Seasonal Precipitation Provides Modest Incremental Information for Retrospective Estimation of Active-Layer Thickness at Monitored Sites Along the Qinghai–Tibet Engineering Corridor, China

Active-layer thickness (ALT) integrates atmospheric forcing with local surface and subsurface hydrothermal conditions, but the incremental predictive value of precipitation after temperature and site memory have been considered to remain uncertain. We combined annual ALT observations from 54 boreholes along the Xidatan–Anduo section of the Qinghai–Tibet Engineering Corridor (2001–2020) with monthly Third Pole Meteorological Forcing Dataset data (1986–2020). A rolling-origin design evaluated nine held-out years (2012–2020) after accounting for site fixed effects, a quadratic temporal trend, previous-year ALT, and an air-temperature lag selected from each training set. Because the principal predictors include target-year precipitation, the analysis represents retrospective or end-of-season annual estimation rather than a lead-time forecast. Among 16 seasonal–lag candidates, the post-screening best fixed model used June–August precipitation averaged over the target year and the three preceding years; it reduced RMSE from 0.203491 to 0.199312 m (ΔRMSE = 0.004179 m; 2.05%). A selection-aware maximum statistic remained supported under site-specific circular shifts (p = 0.001), whereas a common-shift sensitivity that preserved synchronous cross-site climate structure was inconclusive. A pipeline that repeated precipitation-window selection using training data only produced a smaller gain (ΔRMSE = 0.001645 m; 0.81%; p = 0.004). Ridge regression and random forest showed similarly small paired gains, but histogram gradient boosting did not. A continuous mean annual ground temperature (MAGT) interaction did not improve external performance, strict spatial-block × time holdout showed no transferable precipitation gain, and a predictor restricted to precipitation from years t − 1 to t − 4 did not improve RMSE. The fixed-window gain was substantially smaller than the source-reported ±0.05 m uncertainty of an individual ALT estimate. Seasonal precipitation should therefore be treated as an auxiliary covariate for retrospective assessment at monitored sites, not as a stand-alone forecast, an ungauged-site hazard model, or evidence of maintenance-cost savings.

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Journal
Buildings
Published
2026-07-30
DOI
https://doi.org/10.3390/buildings16153023
Primary Topic
Climate change and permafrost
Type
article
Field-Weighted Citation Impact
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article

Seasonal Precipitation Provides Modest Incremental Information for Retrospective Estimation of Active-Layer Thickness at Monitored Sites Along the Qinghai–Tibet Engineering Corridor, China

Qingsong Du, Fei Wang, Guoyu Li, Dun Chen et al.
Buildings
Climate change and permafrost
article

Seasonal Precipitation Provides Modest Incremental Information for Retrospective Estimation of Active-Layer Thickness at Monitored Sites Along the Qinghai–Tibet Engineering Corridor, China

Qingsong Du, Fei Wang, Guoyu Li, Dun Chen, Shunshun Qi
article en

Abstract

Active-layer thickness (ALT) integrates atmospheric forcing with local surface and subsurface hydrothermal conditions, but the incremental predictive value of precipitation after temperature and site memory have been considered to remain uncertain. We combined annual ALT observations from 54 boreholes along the Xidatan–Anduo section of the Qinghai–Tibet Engineering Corridor (2001–2020) with monthly Third Pole Meteorological Forcing Dataset data (1986–2020). A rolling-origin design evaluated nine held-out years (2012–2020) after accounting for site fixed effects, a quadratic temporal trend, previous-year ALT, and an air-temperature lag selected from each training set. Because the principal predictors include target-year precipitation, the analysis represents retrospective or end-of-season annual estimation rather than a lead-time forecast. Among 16 seasonal–lag candidates, the post-screening best fixed model used June–August precipitation averaged over the target year and the three preceding years; it reduced RMSE from 0.203491 to 0.199312 m (ΔRMSE = 0.004179 m; 2.05%). A selection-aware maximum statistic remained supported under site-specific circular shifts (p = 0.001), whereas a common-shift sensitivity that preserved synchronous cross-site climate structure was inconclusive. A pipeline that repeated precipitation-window selection using training data only produced a smaller gain (ΔRMSE = 0.001645 m; 0.81%; p = 0.004). Ridge regression and random forest showed similarly small paired gains, but histogram gradient boosting did not. A continuous mean annual ground temperature (MAGT) interaction did not improve external performance, strict spatial-block × time holdout showed no transferable precipitation gain, and a predictor restricted to precipitation from years t − 1 to t − 4 did not improve RMSE. The fixed-window gain was substantially smaller than the source-reported ±0.05 m uncertainty of an individual ALT estimate. Seasonal precipitation should therefore be treated as an auxiliary covariate for retrospective assessment at monitored sites, not as a stand-alone forecast, an ungauged-site hazard model, or evidence of maintenance-cost savings.

BuildingsVol. 16(15)
University of Alberta (CA), Chinese Academy of Sciences (CN), Northwest Institute of Eco-Environment and Resources (CN), University of Chinese Academy of Sciences (CN)
Science and Technology Department of Gansu Province
Climate action
Openalex Percentile: Top 13%
Climate change and permafrost
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