No abstract

This paper discusses the fitting and use of models for daily rainfall observations. Nonstationary Markovchains are fitted to the occurrence of rain, and gamma distributions, with parameters which vary with the time of year, are fitted to the rainfall amounts. Numerical methods are used to derive results from these models that are important in agricultural planning. Examples include the distributions of soil water content and lengths of dry spells. The process of fitting and using these models provides a straightforward and flexible analysis for rainfall records.

No abstract

No abstract

No abstract