Yin et al. (2026) Future landscape pattern optimization based on runoff response across different temporal scales: A SWAT-PLUS coupled model simulation in the Three Gorges Reservoir Area

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2026
• Date: 2026-04-10
• Authors: Siwei Yin, Yuefeng Wang, Hanhan Wu, Chaogui Lei, Kebing Chen
• DOI: 10.1016/j.ejrh.2026.103426

Research Groups

• School of Geography and Tourism, Chongqing Normal University, Chongqing, China
• Hubei Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geosciences, Wuhan, China
• Chongqing Key Laboratory of Surface Process and Ecological Restoration in the Three Gorges Reservoir Area, Chongqing Normal University, Chongqing, China
• Bureau of Hydrology, Changjiang Water Resources Commission, Wuhan, China

Short Summary

This study coupled the PLUS and SWAT models to simulate future landscape patterns and evaluate their runoff responses under natural and slope-differentiated optimized development scenarios in the Dongli River Basin, Three Gorges Reservoir Area. The research found that optimized landscape patterns, particularly on moderate slopes, can significantly regulate runoff by maintaining specific forest and grassland proportions and improving landscape connectivity, providing quantitative thresholds for sustainable eco-hydrological management.

Objective

• To construct a scenario system based on slope-zoning optimization, designing targeted land use conversion scenarios that emphasize both landscape composition and configuration.
• To assess different temporal hydrological responses by introducing a multi-temporal runoff indicator system (annual runoff, flood runoff, non-flood runoff, maximum daily runoff, and minimum daily runoff) to systematically reveal the comprehensive impacts of landscape changes on flow regimes.
• To identify key thresholds for landscape optimization by quantitatively analyzing the relationships between landscape indices and hydrological metrics within different slope zones to formulate sustainable management strategies for the Three Gorges Reservoir Area.

Study Configuration

• Spatial Scale: Dongli River Basin (DRB), a representative basin within the Three Gorges Reservoir Area (TGRA), covering an area of 1512.88 square kilometers with an elevation range of 134 to 2533 meters. The basin was delineated into 25 sub-basins and further stratified into three slope classes: gentle (<15°), moderate (15°–25°), and steep (>25°).
• Temporal Scale:
  • Land use data: 2000, 2010, 2020 (historical), and 2030 (simulated future).
  • Meteorological and hydrological data: 2003–2020 (calibration: 2006–2010, validation: 2016–2020).
  • Runoff indices were calculated for annual, flood season (May-October), non-flood season (November-April), maximum daily, and minimum daily periods.

Methodology and Data

• Models used:
  • Patch-generating Land Use Simulation (PLUS) model: Used for simulating future landscape patterns under natural and optimized development scenarios.
  • Soil and Water Assessment Tool (SWAT): A physically based, semi-distributed hydrological model used to simulate daily runoff processes and assess hydrological responses.
  • SWAT-CUP (SUFI-2 algorithm): Employed for model parameter calibration and uncertainty analysis.
  • Fragstats 4.2: Used to calculate landscape pattern indices (e.g., Patch density (PD), Largest patch index (LPI), Landscape shape index (LSI), Contagion index (CONTAG), Aggregation index (AI), Shannon’s evenness index (SHEI)).
• Data sources:
  • Natural factors: 30-meter Digital Elevation Model (DEM) from https://www.gscloud.cn/, derived slope data, gridded meteorological data from https://www.resdc.cn/, station-based meteorological data (temperature, radiation, wind speed, relative humidity) from the National Meteorological Science Data Center (https://data.cma.cn/), hydrological data (runoff, precipitation) from the Annual Hydrological Report of the Yangtze River Basin, soil properties from the Harmonized World Soil Database (1:1,000,000), and 30-meter land use data from RESDC.
  • Distance factors: Accessibility metrics (adjacent to roads, water bodies) derived from OpenStreetMap.
  • Socio-economic data: Population and Gross Domestic Product (GDP) indicators from RESDC.

Main Results

• Under the natural development scenario for 2030, landscape pattern changes showed limited hydrological benefits, with a modest improvement in flood mitigation capacity compared to 2000 but minimal variation compared to 2020, and a persistent sharp decline in low-flow runoff.
• Runoff responses to optimized landscape patterns exhibited significant spatial heterogeneity and slope sensitivity. Moderate slopes were identified as core zones for hydrological regulation, showing the most substantial alterations in runoff (minimum daily runoff changes ranging from -51.85% to 224.72%).
• Converting cropland to forest or grassland in steep slope areas generally yielded beneficial hydrological effects, reducing flood runoff and increasing non-flood runoff. Gentle slopes showed the weakest runoff response to landscape pattern changes.
• Ecological thresholds for landscape optimization were identified:
  • Landscape Composition: For moderate slopes, maintaining forest proportions between 32.54% and 51.93% and grassland between 32.54% and 33.19% synergistically achieved flood peak reduction and baseflow augmentation. Cropland should be kept below 26.29%.
  • Landscape Configuration: For moderate slopes, reducing patch fragmentation (Patch density < 1.34) and increasing landscape connectivity (Contagion index > 63.86) effectively increased surface resistance and delayed hillslope runoff convergence.

Contributions

• Developed and implemented a novel landscape pattern optimization method that integrates the PLUS-SWAT model framework, specifically oriented towards slope differentiation and multi-objective hydrological regulation.
• Introduced a comprehensive multi-temporal runoff indicator system (AR, FR, NFR, Max1d, Min1d) to systematically assess the impacts of landscape changes, moving beyond the limitations of single annual runoff analysis.
• Quantitatively identified key ecological thresholds for landscape optimization, encompassing both compositional and configurational landscape indices, providing precise operational ranges for sustainable eco-hydrological management in different slope zones.
• Demonstrated the significant spatiotemporal heterogeneity and slope sensitivity of landscape pattern regulation on runoff, highlighting the critical role of moderate slopes as core zones for hydrological regulation.
• Provided scientific support for developing watershed-scale landscape optimization strategies in ecologically fragile basins like the Three Gorges Reservoir Area, by isolating the hydrological impacts of landscape change from climate change.

Funding

• National Natural Science Foundation of China (No. 42201045; No. U2340217)
• Natural Science Foundation of Chongqing, China (No. cstc2021jcyj-msxmX0692; CSTB2023NSCQ-MSX0632)
• Science and Technology Research Program of Chongqing Municipal Education Commission (No. KJZD-K202400501; KJZD-K202300507; KJQN202300551)
• Belt and Road Special Foundation of The National Key Laboratory of Water Disaster Prevention (Grant No. 2023490911)

Citation

@article{Yin2026Future,
  author = {Yin, Siwei and Wang, Yuefeng and Wu, Hanhan and Lei, Chaogui and Chen, Kebing},
  title = {Future landscape pattern optimization based on runoff response across different temporal scales: A SWAT-PLUS coupled model simulation in the Three Gorges Reservoir Area},
  journal = {Journal of Hydrology Regional Studies},
  year = {2026},
  doi = {10.1016/j.ejrh.2026.103426},
  url = {https://doi.org/10.1016/j.ejrh.2026.103426}
}