Abstract
Rainfall partitioning by trees is an important hydrological process in the contexts of water resource management and climate change. It becomes even more complex where vegetation is sparse and in vulnerable natural systems, such as the Caatinga domain. Rainfall interception modelling allows extrapolating experimental results both in time and space, helping to better understand this hydrological process and contributing as a prediction tool for forest managers. In this work, the Gash model was applied in two ways of parameterization. One was the parameterization on a daily basis and another on a seasonal basis. They were validated, improving the description of rainfall partitioning by tree species of Caatinga dry tropical forest already reported in the scientific literature and allowing a detailed evaluation of the influence of rainfall depth and event intensity on rainfall partitioning associated with these species. Very small (0.0–5.0 mm) and low-intensity (0–2.5 mm h−1) events were significantly more frequent during the dry season. Both model approaches resulted in good predictions, with absence of constant and systematic errors during simulations. The sparse Gash model parametrized on a daily basis performed slightly better, reaching maximum cumulative mean error of 9.8%, while, for the seasonal parametrization, this value was 11.5%. Seasonal model predictions were also the most sensitive to canopy and climatic parameters.
Highlights
Water availability is limited in arid and semiarid regions, with rainfall interception playing an important role on site and catchment water balances, as well as in the context of climate change [1]
A mean rainfall intensity of 1.7 mm h−1 was found when modelling the interception in central–western Spain [2], while rainfall intensities equal to 1.8 and 2.3 mm h−1 were reported for semiarid regions of China and Kenya, respectively [24,50]
The frequency distributions of the event size and intensity were in agreement with other studies about rainfall partitioning in semiarid regions [16,23,24]
Summary
Water availability is limited in arid and semiarid regions, with rainfall interception playing an important role on site and catchment water balances, as well as in the context of climate change [1]. Rainfall partitioning by trees is an intricate process, mainly affected by canopy and weather factors, such as the characteristics of rainfall events, becoming even more complex where vegetation is sparse [2]. There are few studies about simulating or evaluating the rainfall interception in Caatinga vegetation [1,13,14,15,16]. This domain corresponds to an area of tropical dry forest with deciduous tree-shrubs, which covers close to one million km in the Northeast of Brazil, occupying around 50% of this region [17].
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