Paper Information

Journal:   GEOGRAPHICAL DATA   fall 2018 , Volume 27 , Number 107 #a00476; Page(s) 25 To 26.
 
Paper: 

Presenting a soil moisture-based drought index derived from Global Land Data Assimilation System (GLDAS-SMDI) in Central Iran

 
 
Author(s):  NIAZI YAGHOUB*, TALEBI ALI, MOKHTARI MOHAMMAD HOSSEIN, VAZIFEDOUST MAJID
 
* Faculty of natural resources, Yazd University
 
Abstract: 
Introduction: Droughts are long-term phenomena that affect vast areas, causing significant economic damages andlosses in human lives. Droughts are the most costly natural disaster in the world, and affect more people than any other natural disaster. Therefore, it is important to develop early warning systems to mitigate the effects of drought. The easiest way to monitor drought is to use drought indices that calculate drought severity, duration and actual range for each drought type. Several drought indices have been developed based on different variables and parametersto assess drought types. Soil moisture is a significant hydrological variable related to flood and drought and plays an important role in the process of converting precipitation into runoff andstorage of groundwater. Due to the difficulty, cost and time required for the field measurements of soil moisture, this parameter has not been widely used in drought indexes. Recent developments of global databases, based on satellite estimates, as well as rapid progress in hardware and software for modeling complex processes governing the water balance at the ground surface, have led to many efforts to deploy this new tool to reduce the limitations in this field. In this research, a new drought index based on soil moisture, derived from the land surface models of Global Land Data Assimilation System (GLDAS-SMDI) has been provided to monitor the evolution of drought severity. Thisindex is based on the fact that soil moisture is a determinant factor in most of complex environmental processes and has an important role in the occurrence of drought...
 
Keyword(s): Dro ught Monitoring,Soil Moisture,Global Land Data Assimilation System,GLDAS-SMDI index,Central Iran
 
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