Spatiotemporal variation of soil moisture in Northern China based on climate change initiative data

Abstract

In view of the sparse, uneven distribution and poor data continuity of measured soil moisture sites in China and the lack of large-scale research, the soil moisture data set of the European Space Agency (ESA) Climate Change Initiative (CCI) was applied to carry out spatial-temporal variation analysis of soil moisture in five agricultural ecological zones in Northern China. The Pearson correlation coefficient and multiplecomponent metric Kling-Gupta efficiency were used to verify the validity of remote sensing data and to analyze the temporal and spatial variation of soil moisture with the concept of temporal and spatial persistence. The ESA CCI remote sensing soil moisture data had good spatial and temporal adaptability for the whole year in the Huang-Huai-Hai region, in summer in Northeast China, in spring in Northwest China, in summer and autumn in the Loess Plateau, and in summer and autumn in the Inner Mongolian Plateau. The annual mean soil volume water content in Northern China from 1991 to 2016 was 0.06-0.39 m 3 m −3 . Spatially, soil moisture in Northern China has been gradually increasing from west to east. In this area, seasonally, soil moisture was the highest in summer, followed by autumn and then winter and spring.Northeast China, the Loess Plateau, and the Huang-Huai-Hai region are important grain-producing areas in China. The soil moisture in these areas fluctuates widely with seasonal changes and shows an obvious drying trend.Soil water plays an important role in controlling land-air water and energy exchange. Evapotranspiration, infiltration, and runoff of soil water have a great impact on water circulation and crop growth (Peng, Niesel, Loew, Zhang, & Wang, 2015). In arid and semi-arid regions, soil moisture content determines the growth status of green vegetation and agricultural productivity. A long-term lack of soil moisture is likely to cause an imbalance in energy exchange between the atmo-

Agriculture, biology, and environment: Twenty first century challenges and opportunities

“…For important grain producing areas of China, Yao et al. (2020) studied the spatiotemporal variation of soil moisture using European Space Agency Climate Change Initiative data and found strong seasonality in soil moisture. Deng, Liu, Tian et al.…”

“…used leaf explants to improve the regeneration of J. curcas. For important grain producing areas of China,Yao et al (2020) studied the spatiotemporal variation of soil moisture using European Space Agency Climate Change Initiative data and found strong seasonality in soil moisture. sequenced chloroplast genomes (cp genome) of three wetland plants, Umbrella papyrus (Cyperus alternifolius L.), the Powdery alligator-flag (Thalia dealbata Fraser), and Indian shot (Canna indica L.).…”

Enhanced soil moisture improves vegetation growth in an arid grassland of Inner Mongolia Autonomous Region, China

“…An et al (2016) has demonstrated its good performance in analyzing China's grassland dynamics. Yao et al (2021) used 0-10 cm soil moisture site measurement data released by China Meteorological Network to verify the accuracy of ESA CCI-SM grid data. The results also showed that ESA CCI-SM data had a good consistency with the site measurement data in summer and autumn in Inner Mongolia.…”

Spatial and Temporal Variability of Soil Moisture and Its Driving Factors in the Northern Agricultural Regions of China

“…Currently, the commonly used methods for soil moisture monitoring include remote sensing, model simulation, and oven drying methods. With the features of a wide range and spatiotemporal continuity of satellite remote sensing monitoring, researchers carried out soil moisture retrievals at different scales using optical, infrared, and active and passive microwave sensors [14][15][16]. However, remote sensing monitoring for soil moisture has the disadvantage of short data time series, shallow observation depth, and coarse spatial resolution [17,18].…”