SPI-based Regional Drought Prediction Using Weighted Markov Chain Model
نویسنده
چکیده
Drought is one of the most serious natural disasters in China. Drought disasters occur frequently and caused huge economic loss in recently. In this paper, a drought prediction model based on weighted Markov Chain is put forward. An application is demonstrated by Anhui province of Huaihe River in China. Based on the precipitation data during 1958-2006 at monthly scale, the different time scales Standardized Precipitation Index (SPI) is computed and the occurrence frequency of extreme drought, severe drought, moderate drought, slight drought and non-drought is obtained. The prediction of SPI is conducted by weighted Markov Chain model and the prediction accuracy is computed for the SPI of different time scales. The results show that weighted Markov Chain model is an effective tool for drought prediction and can provide decision-making for regional drought management.
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