2012 AIT-NUS-ITB-KU JOINT SYMPOSIUM ON HUMAN SECURITY ENGINEERING Bangkok, Thailand, November 19-20, 2012
Sukhothai Flood Risk Management under changing climate
Sucharit KOONTANAKULVONG1, Anurak SRIARIYAWAT1 and Kwanchai PAKOKSUNG1 1 Faculty of Engineering, Chulalongkorn University, Thailand
E-mail:
[email protected]
Recently, there are numerous disaster events around Asia, starting from Fukushima incident, in Japan, Indonesia earthquake, Bangkok Floods 2011 etc. Besides, the changing climate also induced the unsafe environment to the existing way of infrastructures whether they can still preserve human safety level as it should be or not. The study of climate change revealed that Thai climate showed the change in cyclic characteristics and the seasonal pattern and extreme cases changed since then from the past records. Floods 2011 in Thailand caused a lot of casualties for local residents and also to the logistic of world supply chain. Since most of the Thai cities in the Central Plain located near the river side, the effect of extreme events both precipitation and sea water rise will give significant impacts to the urban flood management planning. The new way of infrastructure planning is needed to counter the present flood issue and also to cover future risk. In the study, the hydrological analysis was conducted to see the difference of peak flood probability change in the upstream of Yom River. The data of flood area and damage were gathered and analysed in the probability function. Future flood situations were simulated to evaluate the risk change in term of flood peak and flood area using climate data from past, present, near future and far future periods based on MRI-GCM data. With new technology on TRMM satellite data and rainfall-runoff-inundation model, the floods in Sukhothai area were then simulated and evaluated. With the flood hazard map concept, the adaptive flood management schemes were proposed in each area of Sukhothai based on the risk level in the study area. From the study, new technology like satellite and simulation helped to better the planning for flood risk management from now to cover the dynamic change of natural disaster, socio-economical loss and adaptive coping capacity of the communities concerned and to seek for acceptable process/solution among parties concerned for infrastructure planning in the changing climate. Key Words : floods, climate change, risk, adaptation, planning, technology
1. INTRODUCTION Recently, there are numerous disaster events around Asia, starting from Fukushima incident, in Japan, Indonesia earthquake, Bangkok Floods 2011 etc. Besides, the changing climate also induced the unsafe environment to the existing way of infrastructures whether they can still preserve human safety level as it should be or not. The study of climate
change revealed that Thai climate showed the change in cyclic characteristics and the seasonal pattern and extreme cases changed since then from the past records (Sucharit K., 2009). Floods 2011 in Thailand caused a lot of casualties for local residents and also to the logistic of world supply chain. Since most of the Thai cities in the Central Plain located near the river side, the effect of extreme events both precipitation, sea water rise and
Year
Peak Dis-
Flood
Damage
Tr
cms charge
sq.km Area
MB cost
year
1995
2,271.50
741.20
394.32
s 32.4
1997
692.80
126.13
49.71
1.48 1
1998
629.30
95.66
19.73
1.38
1999
1,088.70
251.94
174.73
2.72
2002
1,200.90
293.40
300.02
3.34
800 Obs. Sim.
700 600
Flood Area,sq.km
land subsidence will give significant impacts to the urban flood management planning (Sucharit K., 2012; Itti, 2011; N. Phien-wej (2006)). The new way of infrastructure planning is needed to counter the present flood issue and also to cover future risk. In the study, the hydrological analysis was conducted to see the difference of peak flood probability change in the upstream of Yom River where major water source of flood in the Central Plain came from. The data of flood area and damage were gathered and analysed in the probability function. Future flood situations were simulated to evaluate the risk change in term of flood peak and flood area using climate data from past, present, near future and far future periods based on MRI-GCM data. With the introduction of new technology on TRMM satellite data and rainfall-runoff-inundation model, the floods in Sukhothai area were then simulated and evaluated. With the flood hazard map concept, the adaptive flood management schemes were proposed in each area of Sukhothai based on the risk level in the study area. New technology like satellite and simulation helped to better the planning for flood risk management from now to cover the dynamic change of natural disaster, socio-economical loss and adaptive coping capacity of the communities concerned and to seek for acceptable process/solution among parties concerned for infrastructure planning in the changing climate.
A = 0.392 Obs - 160.0 R² = 0.996
500
400 300 A = 0.106 Sim + 84.60 R² = 0.791
200 100 0 0
500
1000
1500
2000
2500
Peak Discharge,cms
Fig.2 Flood area with peak discharge ( at Y14) compared between observed and simulated. 500
450 y = 0.223x - 75.09 R² = 0.845
Damage Cost,MB
400 350 300
250 200 150 100
50 0 0
500
1000
1500
2000
2500
Peak Discharge,cms
Fig.3 Relationship between Sukhothai flood damage cost and peak discharge at Y14.
2. FLOOD AREA AND DAMAGE RELATIONSHIP WITH DISCHARGE PEAK
a)
Simulation results
b) Satellite image
Fig.1 Simulated results compared with satellite image in the study area. Table 1 Flood Situation in the past in Sukhothai Province.
