Analysis of hydrological drought and TWS-related drivers in Yunnan Province Using GNSS-derived TWS, multi-source hydrological data and the XGBoost model

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Authors: Yong Su, Zhanjie Qu, Yakun Pu, Qiong Li, Xi Zhang, Ji Feng
Cited by: 1
References: 68

Abstract

Yunnan Province. Using vertical displacement data from 43 GNSS stations across Yunnan Province, this study first inverted terrestrial water storage anomalies (TWSA) for 2011–2019, then developed the novel GNSS Combined Climatologic Deviation Index (GNSS-CCDI) through integration with precipitation observations, ultimately employing XGBoost modeling to quantify key driving factors. The retrieved TWSA agrees well with GRACE and GLDAS data, yet the latter two underestimate TWSA changes. The GNSS-CCDI is consistent with other drought indices. Five drought events occurred from 2011 to 2019, with the severest starting in July 2011 for 9 months. Main factors influencing TWSA vary across regions, with soil moisture, lake, and snow having the greatest impact in Yunnan. • First application of GNSS-CCDI for Yunnan droughts (2011–2019). • XGBoost reveals key drivers of hydrological drought. • GNSS-CCDI outperforms GNSS-DSI in correlating with traditional indices. • Findings enhance drought monitoring and mechanistic analysis in Yunnan.

Fields of Study & Subjects

Soil Moisture and Remote Sensing GNSS positioning and interference Geophysics and Gravity Measurements

Publication details

Journal / source
Journal of Hydrology Regional Studies
Publisher
Elsevier BV
Volume
64
Pages
103120–103120
Publication date
12 January 2026
Language
EN