He et al. (2025) Hydrological response to land use change under low carbon-optimal economic scenario

Identification

• Journal: Journal of Hydrology
• Year: 2025
• Date: 2025-10-31
• Authors: Yanhu He, Yuyin Yang, Zhenxing Zhang, Luyan Wu, Qian Tan, Zirui Wang, Yang Pan
• DOI: 10.1016/j.jhydrol.2025.134501

Research Groups

• Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou 510006, China
• Illinois State Water Survey, Prairie Research Institute, University of Illinois Urbana-Champaign, 2204 Griffith Drive, Champaign, IL 61820, USA

Short Summary

This study developed a framework integrating land-use simulation (CA Markov) and hydrological modeling (SWAT) with spatiotemporal regression (GTWR) to assess hydrological responses to land-use change under a low-carbon, economic-optimal scenario in the Dongjiang River Basin. It found that by 2035, land-use changes, primarily farmland conversion to forest, grassland, and construction, lead to increased surface runoff and evapotranspiration, decreased soil percolation and groundwater recharge, with significant spatiotemporal heterogeneity and implications for drought and flooding risks.

Objective

• To clarify the hydrological response to land use change under a low-carbon and economic-optimal scenario, considering local spatial heterogeneity, and to provide a scientific basis for regional water resource management and ecological protection policies.

Study Configuration

• Spatial Scale: Dongjiang River Basin (DRB), China, a key water source for the Guangdong-Hong Kong-Macao Greater Bay Area.
• Temporal Scale: Scenarios for 2020 (baseline) and 2035 (low carbon-optimal economic scenario). Analysis conducted at annual, monthly, and daily scales, distinguishing between non-flood (October-March) and flood (April-September) seasons.

Methodology and Data

• Models used: Cellular Automata (CA) Markov model for land-use spatial pattern simulation, Soil and Water Assessment Tool (SWAT) for hydrological simulation, and Geographically and Temporally Weighted Regression (GTWR) model for quantifying local effects of land-use change on hydrological response.
• Data sources: Land-use data (for CA Markov model), hydrological data (for SWAT model calibration and simulation), economic data (for optimal economic scenario development), and carbon sequestration data.

Main Results

• Under the 2035 low-carbon-optimal economic scenario, land-use change is characterized by the expansion of forest, grassland, and construction land, primarily at the expense of farmland.
• This land-use change yields annual economic benefits of 2.4 × 10^7 US dollars but decreases carbon sequestration by 3.03 × 10^6 tonnes per year.
• Compared to the 2020 baseline, the 2035 scenario shows an increase in surface runoff (SURQ) and evapotranspiration (ET), alongside a decrease in soil percolation (PERC) and groundwater recharge (GWQ).
• Annual SURQ increases by 2.94 %, and monthly SURQ increases by 5.38 %. Annual GWQ and PERC reduce by 0.35 % and 0.34 %, respectively.
• Land-use change has minimal impact on the changing trends of hydrological parameters at the daily scale.
• Seasonally, SURQ decreases significantly in the non-flood season (October-March), while SURQ, ET, and GWQ all increase significantly in the flood season (April-September), indicating potential risks of drought and flooding.
• Hydrological responses exhibit significant spatial heterogeneity: SURQ notably decreases in the southwestern lower reaches, while PERC and GWQ notably increase there. ET shows an increasing trend across most of the basin.
• The northeastern region of the DRB shows higher sensitivity of SURQ to land-use change, and the effects of land-use change on GWQ generally increase from south to north within the basin.

Contributions

• Developed a comprehensive and integrated modeling framework (CA Markov, SWAT, GTWR) to simulate future land-use change under low-carbon and economic-optimal scenarios and quantify its spatiotemporal hydrological impacts.
• Provided novel insights into the complex and heterogeneous hydrological responses to land-use change driven by "dual carbon" goals and economic development.
• Offered a scientific basis for formulating targeted regional water resources regulation and ecological protection policies, advancing informed decision-making for water security in rapidly developing basins.

Funding

Not specified in the provided text.

Citation

@article{He2025Hydrological,
  author = {He, Yanhu and Yang, Yuyin and Zhang, Zhenxing and Wu, Luyan and Tan, Qian and Wang, Zirui and Pan, Yang},
  title = {Hydrological response to land use change under low carbon-optimal economic scenario},
  journal = {Journal of Hydrology},
  year = {2025},
  doi = {10.1016/j.jhydrol.2025.134501},
  url = {https://doi.org/10.1016/j.jhydrol.2025.134501}
}

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