Hao et al. (2026) Partitioning precipitation moisture sources in a cold-temperate forest: Seasonal dominance of advection and transpiration in the Greater Khingan Range, China

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2026
• Date: 2026-03-11
• Authors: Yusheng Hao, Debin Jia, Shuai Hao, Shaofeng Guo, Mingyu Ji, Jiaze Li
• DOI: 10.1016/j.ejrh.2026.103328

Research Groups

• College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region 010018, China
• State Key Laboratory of Water Engineering Ecology and Environment in Arid Area, Inner Mongolia Agricultural University, China
• National Field Scientific Observation and Research Station of Greater Khingan Forest Ecosystem, Genhe, Inner Mongolia 022350, China
• College of Forestry, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region 010018, China

Short Summary

This study investigated seasonal precipitation moisture sources in the northern Greater Khingan Range using stable isotopes, backward trajectories, and moisture uptake diagnostics. It found that cold-season precipitation is dominated by long-range advection, while warm-season precipitation shows enhanced local recycling primarily driven by transpiration, though advection remains the largest single source.

Objective

• Document seasonal patterns in precipitation stable isotopes (δ¹⁸O, δ²H, D-excess), evaluate their meteorological controls, and establish the regional Local Meteoric Water Line (LMWL).
• Determine dominant moisture transport pathways and identify key moisture source regions in cold and warm seasons using Moisture Uptake diagnostics.
• Quantify seasonal contributions from advection, transpiration, and surface evaporation to precipitation, including uncertainty analysis.

Study Configuration

• Spatial Scale: Northern Greater Khingan Range, a cold-temperate forest region at the interface between high-latitude westerlies and the East Asian monsoon, spanning a permafrost transition zone. The specific sampling site is the National Observation and Research Station of Forest Ecosystems, Greater Khingan Range, Inner Mongolia (121°29′57″E, 50°54′21″N; 758.3 m above sea level).
• Temporal Scale: Event-based precipitation stable isotope data were collected from July 2022 to June 2025. Plant and surface water samples were collected monthly during the growing season (May–September) and monthly, respectively, over the study period.

Methodology and Data

• Models used:
  • Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model v5.4.0 (backward trajectory mode, 120-hour integration, launched at 1500 m above ground level, hierarchical clustering).
  • Lagrangian Moisture Uptake diagnostic (Sodemann et al., 2008) for identifying moisture uptake hotspots (specific humidity increase Δq ≥ 0.0002 kg kg⁻¹ over 6-hour intervals).
  • Isotope mixing models: Two-end-member (cold season: advective, evaporation) and three-end-member (warm season: advective, transpiration, evaporation).
  • Monte Carlo simulations (N = 5000) for uncertainty analysis of end-member fractions.
  • Local Evaporation Line (LEL) correction method (Gibson and Reid, 2014) for estimating precipitation-forming vapor isotopic composition (δpv).
  • Craig–Gordon model (Gat et al., 1994) for estimating evaporation-derived vapor end-member (δev).
• Data sources:
  • Event-based precipitation stable isotopes (δ¹⁸O, δ²H) collected at the National Observation and Research Station of Forest Ecosystems, Greater Khingan Range.
  • Plant xylem water stable isotopes (δ¹⁸O, δ²H) from Larix gmelinii, Betula platyphylla, Ledum palustre, and Pyrola incarnata.
  • Surface water stable isotopes (δ¹⁸O, δ²H) from the Genhe River.
  • Meteorological data (temperature, relative humidity, precipitation amount) from the National Observation and Research Station of Forest Ecosystems (https://dxf.cern.ac.cn/).
  • Elevation data (Digital Elevation Model - DEM) from ASTER GDEM at a 30 m spatial resolution via Geospatial Data Cloud (http://www.gscloud.cn).
  • Global Data Assimilation System (GDAS) reanalysis data (1° × 1°) for HYSPLIT forcing.
  • Precipitation isotope data from upwind Global Network of Isotopes in Precipitation (GNIP) stations (IRKUTSK, BAGDARIN, QIQIHAR) for advective vapor end-member inference.

