Image from Google Jackets

A rainfall generator for agricultural applications in the tropics

By: Contributor(s): Material type: ArticleArticleLanguage: English Description: 63(1993):1-19Subject(s): LOC classification:
  • 60004
In: Agricultural and Forest Meteorology (Netherlands)Summary: A new rainfall generator, based on a third-order Markov chain, has been developed to simulate the year-to-year variation in rainfall amount that is observed in the tropics. To do this, some of the parameters of the model are themselves sampled randomly. The model has been fitted to over 40 sites in the tropics. The model was tested in detail for three sites in Central and South America and in the African Sahel. Few significant differences were found between the historical and simulated means and variances of yearly and monthly rainfall amount and raindays per month. There were some problems with simulating wet and dry sequences of longer than 9 days. When historical and simulated rainfall records were used to drive a crop simulation model, there was no significant difference in the mean and variance of maize yield response. The results reported suggest that the rainfall model performs adequately for many applications.
Tags from this library: No tags from this library for this title.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Collection Call number Copy number Status Date due Barcode Item holds
Journal Article Journal Article CIAT Library Document collection CINFOS Document Collection CINFOS 60004 (Browse shelf(Opens below)) c.1 Short Loan 100071050
Total holds: 0

A new rainfall generator, based on a third-order Markov chain, has been developed to simulate the year-to-year variation in rainfall amount that is observed in the tropics. To do this, some of the parameters of the model are themselves sampled randomly. The model has been fitted to over 40 sites in the tropics. The model was tested in detail for three sites in Central and South America and in the African Sahel. Few significant differences were found between the historical and simulated means and variances of yearly and monthly rainfall amount and raindays per month. There were some problems with simulating wet and dry sequences of longer than 9 days. When historical and simulated rainfall records were used to drive a crop simulation model, there was no significant difference in the mean and variance of maize yield response. The results reported suggest that the rainfall model performs adequately for many applications. eng

Powered by Koha