55 Watershed, routing process is divided into 9 elements or reach, i.e.: R-30, R-70, R-
110, R-120, R-150, R-160, R-130, R-210, and R-220. Based on the calculation, k parameter for 30, R-70, R-110, R-120, R-150, R-160, R-130, R-210, and R-220 are
60, 60, 60, 60, 30, 30, 60, 30 and 30 minutes respectively.
Table 17. Lag Routing Parameter
Sub Basin Lag Time
Minutes R220
30 R210
30 R130
60 R160
30 R150
30 R120
60 R110
60 R70
60 R30
60
3.2.2. Model Calibration
Model calibration is an essential process needed to assure that the simulation outputs are close to real observations. Once a model was developed and simulated
for the initial parameter estimates, it was calibrated against known discharge runoff rates measured at the gaging station during a storm event that occurred between
selected time events. The available hydro-climatic records of 3 meteorological stations Citeko, Empang and Pasirjaya, and 1 stream flow gage stations Empang
were analyzed for selection of calibration and verification data for the HEC-HMS model.
The model calibration done by adjusting the curve number and impervious values, until the results matched the field data. The process was completed manually
by repeatedly adjusting the parameters, computing, and inspecting the goodness of fit between the computed and observed hydrographs. Comparison between
simulated and observed hydrograph during calibration process shows the good fit, even though there are some deviations or errors. During calibration process by using
half-year daily data February 1, 2010 – July 31, 2010, the accuracy only achieved
56 0.524 of R
2
. It might be due to the areal rainfall pattern spatially doesn’t represent
the real pattern in each sub-basin area and also due to the simplification of some parameters under the model or due to the loss of several data during recording
process.
Figure 17. Simulation versus observation hydrograph, and correlation between
simulation and observed discharges during calibration process. Performance of the model was objectively evaluated by using Nash-Sutcliffe
efficiency and relative volume error, in which it gave good efficiency value NSE of 0.67 and 42.9 of relative volume errors RV
E
. By using three tests it can be stated that the model is satisfactory accepted.
57
3.2.3. Impact of Land Use Changes Scenarios on Water Yield
Four hydrographs were simulated by using the same parameters in which was used during calibration and validation model. In this case, again the rainfall data of
2010 February 1, 2010 – July 31, 2010 Period was used as meteorological input.
All these four scenarios were run using same parameters, except the curve numbers, percent impervious and initial abstraction are based on those previous land use
condition. The curve numbers, percent impervious and initial abstraction of each scenario are shows on Table 18.
Table 18. CN, IMP and Ia for each Scenario for Year 2030
Sub Basin
Scenario 1 Scenario 2
Scenario 3 Scenario 4
CN IMP
Ia CN
IMP Ia
CN IMP
Ia CN
IMP Ia
W280 90.03
94.33 0.22
90.16 96.50
0.22 90.16
96.49 0.22
90.16 96.49
0.22 W300
88.63 77.04
0.26 88.85
80.69 0.25
88.76 79.01
0.25 89.42
90.41 0.24
W310 84.30
31.54 0.37
84.84 41.36
0.36 84.13
35.33 0.38
84.34 44.66
0.37 W340
94.29 39.48
0.12 94.78
49.20 0.11
94.13 45.11
0.12 94.55
54.42 0.12
W350 86.92
26.27 0.30
87.21 31.57
0.29 86.79
26.57 0.30
86.95 32.26
0.30 W370
86.65 23.77
0.31 86.83
26.78 0.30
86.55 21.91
0.31 86.63
23.35 0.31
W380 90.86
31.99 0.20
90.86 31.99
0.20 90.86
31.99 0.20
90.89 32.78
0.20 W390
88.17 20.48
0.27 88.17
20.48 0.27
88.17 20.48
0.27 88.53
26.78 0.26
W400 89.88
25.09 0.23
90.07 28.49
0.22 89.53
24.03 0.23
89.47 26.76
0.24 W410
85.21 23.78
0.35 85.39
26.98 0.34
85.24 24.46
0.35 85.41
27.51 0.34
W420 87.96
33.10 0.27
87.96 33.10
0.27 87.96
33.10 0.27
88.03 34.43
0.27 W430
84.71 17.20
0.36 84.86
19.89 0.36
84.72 17.93
0.36 84.82
20.46 0.36
W450 91.31
10.13 0.19
91.31 10.13
0.19 91.31
10.13 0.19
91.31 10.13
0.19 W460
89.34 21.26
0.24 89.53
24.67 0.23
89.03 19.69
0.25 87.91
20.99 0.27
W470 85.57
27.53 0.34
85.72 31.11
0.33 85.63
28.75 0.34
85.80 34.30
0.33 W480
88.06 33.26
0.27 84.62
34.73 0.36
86.24 31.61
0.32 83.82
33.04 0.39
W490 84.05
17.80 0.38
84.13 19.21
0.38 83.93
15.72 0.38
84.05 17.85
0.38 W500
84.14 17.11
0.38 83.43
17.26 0.40
84.13 15.40
0.38 83.66
15.71 0.39
W510 84.55
13.38 0.37
83.63 13.39
0.39 86.17
13.35 0.32
85.63 13.35
0.34
58 Figure 18.
Simulated hydrograph using 2010 rainfall data for different land use scenarios.
The simulated hydrograph obtain the peak flow and water yield information for four different land use scenarios. The values of each scenario peak flow are
81.00 m3s, 81.10 m3s, 81.00 and 81.10 m3s for scenario 1, scenario 2, scenario 3 and scenario 4 respectively. While the value of water yield are 276,085.00 m3,
278,038.90 m3, 275,143.20 m3 and 279,178.20 m3 all values for water yield are multiplied by 1000, for scenario 1, scenario 2, scenario 3 and scenario 4
respectively.
Table 19. Water Yield Result for Existing and Each Scenario
Condition Peak Flow
m
3
s Water Yield
1000 m3
Existing 2010 81
273,973.60 Scenario 1 2030
81 276,085.00
Scenario 2 2030 81.1
278,038.90 Scenario 3 2030
81 275,143.20
Scenario 4 2030 81.1
279,178.20
