Spatiotemporal Distribution of Drought Based on the Standardized Precipitation Index and Cloud Models in the Haihe Plain, China

Abstract

The Haihe Plain is the largest component of the agriculturally vital North China Plain, and it is characterized by serious water shortage and frequent droughts, which lead to crop reduction and have adverse effects on agriculture and ecology. We used daily precipitation data from 1955–2017; the region’s spatiotemporal characteristics of drought were analyzed by using the standardized precipitation index (SPI), drought probability, and Mann–Kendall test for seasonal scale including two main crops growth seasons for the region’s main crops. Furthermore, a cloud algorithm model was established to analyze the dispersion and instability of the SPI. The annual drought frequency is 28.57%; the SPI for spring has an increasing tendency, while summer shows a significant decreasing trend (p < 0.05); the Haihe Plain has had a tendency towards drought over the last 63 years. The SPI in northwest is the smallest and increases gradually toward the south; the severity of drought in dry years increased from southeast to northwest. The cloud model shows that the SPI randomness of each site decreased significantly and tended to be stable and uniform. The deterministic and stable SPI of each station is stronger in dry years, and the randomness and instability are stronger in wet years. The inter-annual differences of the characteristic values of the SPI cloud model are bigger than the differences among sites, and the inter-annual randomness and inhomogeneity of the SPI are higher.