Hydro‐pedo‐transfer‐functions expressing drought and memory effects on pine tree growth

Over the last 30 years, the impact of climate change in Berlin, Germany, has manifested in the form of reduced summer rainfall, elevated temperatures, and a notable rise in the frequency of days with temperatures surpassing 30°C. All of them are leading to a decreasing water supply and increasing risk of drought. Various field, laboratory, and numerical simulation studies have been done for deriving information on long‐term potential and actual evapotranspiration, water stress during the vegetation period (April–September), and tree ring growth of various pine tree stands in Berlin. Data analysis highlights periodical climate patterns and complex interactions between drought, water supply, and plant growth. Annual tree ring growth is not only related to the actual weather conditions but also to the past climate years. With decreasing water supply, this kind of drought memory effect increases up to 5 years into the past. For Berlin's climate, it is noteworthy that late summer, particularly the water stress in August, represents the most sensitive indicator for tree ring growth. For regionalization purposes, long‐term numerical simulations were done to derive hydro‐pedo‐transfer‐functions (HPTFs) predicting the water stress coefficient of the growing season (Eact‐s/Epot‐s). They only need easily available information such as soil texture, climate water balance, and groundwater depth. Two HPTFs were successfully tested and can be easily applied by geo‐information systems. However, for other climate regions and tree species, HPTFs need to be adapted. Core Ideas Effects of climate change on water supply of pine trees on sandy soils in Central Europe were studied. Tree ring growth was explained using the ratio of actual and potential evapotranspiration predictions. Memory effects of drought on tree ring width were studied. Growth‐effective periods within the vegetation period were evaluated. Hydro‐pedo‐transfer‐functions expressing water stress coefficient using easily available site information for geo‐information systems‐applications were derived.