Main Results

• Precipitation isotopes exhibited "summer enrichment–winter depletion" and strong positive correlation with temperature (δ¹⁸O: r = 0.77–0.93).
• The overall Local Meteoric Water Line (LMWL) for the Greater Khingan Range was δ²H = 7.80 δ¹⁸O + 1.05 (R² = 0.98), with a lower slope and intercept than the Global Meteoric Water Line (GMWL).
• Warm-season rainfall LMWL (δ²H = 6.98 δ¹⁸O − 6.87, R² = 0.90) showed a lower slope and negative intercept, indicating pronounced sub-cloud evaporation and kinetic fractionation.
• Cold-season snowfall LMWL (δ²H = 7.87 δ¹⁸O + 1.24, R² = 0.97) approached the GMWL slope, reflecting reduced evaporation.
• Moisture Uptake diagnostics revealed distinct seasonal shifts in transport pathways:
  • Cold season (October–April): Westerly-derived distant sources (Ural–Central Siberia, Northern Eurasia Rim) dominated moisture uptake (PMUr = 80.2%).
  • Warm season (May–September): Monsoon-related near-source regions (Mongolia–North China Corridor, Northwest Pacific Nearshore Belt, South China Belt) accounted for 85.9% of moisture uptake.
• Isotopic end-member partitioning consistently showed:
  • Cold season: Advective moisture dominance (fadv > 74%), with recycled moisture (fre) generally minor (< 26%), contributing 1.9%–7.6% during December–February.
  • Warm season: Enhanced local recycling (fre = 33.0–45.7%), driven mainly by transpiration (ftr peaking at 39.0% in July). Surface evaporation (fev) was comparatively modest (< 12% in June–August, elevated in May and September).
• Advective moisture remained the leading source year-round, contributing 54.3% even in July (the peak recycling month).
• Monte Carlo simulations confirmed the stability of seasonal end-member fractions, with ftr exhibiting wider confidence intervals in the warm season, indicating higher sensitivity to assumptions.

Contributions

• Provides the first integrated isotope-based investigation of precipitation moisture sources in a high-latitude cold-temperate forest–permafrost transition zone (northern Greater Khingan Range).
• Quantifies seasonal moisture-source dynamics (advection vs. local recycling, including transpiration and surface evaporation) using a robust framework combining precipitation isotopes, HYSPLIT trajectories, Lagrangian Moisture Uptake diagnostics, and end-member mixing with uncertainty analysis.
• Establishes a fundamental seasonal moisture-circulation regime for the region: advective control in the cold season and transpiration-driven recycling enhancement in the warm season.
• Offers quantitative constraints on moisture cycling and precipitation formation, providing benchmarks for ecohydrological model evaluation and assessing hydrological sensitivity to climate change in cold-temperate forests.
• Validates the consistency between different diagnostic tools (HYSPLIT, Moisture Uptake, isotope mixing models) for attributing moisture sources.

Funding

• Inner Mongolia Autonomous Region Postgraduate Scientific Research and Innovation Project (KC2025039B)
• National Natural Science Foundation of China (52169003)
• First-class Academic Subjects Special Research Project of the Education Department of Inner Mongolia Autonomous Region (No. YLXKZX-NND-010)
• Inner Mongolia Natural Science Foundation Joint Fund Project (2023LHMS05024)
• Science and Technology Plan of Inner Mongolia Autonomous Region (2025KYPT0178)

Citation

@article{Hao2026Partitioning,
  author = {Hao, Yusheng and Jia, Debin and Hao, Shuai and Guo, Shaofeng and Ji, Mingyu and Li, Jiaze},
  title = {Partitioning precipitation moisture sources in a cold-temperate forest: Seasonal dominance of advection and transpiration in the Greater Khingan Range, China},
  journal = {Journal of Hydrology Regional Studies},
  year = {2026},
  doi = {10.1016/j.ejrh.2026.103328},
  url = {https://doi.org/10.1016/j.ejrh.2026.103328}
}