Modelling interception and transpiration at monthly time steps : introducing daily variability through Markov chains; Proefschrift Technische Universiteit Delft.

This dissertation presents improved equations for monthly water resources models, in particular for interception and transpiration. Most ofthe existing monthly models do not make a distinction between interception and transpiration, while this distinction is very important for management purposes. Interception is direct feedback to the atmosphere, important to sustain rainfall. Transpiration is a good indicator for plant growth and biomass production. The distinction also contributes to the estimation of recharge and therewith of runoff. The derivations are based on the Markov theory for the occurrence of raindays. The methodology can be used on the basis of an analysis of a few time series of daily data, at a spatial scale of 300 km and not necessarily of the same period as the monthly data. Zimbabwe served as the case study for this dissertation, but the derived equations can be used worldwide as long as the relationship between the monthly rainfall and the mean number of rain-days can be established. The analytical equations obtained are simple and can be easily introduced into GIS or spreadsheet applications. The method offers a valuable tool for water managers and hydrologists, who need to make water resources planning decisions based on limited data and with limited available time