Drought Analysis and Forecast Using Landsat-8 Sattelite Imagery, Standardized Precipitation Index and Time Series

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

Correlation Analysis and Analysis of Drought Time Series Based on Modis Satellite Images and Standardized Precipitation Climatic Index (SPI) on the eastern slope of Zagros

Introduction Drought is one of the environmental disasters that is very frequent in arid and semi-arid regions of the country. Rainfall defects have different effects on groundwater, soil moisture, and river flow. Meteorological drought indices are calculated directly from meteorological data such as rainfall and will not be useful in monitoring drought if the data are missing. Therefore remot...

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...

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...

Using Wavelets and Splines to Forecast Non-Stationary Time Series

 This paper deals with a short term forecasting non-stationary time series using wavelets and splines. Wavelets can decompose the series as the sum of two low and high frequency components. Aminghafari and Poggi (2007) proposed to predict high frequency component by wavelets and extrapolate low frequency component by local polynomial fitting. We propose to forecast non-stationary process u...