Monitoring the 1996 Drought Using the Standardized Precipitation Index

Drought monitoring using deciles index standardized precipitation index and effective Drought index in tehran province iran

Spatio-Temporal Analysis of Drought Vulnerability using the Standardized Precipitation Index (Case study: Semnan Province, Iran)

This study was conducted to identify drought event and its emerging regions in Markazi desert, Iran with focus onSemnan province in a 30 years statistical period. In this research, 61 stations having adequate data selected and usedafter extracting annual statistic from monthly and daily data. Standardized precipitation index values for each stationwere calculated and classified. The Results hav...

Drought Analysis for Kuwait Using Standardized Precipitation Index

Implementation of adequate measures to assess and monitor droughts is recognized as a major matter challenging researchers involved in water resources management. The objective of this study is to assess the hydrologic drought characteristics from the historical rainfall records of Kuwait with arid environment by employing the criterion of Standardized Precipitation Index (SPI). A wide range of...

drought monitoring based on standardized precipitation evaoptranspiration index (spei) under the effect of climate change

introduction: drought is a natural and recurrent feature of climate. the characterizations of it may change under the effect of climate change in future periods. during the last few decades a number of different indices have been developed to quantify drought probabilities. droughts are caused by disruptions to an expected precipitation pattern and can be intensified by unusually high temperatu...

Application of the ARIMA Models in Drought Forecasting Using the Standardized Precipitation Index

The standardized precipitation index (SPI) was used to quantify the classification of drought in the Guanzhong Plain, China. The autoregressive integrated moving average (ARIMA) models were developed to fit and forecast the SPI series. Most of the selected ARIMA models are seasonal models (SARIMA). The forecast results show that the forecasting power of the ARIMA models increases with the incre...