Abstract
In this study, bias-corrected daily rainfall data of eight global climate models (GCMs) was used as input for a hydrologic model (Hydrological Engineering Center - Hydrological Modeling System (HEC-HMS)) to simulate daily streamflow in the Upper Ayerawaddy River basin (UARB), Myanmar. Monthly, seasonal, annual, and decadal mean flows, calculated for the baseline (1975–2014), were compared with projections for future periods (2040s: 2021–2060 and 2080s: 2061–2100) under two Representative Concentration Pathways (RCP 4.5 and RCP 8.5). The spread of low flows (10th and 25th percentile of daily flows) and high flows (75th, 90th, and 100th percentiles) were analyzed for each period. The ensemble of GCMs indicates an increase in mean monthly (except in October and November), seasonal (except post-monsoon), annual, and decadal rainfalls and corresponding flows in the UARB. Future low flows are expected to have high variability while high flows are expected to have higher means than that of baseline. The density distribution analysis of baseline and future flows reveals that future periods are likely to experience an increase in the magnitude of mean flows but a decrease in variability. Rainfall extremes indicated by 1-day maximum rainfall, 5-day consecutive maximum rainfall, and the number of extreme rainfall days reveals frequent wetter extremes in the UARB under future climate conditions. Extreme floods, as estimated by the frequency analysis of daily flows, are also expected to become more frequent during the future periods. These changes in flows can be attributed solely to climate change since the analyses did not account impacts of possible land use change and water resources development in the UARB. This study is a good starting point to assess future flows, and further research is recommended to address the limitations of this study for improved understanding and assessments that will prove useful for planning purposes in the study area.
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Acknowledgements
The authors would like to thank the RIMES (Regional Integrated Multi hazard Early Warning Systems) for providing their data on rainfall and discharge through their project on “Development and Implementation of User-Relevant End-to-End Flood Forecast Generation and Application System for Myanmar” to the first author during his internship at RIMES. Special thanks to the Director General of DMH, Myanmar, Dr. Anshul Agarwal (senior hydrologist, RIMES), and Dr. Pooja Sancheti for their support.
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Ghimire, U., Babel, M.S., Shrestha, S. et al. A multi-temporal analysis of streamflow using multiple CMIP5 GCMs in the Upper Ayerawaddy Basin, Myanmar. Climatic Change 155, 59–79 (2019). https://doi.org/10.1007/s10584-019-02444-3
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DOI: https://doi.org/10.1007/s10584-019-02444-3