College of Water Resources and Architectural Engineering, Northwest A&F University, 712100, Shaanxi, PR China; Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, Shaanxi, PR China.
Department of Physics, Islamia College, Peshawar 25130, Khyber Pakhtunkhwa, Pakistan.
Sci Total Environ. 2021 Mar 10;759:143530. doi: 10.1016/j.scitotenv.2020.143530. Epub 2020 Nov 17.
Increasing frequency and intensity of extreme drought events have harmed the environment, ecosystem, and agricultural productivity. However, the characteristics of agricultural drought in China have not been well understood. The remote sensing (RS) based gridded monthly precipitation, soil moisture, land surface temperature (LST), and normalized difference vegetation index (NDVI) datasets over 1982-2018 were utilized to derive standardized precipitation index (SPI), standardized soil moisture index (SSI), multivariate standardized drought index (MSDI), and vegetation health index (VHI). The variation patterns and trends of SPI, SSI, and MSDI at the 1-, 3-, and 6-month timescales against monthly VHI anomaly were compared to identify the best agricultural drought index in China. The drought variations in the four sub-regions (northwest, north, Qinghai-Tibet area, and south area) were also investigated. The results showed that: (1) Temporal patterns of VHI anomaly were similar to relative soil moisture and slightly different from precipitation. The spatial patterns of MSDI matched with VHI the best than SPI and SSI. (2) All three indices showed positive correlations with VHI at the three timescales. The highest correlation coefficients (r) between MSDI and VHI ranged from 0.25 to 0.67, 0.22 to 0.78, 0.23 to 0.69, and 0.19 to 0.74 in northwest China, north China, Qinghai-Tibet Plateau, and south China, respectively. (3) The connections between monthly VHI and the three drought indices were weaker at the 1-month timescale (0.16 < r < 0.25) than the 3-month (0.39 < r < 0.78) and 6-month (0.26 < r < 0.68) timescales. (4) The VHI significantly increased in most of China except north China. Overall, MSDI showed better performance for monitoring agricultural drought in China's mainland.
极端干旱事件的频率和强度不断增加，对环境、生态和农业生产力造成了危害。然而，中国农业干旱的特征尚未得到很好的理解。本研究利用基于遥感（RS）的 1982-2018 年月度格点降水、土壤水分、地表温度（LST）和归一化差异植被指数（NDVI）数据集，推导出标准化降水指数（SPI）、标准化土壤水分指数（SSI）、多变量标准化干旱指数（MSDI）和植被健康指数（VHI）。比较了 1、3 和 6 个月时间尺度上 SPI、SSI 和 MSDI 与月度 VHI 异常的变化模式和趋势，以确定中国最佳的农业干旱指标。还研究了四个子区域（西北、北方、青藏高原和南方）的干旱变化。结果表明：（1）VHI 异常的时间模式与相对土壤湿度相似，与降水略有不同。MSDI 的空间模式与 VHI 最为匹配，其次是 SPI 和 SSI。（2）在三个时间尺度上，所有三个指数与 VHI 均呈正相关。MSDI 与 VHI 的相关系数（r）最高，范围分别为 0.25 至 0.67、0.22 至 0.78、0.23 至 0.69 和 0.19 至 0.74，在中国西北、华北、青藏高原和南方地区。（3）在 1 个月时间尺度（0.16 < r < 0.25）上，月度 VHI 与三个干旱指数之间的联系弱于 3 个月（0.39 < r < 0.78）和 6 个月（0.26 < r < 0.68）时间尺度。（4）除华北地区外，中国大部分地区的 VHI 均显著增加。总体而言，MSDI 在中国大陆监测农业干旱的表现更好。
