Drought Class Transition Analysis by Markov Chains and Log-Linear Models: Approach for Early Drought Warning
Author(s):
Abstract:
In the present research, probabilistic drought characteristics, i.e., steady state probabilities of drought occurrence, drought termination and expected residence times for each severity class were studied for Mazandaran province, utilizing a modified version of Standardized Precipitation Index (SPI) for 3-, 6- and 12-month time scales and Markov chains. According to results, drought termination time and expected residence time of drought classes with increasing time series steps (from 3- to 12-month) showed increasing and decreasing trends, respectively. Furthermore, log-linear models were applied for short term prediction of drought class transition corresponding to SPI 12-month. Results also indicated that the lowest frequencies occurred during direct transitions from a given drought class to two/three classes with higher (lower) severity. Furthermore, the occurrence probability of each drought class from two previously given drought classes was calculated and validated by the log-linear model. Results of validation of the predictions during 2001 confirmed appropriateness of predictions corresponding to drought class severity for a 2-month lead time from two previous months, particularly when drought was initiating or dissipating. It is concluded that log-linear predictions of drought severity class can be used as a useful tool for early warning to farmers and water managers early in autumn.
Keywords:
Prediction , SPI index , Markov chains , Log , linear model , Early warning
Language:
Persian
Published:
Iranian Journal of Watershed Management Science and Engineering, Volume:8 Issue: 24, 2014
Page:
37
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