How to predict hydrological effects of local land use change: how the vegetation parameterisation for short rotation coppices influences model results

Abstract

Among the different bioenergy sources, short rotation coppices (SRC) with poplar and willow trees are one of the promising options in Europe. SRC provide not only woody biomass but also additional ecosystem services. However, a known shortcoming is the potentially lower groundwater recharge caused by the potentially higher evapotranspiration demand compared to annual crops. The complex feedbacks between vegetation cover and water cycle can be only correctly assessed by application of well-parameterised and calibrated numerical models. In the present study, the hydrological model system WaSim (Wasserhaushalts-Simulations-Model) is implemented for assessment of the water balance. The focus is the analysis of simulation uncertainties caused by the use of guidelines or transferred parameter sets from scientific literature compared to "actual" parameterisations derived from local measurements of leaf area index (LAI), stomatal resistance (Rsc) and date of leaf unfolding (LU). The analysis showed that uncertainties in parameterisation of vegetation lead to implausible model results. LAI, Rsc and LU are the most sensitive plant physiological parameters concerning the effects of enhanced SRC cultivation on water budget or groundwater recharge. Particularly sensitive is the beginning of the growing season, i.e. LU. When this estimation is wrong, the accuracy of LAI and Rsc description plays a minor role. Our analyses illustrate that the use of locally measured vegetation parameters, like maximal LAI, and meteorological variables, like air temperature, to estimate LU give better results than literature data or data from remote network stations. However, the direct implementation of locally measured data is not always advisable or possible. Regarding Rsc, the adjustment of local measurements gives the best model evaluation. For local and accurate studies, measurements of model sensitive parameters like LAI, Rsc and LU are valuable information. The derivation of these model parameters based on local measurements shows the best model fit. Additionally, the adjusted seasonal course of LAI and Rsc is less sensitive to different estimates for LU. Different parameterisations, as they are all eligible either from local measurements or scientific literature, can result in modelled ground water recharge to be present or completely absent in certain years under poplar SRC.