Projection of future climate and comparison of bias correction methods : a case study of the Songkhram River Basin, Thailand | |
| Author | Swar, Cristin |
| Call Number | AIT Caps. Proj. no.CIE-16-10 |
| Subject(s) | Climatic changes--Thailand--Songkhram River Basin--Case studies Climatic changes--Statistical methods Climatic changes--Mathemathical models |
| 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, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Caps. Proj. ; no. CIE-16-10 |
| Abstract | Climate change threatens important sectors of Thailands economy; agriculture and trade. Therefore, it is important for the country to be prepared for the upcoming changes in the climatic conditions like temperature and precipitation. For this purpose, this study aims to project the future temperature and precipitation of the Songkhram River Basin in Thailand us-ing two bias- correction methods- i.e. Linear Scaling and Quantile Mapping. The future climate of the basin has been projected for the periods 2020s, 2050s and 2080s under the Representative Concentration Pathways: RCP 4.5 and RCP 8.5 as recommended by IPCC. Three general circulation models (GCMs) were selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) based- on previous researches for Thailand.The selected bias correction methods were used to find the correction factors in the calibration period (1975-2004) using the raw GCM data and the observed data of the calibration period for precipitation and temper- ature. Further the correction factors were used in the independent data set of the validation period (2005), for both precipitation and temperature, in order to insure the performance of each bias correction method. After validating the dataset, the cor- rection factors were further used to project the future precipitation and minimum and maximum temperature based on the selected time periods. The results from both Linear Scaling and Quantile Mapping methods, were statisti- cally analyzed with the corresponding observed data based on statistical parameters like mean, standard deviation, correlation coefficient, and RMSD (Root Mean Square Difference). From the results it was observed that both the bias correction methods Linear Scaling and Quantile Mapping have different working capabilities based on data availability and variability. It was also noted that, in case of bias correction of raw GCM data for precipitation, Linear Scaling method worked well, i.e. the corrected GCM data had a comparatively better correlation and reduced RMSD with the cor- responding observed data when compared with the result of precipitation data from Quantile Mapping method. However, in the case of temperature, it was noted that the Quantile Mapping method performed better than the Linear Scaling method while cor- recting the raw GCM data for both maximum temperature and minimum temperature. In addition to that, the data for future projection of precipitation and temperature in the Songkhram River basin were analyzed using the outputs of three selected GCMs for three different time periods (2020s, 2050s, and 2080s). In the case of precipitation, based on result from three GCMs, the projection of precipitation shows an increase in monthly precipitation across the basin for both Linear Scaling and Quantile Mapping method. However, there seems to be variations in the annual precipitation trend be- tween the GCMs for the three different time periods under RCP 4.5 and RCP 8.5 with respect to the base period. Whereas, for future maximum and minimum temperature for both Linear Scaling and Quantile Mapping method, it is noted to have an increasing trend for all the three time periods under both scenarios. |
| Year | 2016 |
| Corresponding Series Added Entry | Asian Institute of Technology.Caps. Proj. ; no. CIE-16-10 |
| 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) | Babel, Mukand Singh; |
| Degree | Capstone Project (B.Sc.)-Asian Institute of Technology, 2016 |