River Discharge Projection in Indochina Peninsula under a Changing Climate. Yasuto TACHIKAWA and Duc Toan DUONG
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1 River Discharge Projection in Indochina Peninsula under a Changing Climate Yasuto TACHIKAWA and Duc Toan DUONG 1
2 Research Purpose To project river discharge in the Indochina Peninsula region under a changing climate, then Examine the change of river discharge under a changing climate, and To find out river basins in the region where significant changes related to floods, droughts and water resources could happen.
3 Climate change projection data 20 km resolution future climate simulation data, calculated by MRI-AGCM3.2S, a super high resolution numerical climate model developed at Meteorological Research Institute, Japan Present Climate Experiment: Near Future Climate Experiment: Future Climate Experiment:
4 GCM rainfall projection data provided by Meteorological Research Institute, Japan Precipitation (mm/hr) Provided by Dr. Oku at DPRI, Kyoto University
5 Typhoon 12, Talas, Sep. 1, 2011 Kumaro River basin Five days rainfall: more than 1500mm Estimated peak discharge: 24,000m 3 /s mm
6 Typhoon 18, Man-yi, Sep. 16, 2013 嵐山, 渡月橋 Katsura station 294mm
7 Typhoon 26, Wipha, Oct. 16, 2013 Izu-Oshima, Tokyo, 27 dead, 21 missing
8 Study Area Irrawaddy River basin Salween River basin Red River basin o E 34.0 o N Mekong River basin 91.0 o E 5.0 o N Chao Phraya River basin
9 Research Methodology Input data 20 km resolution future runoff generation data by MRI-AGCM3.2S, Metrological Research Institute, Japan. Present climate experiment: Near future experiment: Future climate experiment: River flow routing model for estimating river flow discharge using the future climate data such as rainfall, evaporation and so on. Analyzing changes of river flow discharge to assess flood risk, drought risk, and water resources.
10 River Flow Routing Model Elevation Flow direction
11 Elevation (m) Topography Data using USGS HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple scale) 11
12 Flow Routing Model using DEMs 1K-FRM/DHM 12
13 River Flow Routing Model Elevation Flow direction
14 River Flow Routing Model kinematic wave model Continuity equation Momentum equation A t + Q x = q L Q = αa m Runoff generation data provided by GCM is given to q L. Q t, x Discharge A t, x Cross section area t time axis x distance axis q L lateral inflow m 1 sin θ 1 α =, m = 5 n B 3 θ slope gradient n roughness coefficient B width of river flow
15 Application to Southeast Asian Region
16 Comparison of projected river discharge using MRI-AGCM3.2S
17 Change Ratio of Mean of Annual River Flow Near Future Climate to Present Climate Future Climate to Present Climate 17
18 Change Ratio of Mean of Annual Maximum Daily Flow Near Future Climate to Present Climate Future Climate to Present Climate 18
19 Change Ratio of Mean of Annual Minimum Daily Flow Near Future Climate to Present Climate Future Climate to Present Climate 19
20 Statistical Analysis of River Discharge Changes Testing hypotheses Null hypothesis H 0 : the is no significant difference between annual mean stream flow/mean of annual maximum daily stream flow/mean of annual minimum daily stream flow for the (near) future climate and the present climate. nf = p, f = p Alternative hypothesis H A : nf p, f p Significant level (probability of error) α = 0.05
21 Test for Statistical Significant Difference between Two Means For normally distributed data, the Welch correction t-test was used to test for statistical significant difference between means of two groups. For non-normally distributed data, the Mann-Whitney U-test was used to test for statistical significant difference between means of two groups.
22 Statistical Significant Differences between the Annual Mean Daily Flow Near future climate and the present climate Ratio of the change Statistical significance
23 Statistical Significant Differences between the Annual Mean Daily Flow Future climate and the present climate Ratio of the change Statistical significance
24 Statistical significant differences between the mean of the annual maximum daily flow Near future climate and the present climate Ratio of the change Statistical significance
25 Statistical significant differences between the mean of the annual maximum daily flow Future climate and the present climate Ratio of the change Statistical significance
26 Statistical significant differences between the mean of the annual minimum daily flow Near future climate and the present climate Ratio of the change Statistical significance
27 Statistical significant differences between the mean of the annual minimum daily flow Future climate and the present climate Ratio of the change Statistical significance
28 Comparison of projected with observed discharge
29 Runoff Simulation for the Entire Japan Five regions were set up for runoff simulation under a changing climate. Hokkaido East Japan Central Japan Kyushu Western Japan
30 Present Climate River Flow Simulation in Kyushu, Japan Chikugo River (2315km 2 )
31 Comparison of flow duration curve of simulated river flow using MRI-AGCM3.2S with observed river discharge Daily discharge Annual 95 th flow Annual 185 th flow Annual 275 th flow Annual 355 th flow Simulated river discharge using MRI-AGCM3.2s Observed river discharge
32 日流量 (m 3 /sec) Comparison of flow duration curve of simulated river flow using MRI-AGCM3.2S and observed river discharge Daily discharge 1000 観測値 90% タイル値観測値中央値観測値 10% タイル値 MRI-AGCM3.2S 90% タイル値 MRI-AGCM3.2S 中央値 MRI-AGCM3.2S 10% タイル値 降順位日数 (day)
33 Ongoing research to estimate future floods caused by typhoon under a changing climate
34 Sousei 創生 Program ( ) Sponsored by Ministry of Education, Culture, Sports, Science and Technology (MEXT) 34
35 Hypothetical typhoon experiment under a changing climate by Ishikawa et al. at DPRI, Kyoto University Control run Best truck Hypothetical typhoon experiment, initial locations of typhoon
36 Typhoon Vera (1959) simulation NHM-5km Best track Track ensemble (71 patterns) Central pressure
37 Typhoon Vera (1959) in future climate Central pressure drops = Intensification Applied for assessing worst-case scenarios: river discharge, flooding, high waves Central pressure
38 Discharge and inundation simulation under hypothetical typhoon data Design water level Design flood discharge
39 CONCLUSION A clear change in annual mean stream flow, mean of annual maximum daily stream flow and mean of annual minimum daily stream flow in the Indochina Peninsula region was detected. The degree of change differs from location to location. The changes appeared in near future climate experiment became clearer in the future climate experiment. The increase of flood risk and drought risk were found in Irrawaddy River Basin, Red River Basin and lower part of Mekong River Basin.
40 CONCLUSION To construct a prpper adaptive measure, we need information of change of a probability distribution of extreme flood characteristics, such as annual maximum discharge, and also a change of the probable maximum flood. Flood simulation using a hypothetical typhoon simulation helps to estimate a change of the probable maximum flood. To predict a change of a probability distribution of extreme flood characteristics, a proper bias correction method and a downscaling method are indispensable.
41 Appendix
42 Statistical Analysis of River Discharge Changes Data normality test The Shapiro-Wilk W test (Gilbert, 1987) was used for normality test. The W test statistic is calculated by W = k 1 n 1 s 2 a i x n i+1 x i i=1 where n is sample size; s is standard deviation; coefficient a i is function of n; x i is variable at rank i; and k is n/2 for even n and (n-1)/2 for odd n. If W < W cr, the data has a non-normal distribution. 2
43 Normality test result for the annual mean stream flow data Present climate Near future climate Future climate
44 Normality test result for the mean of the annual maximum stream flow data Present climate Near future climate Future climate
45 Normality test result for the mean of the annual minimum stream flow data Present climate Near future climate Future climate
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