Impact of Bias-Correction Methods in Assessing the Potential Flood Frequency Change in the Bago River
Ralph Allen E. Acierto*,, Akiyuki Kawasaki*, and Win Win Zin**
*The University of Tokyo
7-3-1 Hongo, Bunkyo, Tokyo 113-8656, Japan
**Yangon Technological University, Yangon, Myanmar
The increasing flood risks in the Bago River due to rapid urbanization and climate change have great implications on the local development and quality of life in the basin. Therefore, the current flood hazard and potential future changes in flooding due to climate change must be assessed. This study investigates the potential flood frequency change in the Bago River and its sensitivity to the bias-correction method used in climate projections from the downscaled Global Climate Model (GCM) output. A pseudo-global warming method using MIROC5 RCP 8.5 was employed to produce 12-km 30-y historical and future climate projections. Empirical quantile mapping (EQM), gamma quantile mapping (GQM), and the multiplicative scaling method (SCM) were used for bias-correcting the rainfall input of the water-energy budget distributed hydrological model (WEB-DHM). The impacts of bias-correction methods used in reproducing the annual maximum series in the frequency analysis are sensitive to the trend of potential future changes in flood discharge frequency estimation. All methods exhibited decreases in the flood peak discharge for 50-yr and 100-yr flood predictions, which may primarily be due to the MIROC5 GCM used. However, the variation in the magnitude of the change is wide. This demonstrates the uncertainty of the frequency analysis for flood magnitude due to the employed bias-correction method. This uncertainty has significant implications on risk quantification conducted using downscaled climate projections. The effect of the uncertainty of the bias-correction method on the annual maximum rainfall time series should be communicated properly when conducting risk and hazard assessment studies.
-  W. W. Zin, A. Kawasaki, and S. Win, “River flood inundation mapping in the Bago River Basin, Myanmar,” Hydrological Research Letters, Vol.9, No.4, pp. 97-102, doi: 10.3178/hrl.9.97, 2015.
-  S. S. Bhagabati and A. Kawasaki, “Consideration of the rainfall-runoff-inundation (RRI) model for flood mapping in a deltaic area of Myanmar,” Hydrological Research Letters, Vol.11, No.3, pp. 155-160, doi: 10.3178/hrl.11.155, 2017.
-  S. Win, W. W. Zin, A. Kawasaki, and Z. M. L. T. San, “Establishment of flood damage function models: A case study in the Bago River Basin, Myanmar,” Int. J. of Disaster Risk Reduction, Vol.28, pp. 688-700, doi: 10.1016/j.ijdrr.2018.01.030, 2018.
-  S. Shrestha and A. Y. Htut, “Land Use and Climate Change Impacts on the Hydrology of the Bago River Basin, Myanmar,” Environmental Modeling & Assessment, Vol.21, No.6, pp. 819-833, doi: 10.1007/s10666-016-9511-9, 2016.
-  A. Y. Htut, S. Shrestha, V. Nitivattananon, and A. Kawasaki, “Forecasting Climate Change Scenarios in the Bago River Basin, Myanmar,” J. of Earth Science & Climatic Change, Vol.5, No.9, Article No.228, doi: 10.4172/2157-7617.1000228, 2014.
-  S. Shrestha and A. Y. Htut, “Modelling the potential impacts of climate change on hydrology of the Bago River Basin, Myanmar,” Int. J. of River Basin Management, Vol.14, Issue 3, pp. 287-297, doi: 10.1080/15715124.2016.1164177, 2016.
-  C. Funk et al., “The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes,” Scientific Data, Vol.2, Article No.150066, doi: 10.1038/sdata.2015.66, 2015.
-  W. C. Skamarock et al., “A Description of the Advanced Research WRF Version 3,” NCAR Technical Note, No.NCAR/TN-475+STR, 2008.
-  C. Liu et al., “Continental-scale convection-permitting modeling of the current and future climate of North America,” Climate Dynamics Vol.49, Issue 1-2, pp. 71-95, doi: 10.1007/s00382-016-3327-9, 2017.
-  T. Yoshikane, F. Kimura, H. Kawase, and T. Nozawa, “Verification of the Performance of the Pseudo-Global-Warming Method for Future Climate Changes during June in East Asia,” SOLA, Vol.8, pp. 133-136, doi: 10.2151/sola.2012-033, 2012.
-  R. Rasmussen et al., “High-Resolution Coupled Climate Runoff Simulations of Seasonal Snowfall over Colorado: A Process Study of Current and Warmer Climate,” J. of Climate, Vol.24, No.12, pp. 3015-3048, doi: 10.1175/2010JCLI3985.1, 2011.
