Predicting water supply and evapotranspiration of street trees using hydro-pedo-transfer functions (HPTFs)
The climate, soil properties, groundwater depth, and surrounding settings in cities vary to a tremendous extent, which all lead to different growing conditions and health for street trees. Because of climate change, the availability of water in cities will undergo changes in the next decades. As urban trees have a very positive influence not only on microclimate but also on biodiversity and life quality in general, they need to be protected. Thus, we need to know how to measure and calculate the availability of water for street trees to optimize their site conditions and water supply. This study presents Hydro-Pedo-Transfer Functions (HTPFs) for predicting water supply and actual evapotranspiration of street trees for varying urban conditions. The HTPFs are easy to use, and the input parameters can either be mapped easily or taken from local climate agencies or soil surveys. The first part of the study focuses on the theoretical background and related assumptions of the HTPFs for predicting water supply, and on obtaining the potential and actual evapotranspiration of urban street trees using easily available data. The second part gives information and exemplifies how this input data can be measured, mapped, or predicted. Calibration of the HTPFs were done using the sap-flow measurements of three Linden trees (Tilia cordata). Exemplarily, the HTPF scenarios for the varying urban site conditions of Berlin are presented. The water supply and actual evapotranspiration of the street trees severely depend on the local climate (summer rainfall and potential evapotranspiration), site conditions (catchment area, soil available water, and degree of sealing), and on the tree characteristics (species, age, and rooting depth). The presented concept and the equations build a good and flexible frame that is easy to program using a spreadsheet tool or an R script. This tool should be tested and validated also for other cities and climate regions.
Published in: Forests, 10.3390/f12081010, MDPI