Flood history in the Sukhothai Province were collected from concerned agencies including flood events in the past, flood area and flood damages as reported by the Department of Disaster Prevention and Mitigation in the study area (Fig. 1). The relationship of the peak discharge, flood area and flood damage were analysed in the probabilistic distribution as shown in Table 1 and Figs. 2, 3. Figs. 4 and 5 showed the probabilitic relationship of flood area and damage in
the Sukhothai Province.
positioned within the same grid cell. A channel is discredited as a single vector along its centerline of the overlying slope grid cell. The channel represents an extra flow path between grid cells lying over the actual river course. Lateral flows are simulated on slope cells on a two dimensional basis. Slope grid cells on the river channel have two water depths: one for the channel and the other for the slope (or floodplain). The inflow-outflow interaction between the slope and river is calculated based on different overflowing formulae depending on water-level and levee-height conditions.
2500
Flood Area,sq.km
2000 1500 y = 18.50x + 148.6 R² = 0.931
1000 500 0 0
10
20
30
40
50
60
70
80
90
100
Return Period,years
Fig.4 Relationship between flood area and return period.
2500 Obs_Y14 Sim_Y14 Selected
2000
1200 Discharge,cms
Damage Cost,MB
1000 800
600
1500
1000
y = 9.024x + 113.1 R² = 0.58
400
500
200 0
0 0
10
20
30
40
50
60
70
80
90
100
Return Period,years
Fig.7 Discharges between observed and simulated at Y.14. Fig.5 Relationship between flood damage cost with period.
Fig.8 RRI calibration results at Y14. Fig.6 Schematic diagram of the rainfall–runoff– inundation (RRI) model (Sayama et al., 2012).
3.
SIMULATION RESULTS
MODEL AND THE
The model, used for flood prejection in this study, is a two dimension rainfall-runoff-inundation (RRI) model (Sayama, et al., 2010; 2012). The model deals with slopes and river channels separately as shown in Fig 6. The river channel is located on the grid cell while the model assumes that both slope and river are
The simulation results showed the discharge at Y14 in the Yom River as in Fig. 7 (calibration, Fig. 8) and Fig. 8 (simulation sample from the selected events in 2011 as shown in circle in Fig. 6 with flood area from satellite image). The simulation results also showed the flood area and the relationship of the flood area and discharge peak, compared with the reported figure from the Department of Disaster Prevention and Mitigation), shown in Fig. 3. It can be seen that the simulated flood area is smaller than the reported figures when the peak discharge is beyond 1000 cms. This is because the reported figure mostly indicated
the most probable flood area reported from the villages. The damage of the flood can also be estimated from the damage curve and flood peak in Fig. 4.
5000
and hydraulic simulation help to better the planning for flood risk management. The new technology can catch the dynamic change of natural disaster, socio-economical loss and the need in the adaptive coping capacity of the communities concerned to cope with the impact from the climate change.
4500
Discharge,cms
4000 3500
5. CONCLUSIONS AND RECOMMENDATIONS
3000 2500 2000
Gumbel distribution Present
1500
Gumbel Distribution Near Future
1000
Observation Data Present
500
MRI Data Near Future
0
0
25
50
75
100
Return Period,years
Fig.10 Return period and annual peak discharge at Y.14 for present and near future.
4. FUTURE FLOOD SITUATIONS AND RISK MANAGEMENT Near future situations (2012-2025) of floods in the study area were simulated from MRI-GCM, bias corrected to fit with past data, and the peak flood at Y14 was simulated and analysed statistically compared with the past records from daily flow (during 1977-2010) as shown in Fig. 10. It can be seen that the impact from the climate change induced increase of peak discharge in the station Y14 and the flood area and flood damage using the previous flood-peak discharge relationships can be estimated and shown in Table 2. The flood area and damage in the near future will increase about 80- 120 % compared with the present period. Due to the increase of flood risk, the flood issue in the Sukhothai Province should be tackled with the flood hazard approach and flood plain management. The approach should be separated into the urban and rural areas where the absorbing capacity and flood damage are different. With the spatial distribution from the simulation of the study, the flood area and flood volume information can be used to set the adaptive measures, i.e., dyking surrounding urban area, to store water in the retention area or to divert flood water through flood way etc., in the Sukhothai Province of both rural and urban areas more appropriate. Besides, the simulated flood information can also be used for risk management discussion among parties concerned to seek for acceptable solution for flood infrastructure planning including future flood situations. From the study, the new technologies like satellite
Past historical information were gathered from the concerned agencies and the relationships of flood peak-flood area-flood damages were formulated in the probabilistic base. The RRI model was used to simulate the flood situations in the study area for more precise spatial distribution after calibration. Near future MRI-GCM climate data were used to project the future flood situations in the study area and it is found that future flood will increase by 80-120 %. The flood hazard approach is recommended to find flood adaptation measures in the future for both urban and rural in the study area in the optimum and acceptable manners under risk management concept. New technology like satellite and simulation in the study proved to help to better the planning for flood risk management from now to cover the dynamic change of natural disaster, socio-economical loss and adaptive coping capacity of the communities concerned and to seek for acceptable process/solution among parties concerned for infrastructure planning in the changing climate.
ACKNOWLEDGMENT: The authors would like to express sincere thanks to the authorities concerned, e.g., Royal Irrigation Department, Electricity Generating Authority, Sukhothai Municipal, Thai Meteorological Department etc. for their data and comment provision. This research is funded by Chulalongkorn University under climate change research cluster.
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