The use of a shuffled complex evolution algorithm for calibration of a dynamic leaf emergence model leads to better spatial ETa predictions

ABSTRACT Dynamic phenology has so far been a modelling aspect that has received little attention. However, it has been shown that leaf emergence takes place earlier due to the shift in vegetation phase caused by climate change and is strongly dependent on temperature. Here, we demonstrate the calibration of a model for dynamic phenology within the water balance model WaSiM. Temperature sums and dormancy are used as controlling variables. The calibration of the respective parameters was realised using a shuffled complex evolution algorithm. ETa relevant parameters were calibrated based on MODIS data as a reference. Evaluation was done by comparing the ETa curves to MODIS ETa curves as well as a comparison of spatial ETa patterns based on Landsat ETa data. The evaluation shows that the dynamic phenology model used is capable of predicting the start of leaf emergence while also leading to better fitting evapotranspiration curves for the deciduous forest compared with the initial static parameterisation approach.