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Volume 17
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10.3390/f17060673
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Multi-Hydrological Factor-Driven Attribution and Future Prediction of Vegetation Dynamics on the Qinghai-Tibetan Plateau

by
Qiang Meng
1,2,
Qiang He
1,2,*,
Wenxin Yang
3,
Peng Chen
4,*,
Jingxia Liu
1,2,
Zhaoqiang Zhou
4 and
Xiaowen Wang
5,6
1
College of Water Conservancy and Civil Engineering, Xizang Agricultural and Animal Husbandry University, Linzhi 860000, China
2
Plateau Water Environment and Water Ecology Laboratory, Xizang Agriculture and Animal Husbandry University, Linzhi 860000, China
3
College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China
4
College of Hydraulic Science and Engineering, Northeast Agricultural University, Harbin 150030, China
5
High-Tech Key Laboratory of Agricultural Equipment and Intelligence of Jiangsu Province, Jiangsu University, Zhenjiang 212013, China
6
School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
*
Authors to whom correspondence should be addressed.
Forests 2026, 17(6), 673; https://doi.org/10.3390/f17060673
Submission received: 1 April 2026 / Revised: 13 May 2026 / Accepted: 28 May 2026 / Published: 31 May 2026
(This article belongs to the Section Forest Hydrology)
Versions Notes

Abstract

Accurately assessing and predicting vegetation dynamics is of great significance for evaluating regional hydrological and ecological environments. This study focuses on the climate-sensitive Qinghai-Tibetan Plateau (QTP), aiming to reveal the spatiotemporal patterns, underlying driving mechanisms, and future trends of vegetation dynamics. The historical turning points of greening trends were identified using the running slope difference method, and the SHapley Additive exPlanations (SHAP) method was employed to analyze the key driving factors. An Xtreme Gradient Boosting (XGBoost) prediction model was constructed and validated, and then coupled with Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model ensemble data to project seasonal vegetation changes under different Shared Socioeconomic Pathways (SSP). The main conclusions are as follows: (1) Vegetation on the QTP showed an overall greening trend with significant spatial heterogeneity. Approximately 47.25% of the area exhibited no trend shift (NS), while 29.42% experienced a shift from greening to browning (GB), with most shifts occurring between 1990 and 2010. (2) Soil moisture and precipitation were the dominant driving factors, with contributions significantly higher than those of temperature, wind speed, and other variables, and they exhibited nonlinear interactive effects with the Normalized Difference Vegetation Index (NDVI). (3) In the future, vegetation is projected to show an overall increasing trend, with stronger responses in spring and autumn. The regional average rate of change is highest in spring, especially under the SSP5-8.5 scenario (17.8% for 2030–2060 and 26.4% for 2061–2100); in autumn, although the regional average rate of change is small, the internal spatial variability is significant. The humid regions in the eastern and southeastern parts of the QTP demonstrated more active greening across all seasons except winter, and high-emission scenarios are expected to exacerbate regional and seasonal differences. This study systematically reveals the adaptive dynamics and future scenarios of vegetation dynamics on the QTP, providing scientific support for the adaptation of alpine ecosystems to global change and the management of regional ecological security barriers.
Keywords: NDVI; CMIP6; Tibetan Plateau; SHAP; XGBoost NDVI; CMIP6; Tibetan Plateau; SHAP; XGBoost

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MDPI and ACS Style

Meng, Q.; He, Q.; Yang, W.; Chen, P.; Liu, J.; Zhou, Z.; Wang, X. Multi-Hydrological Factor-Driven Attribution and Future Prediction of Vegetation Dynamics on the Qinghai-Tibetan Plateau. Forests 2026, 17, 673. https://doi.org/10.3390/f17060673

AMA Style

Meng Q, He Q, Yang W, Chen P, Liu J, Zhou Z, Wang X. Multi-Hydrological Factor-Driven Attribution and Future Prediction of Vegetation Dynamics on the Qinghai-Tibetan Plateau. Forests. 2026; 17(6):673. https://doi.org/10.3390/f17060673

Chicago/Turabian Style

Meng, Qiang, Qiang He, Wenxin Yang, Peng Chen, Jingxia Liu, Zhaoqiang Zhou, and Xiaowen Wang. 2026. "Multi-Hydrological Factor-Driven Attribution and Future Prediction of Vegetation Dynamics on the Qinghai-Tibetan Plateau" Forests 17, no. 6: 673. https://doi.org/10.3390/f17060673

APA Style

Meng, Q., He, Q., Yang, W., Chen, P., Liu, J., Zhou, Z., & Wang, X. (2026). Multi-Hydrological Factor-Driven Attribution and Future Prediction of Vegetation Dynamics on the Qinghai-Tibetan Plateau. Forests, 17(6), 673. https://doi.org/10.3390/f17060673

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