Untitled

Abstract

In the hydrological cycle and in water use, evapotranspiration is one of the most important components because it represents a loss of usable water from the hydrological supply. The purposes of this research are to examine the temporal trend of reference evapotranspiration and pan evaporation for the upper region, the lower region, and the whole catchment of the Chao Phraya River Basin, and to consider the spatial and temporal distribution of monthly reference evapotranspiration. To achieve these purposes, daily reference evapotranspiration from 1971 to 2002 was computed for each weather station using the FAO Penman-Monteith method. The average of monthly reference evapotranspiration in each weather station was calculated. Thereafter, this monthly reference evapotranspiration reference point for evapotranspiration was interpolated using the Co-Kriging interpolation to obtain a spatial value. From the results of this research it can be concluded that the trends of both reference evapotranspiration and pan evaporation in all the regions have decreased from 1971 to 2002 and that the spatial and temporal distribution of mean monthly reference evapotranspiration are affected by the changes in the meteorological variables for each month and for each different region.

Contribution rates of climate variables to the change in reference evapotranspiration in northern Thailand from 1991 to 2019

“…However, monthly ET o trends did not show consistent spatial variations in magnitude and direction (i.e., positive and negative) (Xu et al, 2021). However, the results of Xu et al (2021) for Thailand contradict those of Tebakari et al (2005), Kosa and Pongput (2007), and Thepprasit et al (2009), who reported decreasing trends in ET o . In addition, Bandyopadhyay et al (2009) investigated areas with tropical savanna climates and found a decreasing trend in ET o throughout India during the study period, primarily caused by a notable increase in relative humidity and consistent decrease in wind speed.…”

“…Within this study, ET o was the most sensitive to maximum temperature followed by sunshine duration in the rainy and non‐rainy seasons, whereas previous work found that relative humidity (Jiang et al, 2019; Li et al, 2017; Yin et al, 2010; Zhang, Chen, & Paw, 2019), maximum temperature (for the tropical humid region and northwest arid region; Yin et al, 2010), sunshine hour (for the mountain plateau zone; Fan et al, 2016) and vapour pressure deficit (Jerszurki et al, 2019) were the most influential variables. Sensitivity analyses were not performed in other similar studies (Bandyopadhyay et al, 2009; Kosa & Pongput, 2007; Thepprasit et al, 2009; Xu et al, 2021).…”

“…Most of the other studies that focused on the influence of climate variables on ET o have been based on a sensitivity analysis (Jerszurki et al, 2019) or focused on temporal variations in ET o (Bandyopadhyay et al, 2009; Kosa & Pongput, 2007; Thepprasit et al, 2009). Although sensitivity analyses can elucidate the sensitivity of ET o to relative changes of a single variable, most sensitive climate variables might negligibly affect ET o due to the influence of temporal changes on climate variables.…”

“…Meanwhile, the few studies on ET o trends in Thailand suffer from high uncertainties, mainly because of the lack of consistency in the periods analysed (Kosa & Pongput, 2007; Thepprasit et al, 2009) and differences in data sources. For example, Kosa and Pongput (2007) and Thepprasit et al (2009) used observation data from climate stations, whereas Xu et al (2021) used monthly data products generated by the Climatic Research Unit (CRU) at the University of East Anglia (i.e., CRU TS Version 4.03 Google Earth Interface). The CRU TS4.03 has a resolution of 0.5° × 0.5° on the global scale (Xu et al, 2021).…”

Estimating daily potential evapotranspiration using GNSS-based precipitable water vapor

“…In Thailand, this method has also been applied to evaluate PET. For instance, the spatial and temporal distributions of PET were analyzed to monitor drought conditions and study climate change at the regional level [ [35] , [36] , [37] ]. However, it remains the main limitation for obtaining all required parameters due to the number of potential weather stations restriction.…”