Modelling rainfall interception by urban trees

Trees in the urban environment have significant effects on the hydrological cycle by aiding in the reduction of stormwater runoff through rainfall interception. Factors such as wind exposure, relative humidity and leaf area index in the urban environment differ from those in a forest and affect the...

Full description

Saved in:
Bibliographic Details
Published inCanadian water resources journal Vol. 42; no. 4; pp. 336 - 348
Main Authors Huang, Jie Ying, Black, T.A., Jassal, R.S., Lavkulich, L.M. Les
Format Journal Article
LanguageEnglish
Published Taylor & Francis 02.10.2017
Online AccessGet full text

Cover

Loading…
More Information
Summary:Trees in the urban environment have significant effects on the hydrological cycle by aiding in the reduction of stormwater runoff through rainfall interception. Factors such as wind exposure, relative humidity and leaf area index in the urban environment differ from those in a forest and affect the processes occurring within the canopy of conifers and deciduous tree species differently. This study focused on the interception losses of trees in an urban setting with a view to providing some information on tree selection in urban environments. An analytical model was formulated based on a rainfall interception model developed for sparse canopy forests and preliminary data on water losses from tree canopy interception. The model was validated using empirical data, and an assessment of the performance of the model for four deciduous tree species (white oak, Norway maple, green ash and Prunus sp.). Model-calculated values of interception losses and throughfall were congruent with measured empirical values. Sensitivity analysis with respect to model parameter values revealed that evaporation and rainfall rates were the most sensitive parameters for model output. The ratio of evaporation rate to rainfall rate used in the model was identified as the most dynamic parameter. To measure independently the two components requires further analysis, and a more reliable measurement of leaf area index.
ISSN:0701-1784
1918-1817
DOI:10.1080/07011784.2017.1375865