Detection of the 2022 extreme drought over the Yangtze River basin using two satellite-gauge precipitation products
(2025) In Atmospheric Research 315.- Abstract
In 2022, the Yangtze River Basin in China experienced an unprecedented extreme drought, induced by high temperatures and precipitation deficits. Accurate monitoring of such extreme drought events is vitally significant for disaster mitigation under global warming. This study evaluated the effectiveness of two satellite-based precipitation products: the latest Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Final Run (IMERG-F) v07B and gauge-adjusted Global Satellite Mapping of Precipitation (GSMaP-G) v8, using the Standardized Precipitation Evapotranspiration Index (SPEI) to monitor the record-breaking drought. The evaluation was implemented based on the China Hydro-Meteorology precipitation (CHM_PRE) dataset... (More)
In 2022, the Yangtze River Basin in China experienced an unprecedented extreme drought, induced by high temperatures and precipitation deficits. Accurate monitoring of such extreme drought events is vitally significant for disaster mitigation under global warming. This study evaluated the effectiveness of two satellite-based precipitation products: the latest Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Final Run (IMERG-F) v07B and gauge-adjusted Global Satellite Mapping of Precipitation (GSMaP-G) v8, using the Standardized Precipitation Evapotranspiration Index (SPEI) to monitor the record-breaking drought. The evaluation was implemented based on the China Hydro-Meteorology precipitation (CHM_PRE) dataset with high-density stations. Results showed that the both satellite products presented satisfactory accuracy for the precipitation anomalies and monthly precipitation estimates. IMERG-F generally performed better than GSMaP-G, especially in the upstream region. Although the satellite-based SPEIs were constantly consistent with the CHM_PRE observations (correlation coefficient surpassing 0.9) in the midstream and downstream regions as the timescale increased, they exhibited greater spatial heterogeneity and temporal differentiation at longer timescales. IMERG-F demonstrated strong performance in detecting historical drought events, whereas it displayed worse reliability for the except 1-month drought estimates, as reflected by lower correlation and higher error metrics. During the 2022 extreme drought, IMERG-F-based SPEI had more reliable performance in identifying the stricken area and severity of meteorological drought. Conversely, GSMaP-G was more effective in characterizing the variability of summer agricultural drought and hydrological drought. These findings can provide valuable insights for the use of satellite remote sensing products in monitoring extreme drought events, offering potential to reduce drought risks and improve disaster management strategies.
(Less)
- author
- Wei, Linyong LU ; Jiang, Shanhu ; Ren, Liliang ; Hua, Zulin ; Zhang, Linqi and Duan, Zheng LU
- organization
- publishing date
- 2025-04
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Drought, GSMaP, IMERG, Satellite precipitation product, Yangtze River basin
- in
- Atmospheric Research
- volume
- 315
- article number
- 107929
- publisher
- Elsevier
- external identifiers
-
- scopus:85215240575
- ISSN
- 0169-8095
- DOI
- 10.1016/j.atmosres.2025.107929
- language
- English
- LU publication?
- yes
- id
- 9ba9d0ca-c6a7-4e3e-a455-f3af1cbe07b2
- date added to LUP
- 2025-03-21 08:46:34
- date last changed
- 2025-04-04 14:13:23
@article{9ba9d0ca-c6a7-4e3e-a455-f3af1cbe07b2,
abstract = {{<p>In 2022, the Yangtze River Basin in China experienced an unprecedented extreme drought, induced by high temperatures and precipitation deficits. Accurate monitoring of such extreme drought events is vitally significant for disaster mitigation under global warming. This study evaluated the effectiveness of two satellite-based precipitation products: the latest Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Final Run (IMERG-F) v07B and gauge-adjusted Global Satellite Mapping of Precipitation (GSMaP-G) v8, using the Standardized Precipitation Evapotranspiration Index (SPEI) to monitor the record-breaking drought. The evaluation was implemented based on the China Hydro-Meteorology precipitation (CHM_PRE) dataset with high-density stations. Results showed that the both satellite products presented satisfactory accuracy for the precipitation anomalies and monthly precipitation estimates. IMERG-F generally performed better than GSMaP-G, especially in the upstream region. Although the satellite-based SPEIs were constantly consistent with the CHM_PRE observations (correlation coefficient surpassing 0.9) in the midstream and downstream regions as the timescale increased, they exhibited greater spatial heterogeneity and temporal differentiation at longer timescales. IMERG-F demonstrated strong performance in detecting historical drought events, whereas it displayed worse reliability for the except 1-month drought estimates, as reflected by lower correlation and higher error metrics. During the 2022 extreme drought, IMERG-F-based SPEI had more reliable performance in identifying the stricken area and severity of meteorological drought. Conversely, GSMaP-G was more effective in characterizing the variability of summer agricultural drought and hydrological drought. These findings can provide valuable insights for the use of satellite remote sensing products in monitoring extreme drought events, offering potential to reduce drought risks and improve disaster management strategies.</p>}},
author = {{Wei, Linyong and Jiang, Shanhu and Ren, Liliang and Hua, Zulin and Zhang, Linqi and Duan, Zheng}},
issn = {{0169-8095}},
keywords = {{Drought; GSMaP; IMERG; Satellite precipitation product; Yangtze River basin}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{Atmospheric Research}},
title = {{Detection of the 2022 extreme drought over the Yangtze River basin using two satellite-gauge precipitation products}},
url = {{http://dx.doi.org/10.1016/j.atmosres.2025.107929}},
doi = {{10.1016/j.atmosres.2025.107929}},
volume = {{315}},
year = {{2025}},
}