Yuxiang Liu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Yuxiang Liu has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Dong Li
Middle Reach Hydrology and Water Resource Bureau of Yellow River Conservancy Commission, Jinzhong 030600, China
1 shared publication - Hong-Fei Zang
College of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
1 shared publication - Xuetong Zhao
School of Environment and Resources, Taiyuan University of Science and Technology, Taiyuan 030024, China
1 shared publication - Zhenxing Jia
School of Environment and Resources, Taiyuan University of Science and Technology, Taiyuan 030024, China
1 shared publication - Zhenxing Wang
State Environmental Protection Key Laboratory of Water Environmental Simulation and Pollution Control, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China
1 shared publication
Latest Publications
- Open Access
Evolution, Attribution, and Multi-Scale Lag Prediction of Liulin Spring Discharge
Karst springs are vital water sources in arid and semi-arid regions, with discharge governed by natural recharge conditions and increasingly influenced by human activities. This study investigates Liulin Spring on the eastern margin of the Ordos Basin using hydro-meteorological data (1956–2024), groundwater extraction records (1974–2024), and a restored discharge series that removes the direct effect of abstraction. Evolutionary patterns, drivers, and lagged responses were analysed using the trend-free pre-whitening Mann–Kendall test, Pettitt and moving t-tests, double-mass curve analysis, and detrended and prewhitened cross-correlation, and a parsimonious multiple linear regression (MLR) model with a persistence benchmark and independent temporal validation was constructed for prediction. The results reveal a significant seven-decade decline in four stages—stability, sharp decline, gradual attenuation, and rebound—with a historic minimum of 1.17 m3/s in 2021. Double-mass analysis showed the precipitation–response slope falling to 18.2% of the natural baseline (1956–1973), indicating that the precipitation–discharge relationship has been severely weakened under sustained anthropogenic disturbance; the contrast between the observed and restored double-mass curves identifies groundwater abstraction as the principal stressor, while the individual contributions of coal mine dewatering, land-use change, and other factors cannot be separated by this analysis alone. The restored discharge is strongly persistent (lag-1 ACF = 0.9392); after linear detrending and AR prewhitening, the robust lagged response to precipitation and river runoff concentrates at approximately 2 years, whereas the previously reported multi-decadal correlation peaks are artefacts of the common trend and autocorrelation. The MLR model (training R2 = 0.925) is outperformed by a persistence baseline for one-step-ahead prediction but provides skilful multi-step scenario forecasts; hindcast errors for 2023–2024 are below 0.24 m3/s. Scenario forecasts for 2025–2027 under dry, normal, and wet precipitation conditions (1.33–1.63 m3/s) suggest a stable-to-weak stage rather than a sustained recovery. This study provides a methodological reference for attribution and lag analysis of analogous karst springs, for which the model parameters require site-specific recalibration.
Open AccessEvolution, Attribution, and Multi-Scale Lag Prediction of Liulin Spring Discharge
Karst springs are vital water sources in arid and semi-arid regions, with discharge governed by natural recharge conditions and increasingly influenced by human activities. This study investigates Liulin Spring on the eastern margin of the Ordos Basin using hydro-meteorological data (1956–2024), groundwater extraction records (1974–2024), and a restored discharge series that removes the direct effect of abstraction. Evolutionary patterns, drivers, and lagged responses were analysed using the trend-free pre-whitening Mann–Kendall test, Pettitt and moving t-tests, double-mass curve analysis, and detrended and prewhitened cross-correlation, and a parsimonious multiple linear regression (MLR) model with a persistence benchmark and independent temporal validation was constructed for prediction. The results reveal a significant seven-decade decline in four stages—stability, sharp decline, gradual attenuation, and rebound—with a historic minimum of 1.17 m3/s in 2021. Double-mass analysis showed the precipitation–response slope falling to 18.2% of the natural baseline (1956–1973), indicating that the precipitation–discharge relationship has been severely weakened under sustained anthropogenic disturbance; the contrast between the observed and restored double-mass curves identifies groundwater abstraction as the principal stressor, while the individual contributions of coal mine dewatering, land-use change, and other factors cannot be separated by this analysis alone. The restored discharge is strongly persistent (lag-1 ACF = 0.9392); after linear detrending and AR prewhitening, the robust lagged response to precipitation and river runoff concentrates at approximately 2 years, whereas the previously reported multi-decadal correlation peaks are artefacts of the common trend and autocorrelation. The MLR model (training R2 = 0.925) is outperformed by a persistence baseline for one-step-ahead prediction but provides skilful multi-step scenario forecasts; hindcast errors for 2023–2024 are below 0.24 m3/s. Scenario forecasts for 2025–2027 under dry, normal, and wet precipitation conditions (1.33–1.63 m3/s) suggest a stable-to-weak stage rather than a sustained recovery. This study provides a methodological reference for attribution and lag analysis of analogous karst springs, for which the model parameters require site-specific recalibration.