Ning Zeng
Department of Atmospheric Sciences and
Institute of Geophysics and Planetary Physics
University of California, Los Angeles
James W. Shuttleworth
Department of Hydrology and Water Resources
University of Arizona
John H. C. Gash
Institute of Hydrology
Wallingford, UK
An interception model is derived that links the temporal variability of rainfall with the storm-based description of the interception process. Analytical formulae for long-term interception loss are obtained for precipitation with statistical characteristics derived from observations.
The analysis of the results indicates that point interception loss is controlled primarily by three time scales: the mean inter-storm arrival time $\tau_a$, the mean storm duration $\tau_r$, and the time to evaporate a saturated canopy $\tau_0$ which depends on canopy water holding capacity $W_c$ and the wet canopy potential evaporation rate $E_{I0}$, and less importantly, on storm intensity. Additional assumption of rainfall stationarity leads to a relation between long-term interception loss and gross rainfall that requires a very small amount of input data.
The interception loss predicted by the analytical model agree well with that of a Rutter model driven by a synthetic rainfall time series with the same statistics. Using the parameter values estimated from the observed rainfall data in the Amazon and southwestern France, the analytical results predict long-term interception loss close to that observed.