posted on 2025-12-01, 05:54authored byAbdullah YilmazAbdullah Yilmaz, Lei Yan, Serter Atabay, Lihua Xiong, Kimia Haji Amou Assar
Frequency analysis is crucial in low flow statistics, helping estimate the probability of water availability during low flow seasons and droughts. Low flow frequency analysis typically assumes stationarity, which has been challenged by climate change and variability. Therefore, non-stationary frequency analysis is essential when trends and non-stationarity exist in low streamflow data. This study developed a methodology that includes trend, change point, non-stationarity detection, and stationary and non-stationary low flow frequency analysis for annual minimum streamflow series of 7-day (Q7), 14-day (Q14), 30-day (Q30) and 90-day (Q90) periods, applied to selected river basins in Victoria, Australia. Significant decreasing trends were detected in several basins, with the strongest trends observed in the East Gippsland Basin, where the trend slopes were − 1.02, − 0.989, − 1.035 and − 1.534 for Q7, Q14, Q30, and Q90, respectively. Similarly, significant change points were found with year 2002 being the most common change point year, followed by year 1996, 2000 and 2001. Non-stationary frequency analysis proved superior in capturing the changing characteristics of low flow series. Moreover, the non-stationary models that included physical covariates outperformed those with only time covariates, highlighting the benefit of using covariates related to the physical mechanisms of low flow events. This study emphasizes the importance of non-stationary frequency analysis to prevent misleading conclusions in low flow-based water management, thereby enhancing the reliability and effectiveness of water management strategies.<p></p>