Agricultural drought dynamics in China during 1982–2020: a depiction with satellite remotely sensed soil moisture

IF 6 2区 地球科学 Q1 GEOGRAPHY, PHYSICAL GIScience & Remote Sensing Pub Date : 2023-09-19 DOI:10.1080/15481603.2023.2257469
Hao Sun, Qian Xu, Yunjia Wang, Zhiyu Zhao, Xiaohan Zhang, Hao Liu, Jinhua Gao
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Abstract

Agricultural drought (AD) is a serious threat to food security for many regions worldwide. Understanding the dynamics of AD contributes to preventing or mitigating its adverse impacts. Soil moisture (SM) anomaly is a relatively straightforward indicator of AD. However, most of the previous studies on AD dynamics of China were conducted with non-remotely sensed SM indicators due to the lack of long-term and spatial-continuous SM datasets. Here, such an SM dataset was created by enhancing a satellite remote sensing SM dataset with a machine learning method XGBoost, various remote sensing datasets, and some surface or meteorological parameters from reanalysis data. The new SM dataset has a period of 1982–2020, a spatial resolution of 0.25°, and a temporal resolution of 1 month. Furthermore, Standardized SM Index at one-month scale (SSMI1) was calculated, and AD events were identified using the SSMI1 and a 3-dimensional clustering method. Results demonstrated that 1) the new SM presented comparable or even better performances with the original SM as evaluated with spatial distributions, in-situ SM observations, and manufactured data gaps. 2) The AD was most frequent in North China, followed by the western parts of East China, Northeast, and Southwest China. The centroids of identified AD events were found chiefly in the Northeast, North, Southwest, and western parts of East China. 3) The severity of AD events presented a decreasing trend from 1982 to 2020, while significant drying trends were found mostly in the southern parts of North China, western parts of East China, and Southwest China. 4) The AD dynamics revealed in this study are basically consistent with other studies but also have unique features such as more space details and less drought frequency and count than that of meteorological drought. Further studies are expected to create a long-term satellite SM with faster timeliness, higher resolution, and greater depth.
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1982-2020年中国农业干旱动态:基于卫星遥感土壤湿度的描述
农业干旱是全球许多地区粮食安全面临的严重威胁。了解AD的动态有助于预防或减轻其不利影响。土壤湿度(SM)异常是AD相对直接的指标。然而,由于缺乏长期和空间连续的SM数据集,以往对中国AD动态的研究大多采用非遥感SM指标。本文利用机器学习方法XGBoost、各种遥感数据集以及再分析数据中的一些地表或气象参数对卫星遥感SM数据集进行增强,创建了这样一个SM数据集。新的SM数据集周期为1982-2020年,空间分辨率为0.25°,时间分辨率为1个月。计算一个月尺度的标准化SM指数(SSMI1),利用SSMI1和三维聚类方法对AD事件进行识别。结果表明:1)从空间分布、原位观测和人工数据间隙等方面评价,新模型与原始模型具有相当甚至更好的性能。2) AD以华北地区最常见,其次是华东西部、东北和西南地区。3) 1982 - 2020年,AD事件的严重程度呈下降趋势,而显著的干旱趋势主要集中在华北南部、华东西部和华北南部。4)与气象干旱相比,本研究揭示的AD动态与其他研究基本一致,但也具有空间细节更多、干旱频率和次数较少等独特之处。进一步的研究有望创造出具有更快及时性、更高分辨率和更深深度的长期卫星SM。
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来源期刊
CiteScore
11.20
自引率
9.00%
发文量
84
审稿时长
6 months
期刊介绍: GIScience & Remote Sensing publishes original, peer-reviewed articles associated with geographic information systems (GIS), remote sensing of the environment (including digital image processing), geocomputation, spatial data mining, and geographic environmental modelling. Papers reflecting both basic and applied research are published.
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