Dynamic rain model for linear stochastic environments
DOI:
https://doi.org/10.54302/mausam.v49i1.3606Keywords:
Forecasting, Stochastic, Logistic, Dry farming, Inversion risk, MexicoAbstract
To develop modem agriculture, a vision of an integral management is required, where the complexity of interactions between climatic, biological, economical, social and political factors involved in the food production must systematically be analyzed in a context of regional conditions.
At the same time, it is necessary to develop the ability to forecast both the climatic variations and their possible impact on society. The minimization of this impact on agriculture through consistent practices adequate to local climates, is not only commendable, but basically necessary, besides, the usefulness of these studies in acquiring a better knowledge of those areas with an inversion risk for agricultural and cattle rising development is high.
In this paper a statistical model is used to accomplish the objectives above mentioned. The rainfall variability in several areas of the Tlaxcala State (Mexico) is analyzed with due regard to both inter- and intra-annual relations, considering that the cumulative rainfall, in the former case, follows a logistic curve and in the latter it follows a linear, first order, stochastic process.
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