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ARS Home » Pacific West Area » Riverside, California » Agricultural Water Efficiency and Salinity Research Unit » Research » Publications at this Location » Publication #391972

Research Project: Sustaining Irrigated Agriculture in an Era of Increasing Water Scarcity and Reduced Water Quality

Location: Agricultural Water Efficiency and Salinity Research Unit

Title: Spatiotemporal distribution of drought based on the standardized precipitation index and cloud models in the Haihe Plain, China

item FU, YUJUAN - Shenyang Agricultural University
item ZHANG, XUDONG - Shenyang Agricultural University
item Anderson, Raymond - Ray
item SHI, RUIQIANG - Shenyang Agricultural University
item WU, DI - China Irrigation And Drainage Development Center
item GE, QIUCHENG - Shenyang Agricultural University

Submitted to: Water
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/20/2022
Publication Date: 5/24/2022
Citation: Fu, Y., Zhang, X., Anderson, R.G., Shi, R., Wu, D., Ge, Q. 2022. Spatiotemporal distribution of drought based on the standardized precipitation index and cloud models in the Haihe Plain, China. Water. 14(11). Article 1672.

Interpretive Summary: The North China Plain is one of the most critical agricultural regions of China and Asia and is heavily used for double cropped grain production systems. However, frequent droughts can limit the productivity of this region and one of its main components, the Haihe Plain. Therefore, it is critical to understand how the frequency, severity, and duration of drought is changing to better predict potential issues with crop production and ecosystem services. In this study, we used over 60 years of daily precipitation data to calculate a common drought index, the Standardized Precipitation Index (SPI), across the Haihe Plain. We used statistical tests and an artificial intelligence approach (cloud model) to assess the significance and patterns of changes in the SPI across Haihe Plain for the 1955-2017 time period. The results showed reduced frequency of drought in the spring and increased summer drought frequency. Overall, spring had the greatest frequency of drought, with at least some drought occurring over 35% of the time. Drought frequency and severity was also slightly greater in the northern part of the Haihe Plain compared with the south. The study highlights the potentially significant changes in drought frequency that need to be accounted for with regional agricultural management. This information will be of interest to policymakers responsible for regional production and irrigation managers who need to maximize grain production in the Haihe Plain while less groundwater for irrigation.

Technical 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.