Development of Agricultural Drought Risk Assessment Model for Kermanshah Province (Iran), using satellite data and intelligent methods

• Published in: Options Méditerranéennes. Série A : Séminaires Méditerranéens (CIHEAM) no. 80
• Main Authors: Arshad, S.; Morid, S.; Agha Alikhani, M., Tarbiat Modares University, Tehran (Iran). College of Agriculture, Reza Mobasheri, M., Khaje Nasiredin Toosi University, Tehran (Iran). College of Remote Sensing
• Format: Journal Article
• Language: English
• Published: Zaragoza (Spain) CIHEAM-IAMZ 2008
• Subjects: DROUGHT; GENETIC ALGORITHM; http://www.fao.org/aos/agrovoc#c_2391; http://www.fao.org/aos/agrovoc#c_4881; MODELE; MODELOS; PRINCIPLE COMPONENT ANALYSIS; SECHERESSE; SEQUIA; VULNERABILITY ASSESSMENT
• ISBN: 9782853523905; 285352390X
• ISSN: 1016-121X

Agriculture sector has been affected by severe droughts during recent years in Iran. The existence of an agriculture drought warning system can be a useful means for preparedness and to reduce the consequent losses. This study develops a drought agricultural drought vulnerability assessment model using statistical and intelligent methods for Kermanshah province. The model is specific to rainfed wheat and barley and is able to assess real-time agricultural drought vulnerability associated with crop yield losses at critical phenological stages during the growing season. The model inputs are a combination of drought indices including: PDSI, Z-index, CMI,SPI and EDI, using genetic algorithm method. The model results show that the accurate rates are lower at the first stage than those during the later stages. Enhancement of the model with a Geographic Information System (GIS) has also made the model more capable for spatial analysis