资源环境科技发展态势分析平台

Snow is a major source of water in the western US and has been observed showing variability posed by climate change. The snow variability of the region has been associated with the droughts affecting the societies relying on snow driven rivers. The current study evaluates the spatiotemporal variability of western US snow water equivalent (SWE) over 58 years (1961-2018) as a trend and a shift. The current study tests whether the SWE is consistent during El Nino - Southern Oscillation (ENSO) phases utilizing the Kolmogorov - Smirnov (KS) test. Trend analysis was performed on the SWE data of each ENSO phase. Shift analysis was performed in the entire time series of 58 years. Additionally, the trend in the SWE data was evaluated before and after shift years. Mann-Kendal and Pettit's tests were utilized for the detection of trend and shift respectively. The serial correlation was taken into account during the trend evaluation, while Thiel-Sen approach was used for the evaluation of the trend magnitude. The serial correlation in time series which is the potential cause of overestimation and underestimation of the trend evaluation was found to be absent in the SWE data. The results suggested a negative trend and a shift during the study period. The negative trend was absent during neutral years and present during El Nino and La Niiia years. The trend magnitudes were maximum during La Niiia years followed by those during El Nino years and the entire length of the data. It was also observed that if the presence of negative shift in the SWE was considered, then most of the stations did not show a significant trend before and after the occurrence of a shift. The current study can be utilized by water managers to develop future water management policies, plans, and strategies in the western United States.