Linking NDVI-derived vegetation dynamics with air temperature to model interception and transpiration processes of a conceptual hydrological model

Vegetation dynamics play a critical role in canopy interception and transpiration, yet its representation in hydrological models is often simplified or even entirely omitted. Rising air temperatures have been shown to shift the timing and extend the duration of the vegetation period, directly affecting evapotranspiration. Incorporating vegetation dynamics into hydrological models is therefore essential, particularly in studies assessing the impacts of climate change. In this study, we employ satellite‑derived Normalized Difference Vegetation Index (NDVI) data to parameterize vegetation processes within a distributed HBV-type rainfall–runoff model. For each land cover class in the Upper Danube basin, NDVI regimes over a 25‑year period were derived by averaging values from 1,000 randomly selected points. Seasonal vegetation dynamics were then characterized by fitting trapezoid functions to the annual NDVI regimes, yielding estimates of the onset and end of the growing season.

The analysis of vegetation characteristics revealed that certain land cover classes (particularly deciduous forest, agricultural land and pastures) exhibit notable changes including increases in mean annual NDVI values and earlier onset of the growing season. Moreover, the timing of the active growing season was found to correlate with air temperature indices, such as the number of days above or below certain thresholds. These relationships were used to calibrate temperature thresholds and consecutive day counts to estimate the start and end of the vegetation period. The methodology was implemented in the Upper Danube basin as a case study, providing a foundation for further evaluation of its impact on hydrological simulations. By explicitly linking vegetation dynamics to temperature indices, the approach enables hydrological models to operate independently of direct NDVI observations, which are unavailable in climate change impact studies, while also accounting for elevation effects, as cooler temperatures at higher altitudes naturally delay vegetation onset.