Abstract — Prior knowledge on the starting dates and lengths of dry spells has a significant importance in rain-fed agriculture, irrigation planning, and various decision making processes related to climate. When reviewing statistical analyses already in existence to study the above aspects on dry spell events, it was evident that some analyses worth further review. The statistical and mathematical algorithms used to analyze dry spells varied from empirical frequency distributions to more complex statistical distributions. Empirical frequency distributions involve comparison of frequencies of dry spells at different lengths and probabilities of maximum and conditional dry spells exceeding a user specified threshold. Markov models of order 1-10, Negative Binomial, Truncated Negative Binomial, Eggemberg-Polya and Weibull distributions have been used to find the probabilities of a dry spell event greater than or equal to a certain value. Some of the fitted models were not compared with the results obtained from empirical statistical models. Also, such models have not attempted to forecast length and starting dates of dry spells and thus the information derived from past studies cannot be used efficiently for planning purposes. Further, as forecasting of all the dry spells is impossible, it is also recommended to concentrate only on the most critical dry spells. Droughts and dry spells I
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