Huang et al. (2026) Hydrological drought characteristics and its propagation from meteorological drought in the Jing river basin under environmental change

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2026
• Date: 2026-01-06
• Authors: Tingting Huang, Yu Liu, Zhifeng Jia, Jiaru Shi, Yulin Wei, Pengcheng Sun
• DOI: 10.1016/j.ejrh.2025.103084

Research Groups

• School of Water and Environment, Chang’an University, Xi’an 710054, China
• Key Laboratory of Subsurface Hydrology and Ecological Effects in Arid Region, Ministry of Education, Chang’an University, Xi’an 710054, China
• Department of Biological & Ecological Engineering, Oregon State University, Corvallis, OR, USA
• College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China
• Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, College of Life Sciences, Northwest University, Xi’an, Shaanxi 710069, China
• Key Laboratory of Soil and Water Conservation on the Loess Plateau of Ministry of Water Resources, Yellow River Institute of Hydraulic Research, Zhengzhou 450003, China

Short Summary

This study investigates how human activities alter hydrological drought characteristics and its propagation from meteorological drought in the Jing River basin, China, by isolating anthropogenic influences using the SWAT model. It reveals that human activities intensify short-term hydrological droughts, accelerate their development, and weaken the meteorological-hydrological drought linkage, with precipitation and vegetation cover being key controls.

Objective

• Apply the Soil and Water Assessment Tool (SWAT) model to simulate natural runoff conditions in the Jing River basin (JRB).
• Examine hydrological drought formation and recovery under natural versus human-impacted conditions, quantifying anthropogenic contributions to hydrological drought variability.
• Evaluate the influence of human activities on meteorological to hydrological drought propagation.

Study Configuration

• Spatial Scale: The Jing River basin (JRB), a major tributary of the Wei River on China’s Loess Plateau, encompassing approximately 45,412 square kilometers.
• Temporal Scale: Daily meteorological records from 1981 to 2018; monthly discharge records from 1981 to 2017. The environmental change period was identified from 1998 to 2018, following a detected hydrological change-point in 1997.

Methodology and Data

• Models used:
  • Soil and Water Assessment Tool (SWAT) model: A semi-distributed, physically based hydrological model used to reconstruct natural runoff.
  • Pettitt mutation test: A non-parametric method to identify abrupt change points in precipitation and runoff time series.
  • Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI): Used to assess meteorological and hydrological drought conditions, respectively, calculated by fitting gamma distributions.
  • Run theory: Employed to identify and characterize drought events, including duration, severity, peak intensity, and development/recovery phases.
  • Human Activity Impact Index (HADI): Quantified the proportional influence of human activities on various drought characteristics.
  • Pearson correlation coefficient: Used to evaluate the relationship between SPI and SRI across multiple timescales and estimate drought propagation delay.
  • Linear models: Applied to describe the propagation patterns of different drought characteristics.
• Data sources:
  • Daily meteorological records (1981–2018) from the China Meteorological Data Network, including precipitation, maximum/minimum temperatures, average wind speed, and sunshine duration. Potential evapotranspiration (PET) was derived using the FAO Penman-Monteith method.
  • Digital Elevation Model (DEM) data (1 km spatial resolution) from https://www.gscloud.cn/.
  • Land use data (1 km resolution) from the University of Maryland’s Global Land Cover Production.
  • Soil type data (1 km resolution) from the World Soil Database.
  • Normalized Difference Vegetation Index (NDVI) data from the Global Inventory Modeling and Mapping Studies (GIMMS) dataset.
  • Monthly discharge records (1981–2017) from the Zhangjiashan Hydrological Station, obtained from the National Earth System Science Data Center.

Main Results

• A significant hydrological change-point was identified in 1997, marking the onset of an environmental change period (1998–2018) in the Jing River basin.
• Human activities had a more pronounced influence on short-term (monthly and seasonal) hydrological droughts compared to long-term ones, with a mean Human Activity Impact Index (HADI) of 16.28 %.
• Anthropogenic interventions generally aggravated hydrological droughts by intensifying and accelerating their development phase, leading to increased drought severity and development speed.
• While human activities slightly reduced drought recovery duration and increased recovery speed, these modest mitigating effects were insufficient to offset the stronger aggravating impacts during drought development.
• The number of hydrological drought events increased from 12 under natural conditions to 21 under human activity conditions after 2000, characterized by shorter durations but higher intensity and more rapid development.
• Human activities weakened the linkage between meteorological and hydrological droughts, reducing the maximum Pearson correlation coefficient from 0.532 to 0.417.
• The mean meteorological-hydrological drought propagation time was shortened from 1.1056 months to 0.6324 months due to human activities.
• Under consistent meteorological drought conditions, human activities led to shorter hydrological drought durations but increased their severity and peak intensity, resulting in more abrupt and concentrated impacts.
• Precipitation and vegetation cover (NDVI) were identified as key controls on drought propagation time. Under natural conditions, precipitation and average temperature showed significant negative correlations with propagation time. Under human activity conditions, NDVI exhibited a highly significant negative relationship, indicating its dominant role.
• For specific drought events, human activities caused substantial runoff reductions (e.g., 38.98 % and 34.81 % for events 4 and 9, respectively) and significantly increased drought severity (3.17 and 1.10 times that of natural conditions).

Contributions

• Developed and applied an integrated framework combining the SWAT model, run theory, and the Human Activity Impact Index (HADI) to quantitatively assess anthropogenic influences on hydrological drought characteristics and propagation.
• Provided novel insights into the scale-dependent impacts of human activities on hydrological droughts, distinguishing between short-term and long-term effects.
• Quantified the specific roles of human activities in modifying drought development and recovery phases, highlighting their aggravating effects during development outweighing modest mitigation during recovery.
• Demonstrated how human activities weaken the meteorological-hydrological drought linkage and shorten drought propagation time, leading to more abrupt and intense hydrological drought impacts.
• Identified the shifting dominant controls on drought propagation time from natural factors (precipitation, temperature) to anthropogenic factors (vegetation cover/NDVI) under environmental change.
• Offered a transferable research framework and practical support for designing adaptive drought-risk management and water-resource regulation strategies in arid and semi-arid basins.

Funding

• Fundamental Research Funds for the Central Universities, CHD (300102293209).

Citation

@article{Huang2026Hydrological,
  author = {Huang, Tingting and Liu, Yu and Jia, Zhifeng and Shi, Jiaru and Wei, Yulin and Sun, Pengcheng},
  title = {Hydrological drought characteristics and its propagation from meteorological drought in the Jing river basin under environmental change},
  journal = {Journal of Hydrology Regional Studies},
  year = {2026},
  doi = {10.1016/j.ejrh.2025.103084},
  url = {https://doi.org/10.1016/j.ejrh.2025.103084}
}