Quantification of Cloud Water Interception in the Windward Highlands of San Cristobal Island (Galapagos)

Abstract:

Cloud water interception (CWI) by the vegetation can be an important water input to ecosystems subjected to fog occurrence. In this work, we propose a methodology to estimate CWI by a forest using a Rutter-type interception model. The approach requires the acquisition of input and calibration datasets. Inputs consist in continuous records of meteorological variables, which include cloud water interception using a fog gauge system. Meanwhile, samples of throughfall are necessary for the calibration and validation of the model only and not as inputs, which is an important advantage considering that continuous records of throughfall are challenging to obtain. During two hydrological years, the model has been implemented in an endemic forest of the windward highlands of San Cristobal Island, in which the presence of fog is semi-permanent during half of the year (cool season). In these conditions, this is the first compiling approach for water balance estimation. Results show that CWI reaches 23% and 10% of the total water input of the first and second year, respectively. During the hot seasons, where fog is absent, CWI is negligible as expected, while it represents 37% and 19% of the total water inputs during the first and second cool seasons, respectively. Despite similar wind speed intensities are observed in both cool seasons, the higher value of CWI in the first cool season compared to the second one (535 mm and 305 mm for the first and second year, respectively) is related to higher liquid water content in the air that combined with the observed wind speed intensities, leads to better conditions of CWI. This methodology provides an indirect quantification of CWI by the vegetation from artificial fog gauges, it identifies controlling factors of CWI and it could be used to compare CWI in contrasting land covers.