@article{Hu2025, 
author = {Su-duan Hu and Wen-da Liu and Jun-jian Liu and Jiang-Yulong Wang and Jun-jie Yang and Zhao-yi Li and Zhi-yang Tang and Guo-qiang Wang and Tian-cun Yu},
title = {Evaluation of water quality and water resources carrying capacity using a varying fuzzy pattern recognition model: A case study of small watersheds in Hilly Region},
year = {2025},
journal = {Journal of Groundwater Science and Engineering},
volume = {13},
number = {4},
pages = {386-405},
keywords = {Varying fuzzy pattern recognition model, Dynamic assessment, Small watershed, Water quality evaluation, Water resources carrying capacity},
url = {https://www.sciopen.com/article/10.26599/JGSE.2025.9280061},
doi = {10.26599/JGSE.2025.9280061},
abstract = {Water scarcity and environment deterioration have become main constraints to sustainable economic and social development. Scientifically assessing Water Resources Carrying Capacity (WRCC) is essential for the optimal allocation of regional water resources. The hilly area at the northern foot of Yanshan Mountains is a key water conservation zone and an important water source for Beijing, Tianjin and Hebei. Grasping the current status and temporal trends of water quality and WRCC in representative small watersheds within this region is crucial for supporting rational water resources allocation and environment protection efforts. This study focuses on Pingquan City, a typical watershed in northern Hebei Province. Firstly, evaluation index systems for surface water quality, groundwater quality and WRCC were established based on the Pressure-State-Response (PSR) framework. Then, comprehensive evaluations of water quality and WRCC at the sub-watershed scale were conducted using the Varying Fuzzy Pattern Recognition (VFPR) model. Finally, the rationality of the evaluation results was verified, and future scenarios were projected. Results showed that: (1) The average comprehensive evaluation scores for surface water and groundwater quality in the sub-watersheds were 1.44 and 1.46, respectively, indicating that both met the national Class II water quality standard and reflected a high-quality water environment. (2) From 2010 to 2020, the region's WRCC steadily improved, with scores rising from 2.99 to 2.83 and an average of 2.90, suggesting effective water resources management in Pingquan City. (3) According to scenario-based prediction, WRCC may slightly decline between 2025 and 2030, reaching 2.92 and 2.94, respectively, relative to 2020 levels. Therefore, future efforts should focus on strengthening scientific management and promoting the efficient use of water resources. Proactive measures are necessary to mitigate emerging contradiction and ensure the long-term stability and sustainability of the water resources system in the region. The evaluation system and spatiotemporal evolution patterns proposed in this study can provide a scientific basis for refined water resource management and ecological conservation in similar hilly areas.}
}