Comparison of drought stress indices in beech forests: a modelling study

Abstract

Abstract: Two drought stress indices were applied to managed as well as old-growth beech forests and gaps for the 2001 to 2013 period to aid in the development of an efficient tool for field water supply diagnosis. The relative extractable soil water (REW), which was calculated from the soil water content in the root zone, and the transpiration index (TI), calculated as the ratio between the actual and potential transpiration were used. Both indices were calculated on a daily basis using the water balance model BROOK90, which was fitted and tested using measured data on throughfall and soil water content. A sensitivity analysis apportioned to the input parameters of the drought stress indices was conducted to assess uncertainty. Both drought stress indices showed the greatest drought stress in the years 2009, 2003 and 2011, as also indicated by the Standardized Precipitation Evapotranspiration Index (SPEI) at the nearest meteorological station. However, drought stress intensity and duration differed between the indices and study sites. Greater water supply stress was shown in the forests than the gaps. Furthermore, the agreement among the indices was smaller for gaps compared with forests, which implies that careful index selection is needed when comparing water supply stresses in different stages of forest stand development. Due to the low amount of input data required and the parameters that can be measured with relative ease in the field, REW might be an efficient tool for field water supply diagnosis when analyzing the drought stresses of similar forest types and at unique stages of development. REW satisfactorily indicated drought stress in forests but to a lesser extent in gaps. TI demonstrated more consistent differences in drought stress between forests and gaps and therefore proved to be the appropriate index for a detailed analysis of drought stress variation between different stages of forest stand development. However, due to a greater number of required input data and more demanding parameters, TI appears to be a more complex tool than REW for field water supply diagnosis in forests.