Amir Naghibi

Water balance models provide insights into ongoing changes in the water cycle. Among them, monthly water balance models (MWBMs) are especially suitable for large-sample and global assessments, which are important for adaptation to global environmental change. This study evaluates monthly water balances from 14 models across more than 2,000 global catchments, comparing the modelś capacities to reproduce water-cycle processes and produce results. We showed that most of the considered models produce reasonable runoff simulations across most settings. However, notably not in catchments at latitudes above 60°N or when the ratio of snowfall to total precipitation exceeds 20 %. By contrast, the inclusion of a non-linear snow module enabled the extended models to achieve similarly good performance in snow-affected basins as in non-snow basins. The improved fit was not mainly due to an increased number of fitting parameters, but rather to a better representation of physical processes, including freeze–thaw cycles. Furthermore, models generally performed slightly better in relatively humid regions than in arid ones. For instance, performances were not sensitive to model structure when catchments were humid enough, with approximate thresholds of annual precipitation exceeding 1000 mm and annual runoff exceeding 300 mm. Also, simulation results for larger catchments were frequently more stable than those for smaller catchments. We expect these insights could aid in assessing, identifying, and addressing potential biases in regional water balance modeling studies worldwide, which may be important for finding effective solutions to mitigate the effects of ongoing hydroclimatic change.