Development of the seasonal non-monotonic Mann-Kendall test for hydroclimatic data

Climate change can show different characteristics at low and high values of a time series, leading to non-monotonic trends. The Mann-Kendall (MK) and seasonal MK tests can only detect monotonic trends and ignore different behaviors in low and high value groups. To overcome this limitation, extending the recently proposed non-monotonic MK (NMK) test, the seasonal NMK (SNMK) test is proposed. The method was applied to four stations in Türkiye with four different climatic and topographic characteristics using monthly total precipitation data for the 1969-2020 for seasonal trend behavior. The results showed that while no significant trends were detected in entire time series, intra-seasonal and annual data, both monotonic and non-monotonic significant trends emerged in seasonal analyses. Especially in two stations, opposite changes in low and high values, increased seasonal variance and non-monotonic seasonal trends were observed. The test can be used for regional trend analysis by replacing seasonal data with regional data. It is also predicted that the SNMK test can be used as an effective decision support tool in areas with high seasonality such as water resources management, agriculture, energy planning and disaster management.