Quantification of uncertainty in future climate change projections in the Chindwin River Basin, Myanmar | |
| Author | Myat Thiri Lwin |
| Call Number | AIT Caps. Proj. no.CIE-18-18 |
| Subject(s) | Climatic changes--Myanmar--Chindwin River Basin Uncertainty (Information theory) |
| Note | A capstone project report submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Engineering Civil And Infrastructure Engineering |
| Publisher | Asian Institute of Technology |
| Series Statement | Caps. Proj. ; no. CIE-18-18 |
| Abstract | Overall objective Qf the study was to quantify the uncenainties of future climate cbange P(Q- jections in Chindwin River Basin, Myanmar. The specific objectives were aimed at studying future projections of rainfall and temperature and comparison between observed and future data analysis. And to quantify the uncertainties in future climate projections using Bayesian Model Averaging (BMA) method. Since, Bayesian Model Averaging (BMA) method can combine the forecasts of different models together to generate a new one which is expected to be better than any individual models forecast, it has been widely used in hydrology for ensemble hydrologic prediction. The research focus in this study is shifted onto the com- parison of the prediction uncertainty interval generated by BMA with that of each individual modeL And, R studio programming software was used to determine the uncertainties from climate models projections. One station from low elevation (Hkamti Station) and one sta- tion from high elevation (Mawlaik Station) were selected from total Ifi stations. in Chindwin river basin. The analysis was performed observed data of 3 meteorological variables namely: rainfall, maximum temperature and minimum temperature. The observed daily rainfall and temperature data of two stations for the base periods 1976 to 2006 and the future period for rainfall and temperature is divided into 3-time scales; near future (2010-2039), mid future (2040-2069), far future (2070-2099). For future analysis, Bias corrected data were used from 2 Regional Climate Models (ACCESS and MPIESM). RCP 4.5 and RCP 8.5 emission sce- nario were used for this analysis. Results showed future rainfall and temperature projections in the area. Finally, the uncertainties intervals of each individual climate model and two BMA combination schemes are assessed and compared. |
| Year | 2018 |
| Corresponding Series Added Entry | Asian Institute of Technology. Caps. Proj. ; no. CIE-18-18 |
| Type | Capstone Project |
| School | School of Engineering and Technology (SET) |
| Department | Department of Civil and Infrastucture Engineering (DCIE) |
| Academic Program/FoS | Civil and Infrastructure Engineering (CIE) |
| Chairperson(s) | Shrestha, Sangam; |
| Examination Committee(s) | Duc Hoang Nguyen; |
| Degree | Capstone Project (B.Sc.)-Asian Institute of Technology, 2018 |