Yang et al. (2026) A Global Assessment of Climate Change and Anthropogenic Effects on Changes in Streamflow

Identification

• Journal: Water Resources Management
• Year: 2026
• Date: 2026-03-01
• Authors: Ruting Yang, Xiongpeng Tang, Silong Zhang, Chao Gao, Yanli Liu, Shuaifeng Lu, Fubo Zhao, Bikui Zhao
• DOI: 10.1007/s11269-025-04448-4

Research Groups

• College of Water Sciences, Beijing Normal University, Beijing, China
• Water Security Research Institute, Beijing Normal University, Zhuhai, China
• Guangdong-Hong Kong Joint Laboratory for Water Security, Beijing Normal University, Zhuhai, China
• State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, China
• Centre Testing International Group Co., Ltd, Shenzhen, China
• Department of Earth and Environmental Science, School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an, China
• Guangdong Research Institute of Water Resources and Hydropower, Guangzhou, China

Short Summary

This study globally assessed spatiotemporal streamflow changes in 2264 catchments from 1961–2014, quantifying the contributions of precipitation, potential evapotranspiration, and landscape characteristics using the Budyko hypothesis. It found that precipitation was the dominant factor for streamflow changes in most catchments, with significant regional variations in trends and sensitivities to climate and anthropogenic factors.

Objective

• To identify the spatiotemporal trends of observed streamflow during the period 1961–2014 in global 2264 catchments.
• To quantify the contributions of precipitation (P), potential evapotranspiration (Ep), and landscape parameter (n) to streamflow changes, classified by climate types, using the Choudhury-Yang equation based on the Budyko hypothesis.
• To evaluate the relationships between parameter n and multiple anthropogenic factors across the globe.

Study Configuration

• Spatial Scale: Global, covering 2264 catchments.
• Temporal Scale: 1961–2014 (54 years), divided into a baseline period (1961–1985) and two change periods (1986–2000 and 2001–2014).

Methodology and Data

• Models used:
  • Choudhury-Yang equation (based on Budyko hypothesis) for streamflow attribution.
  • Mann–Kendall (MK) test and Trend-Free Pre-Whitening (TFPW-MK) test for trend analysis.
  • Pettitt, Standard Normal Homogeneity Test (SNHT), and Buishand tests for abrupt change point detection.
  • Spearman correlations to evaluate relationships between parameter n and anthropogenic factors.
• Data sources:
  • Streamflow observations: Daily and monthly discharge from 2264 gauging stations (Global Streamflow Indices and Metadata Archive (GSIM), Australian Bureau of Meteorology (ABM), Chilean Center for Climate and Resilience Research, Yangtze River Conservancy Commission (YRCC)).
  • Meteorological data: Monthly precipitation (P) and potential evapotranspiration (Ep) from the TerraClimate dataset (spatial resolution: 1/24° × 1/24°).
  • Anthropogenic characteristic data:
    • Normalized Difference Vegetation Index (NDVI) from Global Inventory Modeling and Mapping Studies (GIMMS) (8 km spatial resolution, 1981–2014).
    • Forest cover loss from Hansen Global Forest Change dataset (version 1.9).
    • Cropland area from MODIS Land Cover Type (MCD12Q1) Version 6.1 (500 m spatial resolution, 2001–2014).
    • Impervious surface area from Global Artificial Impervious Area (GAIA) (30 m spatial resolution, 1985–2014).
    • Population data from WorldPop Global Project Population Data (100 m spatial resolution, 2000–2014).
    • Nighttime light index from Nighttime Lights Time Series Version 4 (1000 m spatial resolution, 1992–2013).
  • Climate classification: Köppen-Geiger climate classification version 1 (1 km spatial resolution, 1980–2016).

Main Results

• During 1961–2014, significant increasing trends (p < 0.05) in annual streamflow (16.65% of catchments) were observed in northeastern North America, northern Europe, and central-southern South America. Significant decreasing trends (12.01% of catchments) occurred in western North America, eastern South America, southern Australia, and southwestern China, largely consistent with precipitation trends.
• The mean elasticities of streamflow to changes in precipitation (εP), potential evapotranspiration (εEp), and landscape parameter (εn) were 2.19, -1.19, and -1.16, respectively, indicating that a 1% change in these factors results in a 2.19%, -1.19%, and -1.16% change in mean annual streamflow.
• Arid and semi-arid catchments (e.g., central-southwestern North America, eastern South America, southern Africa, Australia) exhibited greater streamflow elasticities (higher sensitivity) compared to humid catchments (e.g., eastern and northwestern North America, Europe, southeastern South America, parts of Asia).
• For the period 1986–2000, streamflow changes were dominated by P in 50.7% of catchments, Ep in 0.9%, and n in 48.4%. Climate change (P+Ep) dominated in 52.1% of catchments, and human activities (n) in 47.9%.
• For the period 2001–2014, the dominance shifted slightly: P in 53.1% of catchments, Ep in 2.4%, and n in 44.5%. Climate change dominated in 53.8% of catchments, and human activities in 46.2%. Overall, climate change was the dominant factor in most catchments during both periods.
• Globally, parameter n showed positive correlations with NDVI, forest loss, cropland area, and impervious surface in more catchments, suggesting these factors tend to increase n and reduce streamflow. Conversely, n showed negative correlations with population density and nightlight index in more catchments, implying these factors tend to decrease n and increase streamflow. These relationships exhibited high spatial heterogeneity.

Contributions

• Provided a comprehensive global assessment of climate change and human activities' impacts on streamflow changes across 2264 catchments over a 54-year period.
• Quantified the distinct contributions of precipitation, potential evapotranspiration, and landscape characteristics to streamflow changes, specifically categorized by Köppen-Geiger climate types, offering region-specific insights.
• Evaluated the relationships between the Budyko landscape parameter (n) and multiple anthropogenic factors (NDVI, forest loss, cropland area, impervious surface, population density, nightlight index) on a global scale, highlighting the spatial heterogeneity of these influences.
• Offered meaningful guidance for understanding complex streamflow dynamics and supporting effective water resource planning and management strategies globally under varying climatic conditions.

Funding

• National Natural Science Foundation of China (Grant Nos. 52325902, 52361145889, 52409004, and 52409006)
• National Key Research and Development Program of China (Grant No. 2022YFC3202301)
• Research Fund of Key Laboratory of Water Management and Water Security for Yellow River Basin, Ministry of Water Resources (under construction) (Grant No. 2023-SYSJJ-06)
• Guangdong-Hong Kong Joint Laboratory for Water Security (Grant No. 2020B1212030005)

Citation

@article{Yang2026Global,
  author = {Yang, Ruting and Tang, Xiongpeng and Zhang, Silong and Gao, Chao and Liu, Yanli and Lu, Shuaifeng and Zhao, Fubo and Zhao, Bikui},
  title = {A Global Assessment of Climate Change and Anthropogenic Effects on Changes in Streamflow},
  journal = {Water Resources Management},
  year = {2026},
  doi = {10.1007/s11269-025-04448-4},
  url = {https://doi.org/10.1007/s11269-025-04448-4}
}