آنالیز ویژگی های جامع خشکسالی بر اساس یک شاخص غیر خطی چند متغیره خشکسالی Comprehensive drought characteristics analysis based on a nonlinear multivariate drought index

1. Introduction Droughts and floods are extreme events (Mishra and Singh, 2010; Hao et al., 2016; Maity et al., 2016) in nature causing great harm to humans, agricultural production and society. They are especially damaging in the northwest arid area of China (Li et al., 2011; Hao et al., 2016). According to statistics, global economic losses due to droughts reached up to 6-8 billion dollars, far exceeding losses caused by other meteorological disasters (Wilhite, 2001). More seriously, water demand has climbed sharply due to the expanding scale of industry, agriculture, energy, development of the social economy, global warming, and rapid increase of the world’s population. It has led to the exacerbation of the water shortage and obvious global drought trend (Cammalleri et al., 2015; Nam et al., 2015; Caracciolo et al., 2016). Therefore, an accurate drought risk assessment is fundamental to prevent and mitigate drought disasters. Drought event identification is the basis of drought risk assessment. Drought event is a multivariate phenomenon (Xu et al., 2015). Its negative influence presents multivariate drought characteristics (such as drought duration, peak, severity, and affected area). Traditional drought risk assessment only considers one drought characteristic and may not reflect the complex characteristics of drought events (Xu et al., 2015). Therefore, one purpose of this study is the multivariate drought risk assessment considering three drought characteristics: drought duration, peak, and severity. To accurately identify drought events, a dependable drought index is indispensable. Drought index can reflect drought anomalies or degrees (Wilhite, 2001), and is also the basis for credible drought risk assessment. It is primarily employed to quantify or monitor drought events. Currently, numerous drought indices, including single, multiple, and composite indices (Mishra and Singh, 2010, Cammalleri et al., 2015; Waseem et al., 2015) have been used to evaluate different types of droughts. A single drought index only considers one variable, such as precipitation, runoff or soil moisture (Waseem et al., 2015). A multiple drought index takes more variables into consideration. A single drought index or multiple drought index mostly can typically reflect one type of drought (meteorological, hydrological, agricultural or socioeconomic drought). In addition, drought events identifications based on different drought indices are a little bit different from each other. Most importantly, different types of droughts may occur simultaneously, and it is hard to distinguish them (Hao and Singh, 2015). Therefore, the single and multiple drought indices are insufficient to reveal the complicated relationship among different variables. To overcome this issue, the composite index was proposed.