however, tends to overestimate stream flows on the falling limb. Judging from
the high EI values for the calibration, validation trial exercises of 0.9820,
0.9801 and 0.621, respectively, the performance of HEC-HMS for modeling runoff
is considered satisfactory.
FLOOD LEVEL EVALUATION
Rainfall and runoff data on the 17th to 25th December 2006 for Kota Tinggi
were used in the calibration and validation process. The corresponding storms
sizes were 51, 275 and 130 mm, respectively. The model parameters values obtained
were based on a storm event of 19 December 2006 that corresponds to a much higher
flood event. This is shown in Table 8. All parameters were
selected based on the topography and the historical flow data of Kata Tinggi
catchment. Figure 8a shows a strong indication that the simulated
hydrographs follow the trend of the observed hydrographs. But it should be noticed
that the time to peak is lagged by one day for calibration and validation. Figure
8b shows the daily Unit Hydrograph parameters for different storm events
and Fig. 8c gives the summary result of the flood events for
Kota Tinggi watershed. Figure 8d shows the performance of
the parameters for different storm events, (c) Performance of the derived model
yields a correlation value of 0.905.
|| Parameters used in modeling
The derived model was verified using the event of 19 December 2006. Results
have shown that there is a discrepancy of only 4.0% with the observed and simulated
flowrate of 145.3 and 150.9 m3 sec-1, respectively.
Based on the results and data confirmation, HEC-HMS can be a reliable tool to model river flows. Selected model parameters are calibrated to obtain the most appropriate values for the study site. The model performance of the derived model yield coefficient values close to 1.0. Results of analysis have also found that HEC-HMS can also be used to generate missing data and estimate flood from rainfall data. In conclusion, the derived model using HEC-HMS can be used as a tool to predict flood levels, flowrates as well as for design purposes.
The authors would like to thank the Ministry of Higher Education Malaysia, Department of Irrigation and Drainage Malaysia, University Tun Hussein Onn Malaysia under Grant No. 566 and Universiti Teknologi MARA for the support of this research.