1. USING NUMERICAL PREDICTED RAINFALL DATA FOR A DISTRIBUTED HYDROLOGICAL MODEL TO ENHANCE FLOOD FORECAST: A CASE STUDY IN CENTRAL VIETNAM
Nguyen Thanh Son, Luong Tuan Anh, Tran Tan Tien, Tran Ngoc Anh
Hanoi University of Science (HUS), Hanoi, Vietnam
Stream
Watershed border
Hydrological station
Rainfall station
Tra Khuc river
1. Introduction
The central part of Vietnam is located in between the high mountain range (as the border with Lao) and coastal line thus most of the areas are very narrow, and the upstream catchments are very steep. This region also suffers a lot of typhoons and tropic cyclones during the rainy season which cause many seriously floods with great losses and damages. And in order to mitigate the flooding damage the quality of flood forecast is one of the most important issues.
Due to the steep and narrow topographical condition in these upstream catchments, the concentration time is very short accompanying with the poor gauging system, it’s difficult to use hydrological data to make the long lead-time prediction, therefore using observed and predicted rainfall data is crucial.
In this study, the predicted rainfall data from a weather model (RAMS) were used as input for the distributed hydrological model to increase the lead-time of flood forecast from 12 hr to 72 with the reasonable results in an upstream watershed in Central Vietnam. The success of the study encourage us to verify this approach in other upstream catchments and then in operational activities.
2. Method and Material
2.1 RAMS (the Regional Atmospheric Modeling System) model:
RAMS is the weather forecast model developed by Colorado State University and ASTER institute. The model has been adapted by Faculty of Hydro-Meteorology and Oceanography (HUS) to apply in Vietnam region using nested grid level 3 to increase the accuracy of the rainfall and typhoon track prediction.
2.2. Distributed hydrological model (KW-1D):
Fig. 2 Map of Tra Khuc river catchment
The 1D kinematic wave equation (Eqs. 1, 2) was applied to simulate the runoff flows in surface and channels, while the SCS method (Eq. 3) was used to calculate the losses from the rainfall and then the lateral inflow.
These equations was discretized using FEM and then soled by weighted residual Garlekin method
3. Application in Central Vietnam
3.1 Tra Khuc river catchment (Son Giang st.): Is located in Quang Ngai Province with 2440km2, originates from the eastern part of high-land Kon Plong in 1000m elevation (Fig. 1, 2). The averaged steepness is 29.3% and 75% of the catchment area are mountainous.
The catchment was divided into 39 bands and 150 elements with 9 sub-basins (Fig 3) using GIS tools,
Fig. 1 Location of Tra Khuc river catchment
3.2 Using RAMS for rainfall prediction in Tra Khuc catchment: In order to downscale the regional data, the grid resolution 3x3km was used. The good agreement between the simulated and observed results was shown in Fig. 4. These data are 3-day accumulate rainfall, and then the predicted rainfall data from RAMS will be used as input data in hydrological model for forecast purpose.
3.3 Model calibration and verification: The model was calibrated with the data from 8 flood events ( ) and then verified with other 6 independent floods (2001-
2002) to show the good agreement with the gauged data at Son Giang Station (Table 1, 2). Therefore, the parameter set can be applied to simulate the hydrograph for the forecast.
Fig. 3 Computational element grid
Table 1. Calibration results No
Flood period
Peak error
Volume error R2 1
13/XI - 19/XI /1998
34.3%
16.3%
70.1% 2
4/XI - 12/XI/1998
12.8%
33.5%
92.0% 3
25/XI - 30/XI /1998
10.7%
16,9%
94.7% 4
22/X - 27/X/ 1999
17.1%
8.0%
94.3% 5
9/X - 12/X/2000
6.3%
10.9%
72.6% 6
7/X - 19/X/2000
9.0%
18.6%
88.7% 7
27/X - 31/X/2000
10.4%
11.3%
90.0% 8
20/XII -24/XII/2000
6.5%
13.5%
87.1%
Average
13.4%
16.1%
86.2%
Table 2. Verification results No
Flood period
Peak error
Volume error R2 1
20/X - 23/X/2001
6.7%
11.1%
88.9% 2
11/XI -16/XI/2001
16.8%
17.7%
85.8% 3
14/XII-18/XII/2001
13.6%
6.5%
76.6% 4
25/X - 28/X/2002
11.0%
1.1%
91.3% 5
6/XI - 9/XI/2002
6.4%
14.1%
89.1% 6
10/XI - 12/X/2002
15.7%
4.3%
79.1%
Average
11.7%
9.1%
85.1%
Fig. 4 An example of flood simulation
Fig. 4 Comparison of simulated and observed data in Oct. 22, 2005
3.4 Applying for flood forecasting: The integrated system including RAMS and KW-1D was applied to predict 2 real-time floods in Tra Khuc river catchment in 2005 with the lead-time was 72h. The simulated results agreed with the observation (Table 3 and Fig. 5).
Table 3. Flood forecast results No
Flood period
Peak error
Volume error R2
S/ 1
02/X - 5/X 2003
46.6%
79.4%
42.5%
1.14 2
13/X - 16/X 2003
32.7%
31.7%
54.7%
0.64 3
31/X - 2/XI 2005
7.5%
30.5%
76.9%
0.46
Average
28.9%
47.2%
58.0%
0.75
4. Conclusion
The results from this study show the advantages of integrated system to predict floods in upstream catchments which have small water concentration time. The lead-time of prediction can be increase up to 72h with the reasonable accuracy.
Fig. 5 An example of flood forecasting