Zhou et al. (2026) Integrating distributed hydrologic simulation with low-flow resilience: a spatiotemporal perspective

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-02-10
• Authors: Yan Zhou, Chi Zhang, Rui Hao, Yongxin Liao, Wei Yin, Dianchang Wang
• DOI: 10.1016/j.jhydrol.2026.135112

Research Groups

• National Engineering Research Center of Eco-Environment in the Yangtze River Economic Belt, Wuhan, Hubei, China
• China Three Gorges Corporation, Wuhan, Hubei, China

Short Summary

This study utilizes a fully distributed watershed hydrologic model to investigate low-flow resilience in a poorly gauged basin, revealing distinct spatiotemporal patterns where low flow emerges after approximately 120 days of minimal rainfall, and downstream reaches exhibit higher resilience compared to upstream areas.

Objective

• To conduct a detailed investigation of low-flow resilience and its spatiotemporal dynamics in a poorly gauged basin using a fully distributed watershed hydrologic model.
• To delineate and characterize low-flow recessions by their duration and magnitude from predicted spatiotemporal hydrographs.
• To compute area-normalized metrics for quantitative and comparable assessment of low-flow resilience across space and time.
• To thoroughly examine the temporal dynamics, spatial distribution, and progression patterns of low-flow resilience.

Study Configuration

• Spatial Scale: Watershed-wide, distributed analysis across all cross-sections, differentiating between upstream (hilly headwaters) and downstream (plains) reaches.
• Temporal Scale: Analysis of prolonged low-flow conditions, including emergence after approximately 120 days of minimal rainfall, recurring episodes, and identification of a 3-day critical rainfall deficit window.

Methodology and Data

• Models used: Fully distributed watershed hydrologic model.
• Data sources: Predicted spatiotemporal hydrographs generated by the distributed hydrological model; low-flow recessions delineated from these hydrographs; area-normalized resilience metrics computed from the delineated recessions.

Main Results

• Temporally, low flow initiated after approximately 120 days of minimal rainfall, followed by recurring episodes showing deteriorating resilience shortly after rainfall deficits, indicating prolonged depletion of subsurface storage.
• Spatially, downstream reaches demonstrated higher resilience, characterized by earlier entry into and recovery from low-flow conditions. In contrast, upstream reaches responded later but exhibited faster resilience deterioration, consistent with terrain-driven heterogeneity.
• Event-based analysis identified a 3-day rainfall deficit during low flow as a critical window for preemptive intervention.

Contributions

• Developed a framework that bridges physically interpretable resilience indicators with operational triggers and spatiotemporal management priorities.
• Provided a transferable basis for drought preparedness, ecological-flow safeguards, and coordinated management of surface water and groundwater, particularly in data-limited watersheds.
• Introduced area-normalized metrics for low-flow resilience, enabling quantitative comparison across both space and time.

Funding

• Not explicitly stated in the provided text.

Citation

@article{Zhou2026Integrating,
  author = {Zhou, Yan and Zhang, Chi and Hao, Rui and Liao, Yongxin and Yin, Wei and Wang, Dianchang},
  title = {Integrating distributed hydrologic simulation with low-flow resilience: a spatiotemporal perspective},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.135112},
  url = {https://doi.org/10.1016/j.jhydrol.2026.135112}
}