-  K. L. Rasmussen, A. F. Prein, R. M. Rasmussen, K. Ikeda, and C. Liu, “Changes in the convective population and thermodynamic environments in convection-permitting regional climate simulations over the United States,” Climate Dynamics, doi: 10.1007/s00382-017-4000-7, 2017.
-  D. P. Dee et al., “The ERA-Interim reanalysis: configuration and performance of the data assimilation system,” Quarterly J. of the Royal Meteorological Society, Vol.137, No.656, pp. 553-597, doi: 10.1002/qj.828, 2011.
-  V. F. Banzon, R. W. Reynolds, D. Stokes, and Y. Xue, “A 1/4◦-Spatial-Resolution Daily Sea Surface Temperature Climatology Based on a Blended Satellite and in situ Analysis,” J. of Climate, Vol.27, No.21, pp. 8221-8228, doi: 10.1175/JCLI-D-14-00293.1, 2014.
-  F. Kimura and A. Kitoh, “Downscaling by Pseudo Global Warming Method,” The Final Report of the ICCAP, 2007.
-  L. Wang and T. Koike, “Comparison of a Distributed Biosphere Hydrological Model with GBHM,” Annual J. of Hydraulic Engineering, Vol.53, pp. 103-108, 2009.
-  M. Shrestha, T. Koike, L. Wang, and K. Yoshimura, “Long-Term (1948-2006) Simulation of Snow Depth at Yagisawa Dam Site Using JP10 Reanalysis and Energy Balance Snow Model (WEB-DHM-S),” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol. 69, No.4, pp. I_175-I_180, doi: 10.2208/jscejhe.69.i_175, 2013.
-  A. M. Bhatti, T. Koike, and M. Shrestha, “Climate change impact assessment on mountain snow hydrology by water and energy budget-based distributed hydrological model,” J. of Hydrology, Vol.543, Part B, pp. 523-541, doi: 10.1016/j.jhydrol.2016.10.025, 2016.
-  P. A. Jaranilla-Sanchez, L. Wang, and T. Koike, “Modeling the hydrologic responses of the Pampanga River basin, Philippines: A quantitative approach for identifying droughts,” Water Resources Research, Vol.47, Issue 3, doi: 10.1029/2010WR009702, 2011.
-  M. Shrestha, T. Koike, P. A. Jaranilla-Sanchez, L. Wang, and Y. Wakazuki, “Assessment of Hydrologic Response to Future Climate Change in the Tone River Basin of Japan,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.72, No.4, pp. I_25-I_30, doi: 10.2208/jscejhe.72.i_25, 2016.
-  P. A. Jaranilla-Sanchez et al., “Hydrological Impacts of a Changing Climate on Floods and Droughts in Philippine River Basins,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.69, No.4, pp. I_13-I_18, doi: 10.2208/jscejhe.69.i_13, 2013.
-  D. Yamazaki, D. Ikeshima, J. Sosa, P. D. Bates, G. H. Allen, and T. M. Pavelsky, “MERIT Hydro: A High-Resolution Global Hydrography Map Based on Latest Topography Dataset,” Water Resources Research, Vol.55, Issue 6, pp. 5053-5073, doi: 10.1029/2019WR024873, 2019.
-  B. Lehner, “HydroSHEDS Technical Documentation Version 1.2,” 2013, https://www.hydrosheds.org/images/inpages/HydroSHEDS_TechDoc_v1_2.pdf [accessed September 23, 2018]
-  J. E. Vogelmann, S. M. Howard, L. Yang, C. R. Larson, B. K. Wylie, and N. V. Driel, “Completion of the 1990s National Land Cover Data Set for the Conterminous United States from Landsat Thematic Mapper Data and Ancillary Data Sources,” Photogrammetric Engineering & Remote Sensing, Vol.67, No.6, pp. 650-662, 2001.
-  R. Myneni, Y. Knyazikhin, and T. Park, “MCD15A2H MODIS/Terra+Aqua Leaf Area Index/FPAR 8-day L4 Global 500m SIN Grid V006,” NASA EOSDIS Land Processes DAAC, doi: 10.5067/MODIS/MCD15A2H.006, 2015.
-  S. Kobayashi et al., “The JRA-55 Reanalysis: General Specifications and Basic Characteristics,” J. Meteorological Society of Japan. Ser. II, Vol.93, No.1, pp. 5-48, doi: 10.2151/jmsj.2015-001, 2015.
-  M. Iturbide et al., “The R-based climate4R open framework for reproducible climate data access and post-processing,” Environmental Modelling & Software, Vol.111, pp. 42-54, doi: 10.1016/j.envsoft.2018.09.009, 2019.
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