A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Remote Sensing and Geographic Information Systems

Thesis (M.Sc.) - Asian Institute of Technology, 2023

Potential Evapotranspiration (PET) holds significant importamce in both the energy balance and hydrological cycle. While the PET-PM model stands as the most widely employed approach for daily PET estimation, it necessitates the inclusion of parameters such as solar radiation, relative humidity, temperature, and wind speed. In Thailand, the availability of suitable meteorological stations for acquiring essential data is constrained, leading to the omission of certain input parameters in numerous geographical locations. The primary aim of this investigating is to formulate an improved version of the potential. In addition, several spatial interpolation methods were determined and analyzed PET pattern in this study. The outcome of the initial objective involved the development of daily PET utilizing the Revised Thornthwaite (RTH) model. This was achieved through the integration of PET-PM, PET-THtef, PWV, and temperature data collected over 2020 from 10 GNSS stations, 10 weather stations situated within the HII, and an additional 9 weather stations associated with the TMD that provided adequate data. In this study, the RTH model was used the multiple linear regression analysis for model development and validation The RTH model for over region was developed using datasets of 6 GNSS stations. Furthermore, for model validation, datasets from 4 GNSS stations were utilized. The findings indicate that the RTH model demonstrated satisfactory performance in estimating daily PET, with statistical metrics including R2=0.79, MAE=0.78, MSE- 0.97, and RMSE=0.98 mm per day. In addition, the outcomes indicate that the Kriging interpolation methods yielded the highest accuracy in estimating daily PET during the summer, with respective values of MAE= 1.05, MSE= 2.12, RMSE=1.4 mm per day, and R2=0.51. Furthermore, the winter season exhibited MAE= 1.02, MSE=1.93, RMSE=1.39 mm per day, and R2=0.51. For the rainy season, the corresponding results were MAE=0.96,MSE-2.19, RMSE=1.48 mm per day, and R2=0.35. Moreover, the PET distribution pattern was highest during timeframe spanning Mar to May 2020 in the southern region. The result of RTH model can be application for estimating PET at other GNSS stations in the region. Moreover, the PET spatial distribution pattern map can be applied in hydrological and agricultural managements.