Zheng et al. (2025) Groundwater Storage as a Key Driver of Subannual Streamflow Variability

Identification

• Journal: Hydrology and Water Resources
• Year: 2025
• Date: 2025-09-17
• Authors: Hongxing Zheng, Yongqiang Zhang, Changming Liu, L. Ruby Leung, Chunmiao Zheng, Dongdong Kong, Günter Blöschl
• DOI: 10.53941/hwr.2026.100002

Research Groups

• Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
• CSIRO Environment, Black Mountain, Canberra, ACT, Australia
• Pacific Northwest National Laboratory, Richland, WA, USA
• School of the Environment and Sustainable Engineering, Eastern Institute of Technology, Ningbo, China
• Department of Atmospheric Science, School of Environmental Studies, China University of Geosciences, Wuhan, China
• Institute of Hydraulic and Water Resources Engineering, Technische Universität Wien, Vienna, Austria

Short Summary

This study demonstrates that groundwater storage is a key driver of subannual streamflow variability, significantly buffering streamflow responses to precipitation changes at monthly and seasonal scales, particularly in water-limited regions. It highlights that traditional annual-scale streamflow elasticity overestimates the impact of precipitation on subannual streamflow, necessitating the inclusion of groundwater storage for a comprehensive understanding of hydrological responses to climate variability.

Objective

• To investigate the relative contributions of precipitation, potential evaporation, and groundwater storage to streamflow variability across monthly, seasonal, and annual timescales.
• To quantify streamflow elasticities to these three drivers and assess their temporal dependence using a global dataset of catchments.

Study Configuration

• Spatial Scale: 1628 unregulated small catchments distributed across the globe, each with an area less than 10,000 square kilometers.
• Temporal Scale: Daily observations spanning 1948 to 2015 (over 20 years per catchment), analyzed at monthly, seasonal (three-month aggregated), and annual scales.

Methodology and Data

• Models used:
  • Streamflow elasticity framework to attribute streamflow variability to precipitation, potential evaporation, and groundwater storage.
  • Three potential evaporation (PET) models: Priestley-Taylor, Penman, and Morton’s method for wet environment areal evaporation.
  • Groundwater storage estimation based on a linear reservoir model (Qb = αS) derived from baseflow separation.
  • Five baseflow separation approaches: four recursive digital filter approaches (Lyne and Hollick, Boughton, Chapman and Maxwell, Eckhardt) and one standard Institute of Hydrology algorithm.
  • Four global hydrological models (HBV-SIMREG, LISFLOOD, PCR-GLOBWB, SURFEX-trip) were used for comparison and evaluation of model performance.
• Data sources:
  • Meteorological and Albedo: Princeton Global Forcing (PGF) dataset (0.25-degree resolution, 1948-2015) for precipitation, air temperature, vapor pressure, shortwave/longwave downward radiation, and wind speed. MODIS MOD43C1 product (500 m resolution, resampled to 0.25-degree) for monthly mean albedo (2000-2006).
  • Streamflow: Global Runoff Data Centre (GRDC), Geospatial Attributes of Gages for Evaluating Streamflow (GAGES)-II database, Australian Bureau of Meteorology, and Chinese Academy of Sciences.
  • Dam locations for catchment selection: Global Reservoir and Dam (GRanD) database (v1.1), International Commission of Large Dams, Meridian World Data, and National Land and Water Resources Audit of Australia.

Main Results

• Streamflow elasticity to precipitation (εP) increases from monthly to annual scales, while groundwater storage elasticity (εS) decreases from monthly to annual scales, indicating a stronger buffering effect of groundwater at shorter timescales.
• At monthly and seasonal scales, groundwater storage significantly buffers streamflow variability, making streamflow more resilient to precipitation changes than at the annual scale.
• At the annual scale, precipitation is the dominant contributor to streamflow variability (relative contribution > 50% for 77.2% of catchments).
• At the monthly scale, groundwater storage is a prominent contributor (relative contribution > 50% for 30.9% of catchments), with precipitation's contribution being comparatively smaller (relative contribution > 50% for 47.6% of catchments).
• The contribution of groundwater storage to streamflow variability is more pronounced in water-limited (dry) regions (aridity index > 1.35) compared to energy-limited (wet/cold) regions (aridity index < 0.76).
• Current global hydrological models fail to accurately capture the scale-dependent elasticities of streamflow to precipitation and groundwater storage, particularly at subannual scales, highlighting their limitations in simulating monthly streamflow variability.

Contributions

• Provides a novel, data-driven framework to quantify the scale-dependent contributions of precipitation, potential evaporation, and groundwater storage to streamflow variability across monthly, seasonal, and annual timescales using a large global catchment dataset.
• Establishes groundwater storage as a critical, often overlooked, driver of subannual streamflow variability, demonstrating its significant buffering capacity against precipitation changes, especially in water-limited environments.
• Reveals that using annual streamflow elasticity can lead to substantial overestimation of streamflow changes at monthly and seasonal scales, emphasizing the need for a multi-temporal perspective in hydrological assessments.
• Identifies a critical gap in current global hydrological models, urging for improved representation of monthly groundwater recharge to enhance the reliability of hydrological impact projections under climate variability.

Funding

• "Quantifying Groundwater Changes and Development of Better Agricultural Water Saving Techniques in the Western Ordos" Program funded by the Bureau of Science and Technology of the Erdos (Grant No. ZD20232302).
• Talent Program of the Ministry of Science and Technology of China.
• Office of Science, U.S. Department of Energy, Biological and Environmental Research as part of the Regional and Global Model Analysis program area (PNNL operated by Battelle Memorial Institute under contract DE-AC05-76RL01830).
• Funding agencies of Zhejiang Province and Ningbo Municipality through the program "Novel technologies for joint pollution reduction and carbon sequestration."

Citation

@article{Zheng2025Groundwater,
  author = {Zheng, Hongxing and Zhang, Yongqiang and Liu, Changming and Leung, L. Ruby and Zheng, Chunmiao and Kong, Dongdong and Blöschl, Günter},
  title = {Groundwater Storage as a Key Driver of Subannual Streamflow Variability},
  journal = {Hydrology and Water Resources},
  year = {2025},
  doi = {10.53941/hwr.2026.100002},
  url = {https://doi.org/10.53941/hwr.2026.100002}
}