Integrated soil moisture fusion for enhanced agricultural drought monitoring in China

Aifeng Lv, Xianglei Yang, Wenxiang Zhang and Yan Han

Agricultural Water Management, 2025, vol. 311, issue C

Abstract: Frequent drought events have a profound impact on the natural environment and socio-economics. Therefore, accurate drought monitoring is essential to prevent and minimize drought losses. In this study, we developed an improved soil moisture dataset (Merged-SM) by using Triple Collocation (TC) and Linear Weight Fusion (LWF) methods to fuse soil moisture data from ERA5-Land, ESA CCI, and MERRA-2. The dataset was validated against in-situ data and applied to investigate the spatiotemporal dynamics of agricultural droughts across China. Results show that (1) Merged-SM exhibits superior accuracy and spatial coverage in comparison to individual datasets, achieving a higher correlation with in-situ data (R = 0.573) and a reduced unbiased root mean square error (ubRMSE = 0.027–0.047). (2) The Merged-SM accurately identified the onset, duration, and spatial extent of agricultural drought events, showing a significant negative correlation with agricultural disaster area (R = −0.418, P = 0.006). (3) Temporally, agricultural droughts across most regions of China displayed stable or alleviating trends, with particularly notable relief observed in Region VI. Spatially, 58.25 % of China's territory experienced a decrease in drought intensity, especially in the Qinghai-Tibetan Plateau, North China Plain, and southern regions, while certain areas in northern and southwestern China recorded an intensification of drought conditions. (4) The correlation between meteorological drought and agricultural drought was found to be stronger during the summer (R = 0.68) and autumn (R = 0.63) compared to winter and spring. The propagation time from meteorological drought to agricultural drought varied seasonally, being shortest in summer (2.54 months) and longest in winter (6.54 months). These findings highlight the potential of the Merged-SM dataset for improving agricultural drought monitoring and provide critical insights into the spatiotemporal dynamics and propagation mechanisms of droughts in China.

Keywords: Data fusion; Triple collocation; Soil moisture; Spatiotemporal analysis; Drought monitoring (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378377425001155
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:agiwat:v:311:y:2025:i:c:s0378377425001155

DOI: 10.1016/j.agwat.2025.109401

Access Statistics for this article

Agricultural Water Management is currently edited by B.E. Clothier, W. Dierickx, J. Oster and D. Wichelns

More articles in Agricultural Water Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().