Wang et al. (2026) A wetland partitioning method based on the hydrological connectivity and the underlying causes of their occurrence

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-03-03
• Authors: Weize Wang, Peng Hu, Zefan Yang, Qin Yang, Jianhua Wang, Dandong Cheng, Jiwei Zhu
• DOI: 10.1016/j.jhydrol.2026.135239

Research Groups

• State Key Laboratory of Water Engineering Ecology and Environment in Arid Area, Xi’an University of Technology, Xi’an 710048, China
• State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
• Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China

Short Summary

This study developed a wetland partitioning method based on hydrological connectivity using hydrodynamic modeling and clustering, demonstrating its effectiveness in delineating subareas in the Zhalong Wetland and revealing how human activities and topography influence connectivity across different hydrological years.

Objective

• To develop a wetland partitioning method based on hydrological connectivity using hydrodynamic modelling, characteristic value extraction, and spatially constrained hierarchical clustering.
• To investigate the spatial variations in hydrologically connected subareas across different hydrological years and the impacts of hydraulic engineering and topography on hydrological connectivity in the Zhalong Wetland, China.

Study Configuration

• Spatial Scale: Zhalong Wetland, China (regional wetland scale).
• Temporal Scale: Comparative analysis across different hydrological conditions (wet, normal, and dry years).

Methodology and Data

• Models used: Hydrodynamic modelling, characteristic value extraction, spatially constrained hierarchical clustering.
• Data sources: Not explicitly detailed, but implied to include hydrological data (e.g., water levels, flows) and topographic data for hydrodynamic modelling. The method is noted for requiring substantially less data compared to field sampling and statistical clustering.

Main Results

• The developed method effectively delineates hydrologically connected subareas within wetlands.
• The number of hydrologically connected subareas varies significantly with hydrological conditions: 7 in a wet year, 11 in a normal year, and 12 in a dry year.
• The formation of these subareas is attributed to erosion from reservoir discharge, obstruction by roads and ditches, and natural topography.
• Surface water quality parameters differ among these subareas due to variations in flow patterns, source-sink dynamics, and aquatic vegetation distributions.
• The method requires substantially less data than traditional field sampling and statistical clustering, making it suitable for data-scarce regions.

Contributions

• Introduces a novel, data-efficient wetland partitioning method based on hydrological connectivity, integrating hydrodynamic modelling and spatially constrained clustering.
• Provides quantitative insights into how human hydraulic engineering and natural topography drive wetland fragmentation and reduce hydrological connectivity across varying hydrological regimes.
• Offers a practical tool for hydrological and ecological monitoring and targeted wetland management, particularly in data-limited environments.

Funding

• Not explicitly stated in the provided text.

Citation

@article{Wang2026wetland,
  author = {Wang, Weize and Hu, Peng and Yang, Zefan and Yang, Qin and Wang, Jianhua and Cheng, Dandong and Zhu, Jiwei},
  title = {A wetland partitioning method based on the hydrological connectivity and the underlying causes of their occurrence},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.135239},
  url = {https://doi.org/10.1016/j.jhydrol.2026.135239}
}