Zhang et al. (2026) Runoff variation and attribution analysis in northern Chinese watersheds using an ABCD-snowmelt hydrological model

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2026
• Date: 2026-01-10
• Authors: Bo Zhang, Limin Duan, Yixuan Wang, Jin Sun, Shaojie Chu, Guixin Zhang, Javed Iqbal, Tingxi Liu
• DOI: 10.1016/j.ejrh.2026.103115

Research Groups

• State Key Laboratory of Water Engineering Ecology and Environment in Arid Area, Inner Mongolia Agricultural University, Hohhot, China
• Inner Mongolia Key Laboratory of Ecohydrology and High Efficient Utilization of Water Resources, Hohhot, China
• Inner Mongolia section of the Yellow River Basin Water Resources and Water Environment Comprehensive Management Autonomous Region Collaborative Innovation Center, Hohhot, China
• Environmental Research Institute, Shandong University, Qingdao, China

Short Summary

This study quantifies the impacts of climate change and human activities on runoff dynamics in nine northern Chinese watersheds using an ABCD-snowmelt hydrological model, revealing significant runoff declines and spatiotemporal heterogeneity in attribution across different watershed types.

Objective

• To systematically quantify the relative contributions of human activities and climate change to runoff in typical watersheds of northern China at monthly, seasonal, and annual scales.
• To reveal the spatial heterogeneity of runoff response mechanisms by comparing mountain forest, steppe, and sandy coarse sand watersheds.
• To precisely identify the critical role of snowmelt runoff during the spring flood season and elucidate the seasonal regimes of runoff evolution.

Study Configuration

• Spatial Scale: Nine representative watersheds across northern China, categorized into mountain forest (Miandu, Chaoer, Taoer), steppe (Balager, Xilin, Shandian), and sandy coarse sand (Huangfuchuan, Xiliugou, Maobula) watersheds.
• Temporal Scale: Monthly, seasonal (spring, summer, autumn, winter), and annual scales, spanning various periods between 1951 and 2020 (with specific hydrological years for each watershed, e.g., 1960–2020 for Miandu).

Methodology and Data

• Models used:
  • Mann–Kendall test and Pettitt test for trend and abrupt change point detection.
  • ABCD-snowmelt hydrological model (an enhanced version of the ABCD model integrating a snowmelt module).
• Data sources:
  • Observed monthly runoff records from outlet hydrological stations (1953–2020).
  • Meteorological data from National Surface Weather Station Daily Dataset (V3.0) by China Meteorological Administration (1951–2014).
  • 1-km monthly meteorological gridded dataset (2015–2020).
  • Potential evapotranspiration calculated using FAO-modified Penman–Monteith equation.
  • Land Use and Land Cover (LULC) dataset (annual, 30-meter resolution) for China (1985–2023).

Main Results

• Runoff Trends: With the exception of a transient increase in dry-season runoff in the Miandu watershed, all other watersheds exhibited significant declines in annual, wet-season, and dry-season runoff. The magnitude of annual decrease followed the order: sandy coarse sand > steppe > mountain forest watersheds.
• Monthly Scale Attribution: Runoff dynamics in March and April were strongly affected by spring snowmelt, with climate change emerging as the dominant driver in steppe and sandy coarse sand watersheds.
• Seasonal Scale Attribution:
  • Spring and summer runoff variations were largely controlled by climate change.
  • Winter runoff showed comparable contributions from climate change and human activities.
• Annual Scale Attribution:
  • Mountain Forest Watersheds: Runoff changes were primarily attributed to climate change (73–86 %).
  • Steppe Watersheds: Runoff changes were more strongly influenced by human activities (43–65 %).
  • Sandy Coarse Sand Watersheds: Runoff changes were predominantly influenced by human activities (62–80 %).
• Model Performance: The ABCD-snowmelt hydrological model performed well (NSE > 0.50), with higher applicability in mountain forest watersheds (mean NSE = 0.80) compared to steppe (mean NSE = 0.62) and sandy coarse sand watersheds (mean NSE = 0.57). The model reproduced low flows well (R² > 0.79) but underestimated peak flows (R² < 0.67).
• Human Activity Drivers: Land-use changes, including grassland degradation from overgrazing, agricultural and forestry expansion, increased irrigation, and extensive soil and water conservation measures (e.g., check dams, afforestation), were identified as key drivers of runoff reduction, particularly in steppe and sandy coarse sand watersheds.

Contributions

• This study provides a comprehensive, multi-temporal scale (monthly, seasonal, annual) quantification of climate change and human activity impacts on runoff in northern Chinese watersheds, addressing limitations of previous studies that focused on annual scales or single evaluation methods.
• It reveals the spatiotemporal heterogeneity of runoff responses across distinct watershed types (mountain forest, steppe, sandy coarse sand), offering a comparative analysis previously lacking.
• The research accurately identifies and elucidates the critical role of spring snowmelt in runoff generation, particularly in cold regions, and its attribution to climate change.
• The findings offer a clear scientific basis for developing targeted ecological restoration measures and sustainable water-resource management strategies in northern China.

Funding

• National Natural Science Foundation of China (U23A2001, 51939006, 52269005)
• Natural Science Foundation of Inner Mongolia Autonomous Region of China (2022MS05055, 2025YQ006)
• Inner Mongolia Agricultural University Basic Research Business Expenses Project (BR251018)
• First-class Academic Subjects Special Research Project of the Education Department of Inner Mongolia Autonomous Region (YLXKZX-NND-010)
• Inner Mongolia Autonomous Region Science and Technology Leading Talent Team (2022LJRC0007)
• Ministry of Education's Innovation Team Development Plan Project (IRT_17R60)
• Ministry of Science and Technology's Science and Technology Innovation Team Project in Key Areas (2015RA4013)

Citation

@article{Zhang2026Runoff,
  author = {Zhang, Bo and Duan, Limin and Wang, Yixuan and Sun, Jin and Chu, Shaojie and Zhang, Guixin and Iqbal, Javed and Liu, Tingxi},
  title = {Runoff variation and attribution analysis in northern Chinese watersheds using an ABCD-snowmelt hydrological model},
  journal = {Journal of Hydrology Regional Studies},
  year = {2026},
  doi = {10.1016/j.ejrh.2026.103115},
  url = {https://doi.org/10.1016/j.ejrh.2026.103115}
}