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Updated: Jun 11, 2026

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Development of a river habitat quality index (RHQI) framework for dry-hot valleys: Unraveling driving mechanisms and
Yaqiu Liu1, Fengyue Zhu2, Mingdian Liu2
1National Agricultural Scientific Observing and Experimental Station for Fisheries Resources and Environment, Guangzhou, Scientific Observing and Experimental Station of Fishery Resources and Environment in the Middle and Lower Reaches of Pearl River, Key Laboratory of Prevention and Control for Aquatic Invasive Alien Species, Fishery Ecological Environment Monitoring Center of Pearl River Basin, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of Aquatic Animal Immunology and Sustainable Aquaculture, Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, 510380, China.
Abstract:
Establishing a comprehensive habitat quality assessment suitable for the dry-hot valley and elucidating its key driving mechanisms are essential for maintaining habitat quality and promoting the conservation of fishery resources within this specialized environment. From June 2023 to September 2024, field investigations were conducted at thirteen sampling sites within the Yuanjiang River, a representative dry-hot valley system in southeastern China. Subsequently, the River Habitat Quality Index (RHQI) assessment system was developed, incorporating twenty-one indicators related to the water environment, river structure, biological factors, and anthropogenic influences. The habitat quality assessment identified six sampling sites of excellent quality and nine of good quality, primarily located in the midstream and downstream areas (e.g., HH, YuY, LHT, and HK). Conversely, 53.85% of the sites upstream were classified as having fair habitat quality, indicating an improvement in habitat conditions downstream. Random forest (RF) analysis and stepwise regression demonstrated that various factors-including water quality, biotic index (BI), biological monitoring working party index (BMWP), water quantity, river sinuosity, sediment type, riverbank vegetation coverage, and surrounding land use-significantly affected variations in fish diversity, biotic integrity, and habitat quality. Furthermore, the partial least squares-structural equation model (PLS-SEM) demonstrated that anthropogenic activities indirectly influence habitat quality by altering water environments and river structures, with biological indicators serving as the primary direct mediators. This mechanistic understanding provides a precise entry point for ecological management in dry-hot-region valleys. This investigation also provides a foundation for informed decision-making concerning the conservation of fishery resources and the evaluation of habitat quality in the Yuanjiang River Basin.
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