Abstract
Reference Evapotranspiration (ET0) is an essential factor in irrigation scheduling, climate change studies, and drought assessment. The study's main objective was to identify the influences of detrending input climatic parameters (CPs) on ET0 using linear and nonlinear approaches throughout 1980–2015 in Gangtok, East Sikkim, India. The benchmark values of ET0 were calculated using the global standard FAO56 Penman–Montieth equation. The ET0-related CPs included for the analysis are maximum temperature (Tmax), minimum temperature (Tmin), maximum relative humidity (RHmax), minimum relative humidity (RHmin), and sunshine duration (SSH). The linear and nonlinear trends in various CPs affect ET0 change. Linearly detrended series was obtained by linear regression method whereas, nonlinearly detrended series was obtained using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise method. Twenty-three scenarios, including the original scenario, 11 scenarios in Group1 (CPs de-trended linearly), and 11 scenarios in Group2 (CPs de-trended nonlinearly) were generated. Influences of Tmax and SSH were more substantial than the influences of other CPs for both Group1 and Group2. This results in the SSH masked the weak influences of other CPs. The effects of the trends in CPs, especially of SSH and Tmax, were clearly shown. The ET0 values decreased significantly during 1980–2015; however, no significant decreasing trend was observed in the case of SSH, during the same period. The nonlinear detrending gave closer results to the benchmark values as compared to linear detrending because of non-monotone variations of the ET0 and CPs. Therefore, the results from nonlinear detrending were more plausible as compared to linear detrending. The diminishing trend of ET0 prompted an overall alleviation in dry spell, hence there would be a somewhat lower risk of water use in the study region.
Better sensitivity to linear and nonlinear trends with position than with color
