Rainfall interception and drop size-development and calibration of the two-layer stochastic interception model.

This paper reviews the development of the stochastic interception model from the original, single-layer, drop-size-dependent model to the two-layer model that recognizes that vegetation canopies are wetted through both the primary impact of raindrops to the top layer of the canopy and secondary impacts from drops falling from the vegetation to lower layers of the canopy. It is shown that drop volumes of primary raindrops can be calculated from the Marshall-Palmer distribution and drop volumes of secondary drops can be estimated from disdrometer measurements of the characteristic volume appropriate to the particular vegetation species. It is recognized that, in addition to the volume-dependent stochastic wetting effect, there is also another drop-size-dependent wetting effect that is related to the kinetic energy of the raindrops, which reduces the maximum storage that can be achieved on the canopy. The predicted wetting functions for canopies of different density are described and compared with observations made with the use of a rainfall simulator. It is also shown that the species-dependent model parameters can be determined from measurements made with the rainfall simulator. The improved performance of the model compared with conventional interception models is demonstrated for a tropical forest in Sri Lanka. Application of the two-layer model may explain why interception losses from coniferous, fine-leaved forests in the temperate, low-intensity rainfall climate of the uplands of the U.K. are among the highest in the world, whereas interception losses from tropical broad leaved forest in high-intensity rainfall climates of the tropics are among the lowest.