Indicators of Hydrologic Alteration (IHA) are commonly screened with the Range of Variability Approach (RVA), which captures frequency shifts but can miss changes in central tendency, dispersion, distributional shape, and trend. We propose a Comprehensive Degree (CD) index that integrates RVA with these four statistical dimensions and apply it to daily discharge at the Xining station on the Huangshui River (1954–2022). Using conventional RVA, the overall alteration was 61.16% (moderate). After integration, alteration increased by 7.59% to 68.75%, reclassifying the regime as high. Across 32 Indicators, 15 showed larger alteration and 12 moved up one class, whereas 17 decreased and 2 moved down. Distributional shape and trend dominated the signal, revealing strongly altered ecohydrological indicators—most notably low-pulse frequency/duration and 3-day minimum—and, additionally, flagging indicators that RVA downplays (e.g., April–August monthly flows) via high trend and distributional shape shifts. The framework addresses RVA’s frequency-only blind spots, is more robust to short-term or episodic fluctuations, and improves diagnostic precision and ecological interpretability. These results provide a decision-ready basis for adaptive environmental flow management in climatically sensitive, topographically complex plateau basins.
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Wang et al. (2025) studied this question.
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