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• Four types of models quantified anthropogenic changes and climate variability. • SEM for the attribution analysis of runoff changes was constructed. • SEM quantifies runoff change attribution better than traditional models. • Human activities are the dominant factor of runoff change in Shiyang River Basin. • The contribution rate of water withdrawal to runoff reduction was 50 % during 1961–2020. Recently, with the increasing global warming and intensity of human activities, runoff has significantly decreased. This has had a severe impact on water resources development and utilization, as well as ecological and environmental construction. To understand hydrological cycles and promote sustainable utilization of water resources, it is crucial to conduct attribution analysis of runoff changes. This study employed traditional models, including empirical statistics, elasticity coefficients, hydrological modeling, and introduced a simple and efficient model – structural equation modeling (SEM) – to quantify the impact of various factors on runoff changes. The findings revealed a notable decreasing trend in natural runoff in the Shiyang River from 1960 to 2020, while precipitation, snowmelt, potential evapotranspiration (ET0), and temperature exhibited increasing trends. The integrated the results from multiple models highlighted that human activities emerged as the primary driver influencing runoff changes. From 1972 to 2020, the factors contributing to runoff reduction were ranked in the order: water withdrawal (50 %) > LUCC (20 %) > ET0 (16 %) > temperature (8 %). Factors contributing to runoff increase were ranked: precipitation = water diversion project (20 %) > snowmelt (6 %). The impact of reservoir regulation on runoff initially exhibited a negative correlation (impact rate of 10 %) and later turned positive (impact rate of 6 %). The SEM model, employed for runoff change attribution analysis, demonstrated a good fit and was consistent with results obtained from the SWAT model. Compared to traditional methods, SEM not only allowed for quantitative analysis of the factors' impact on runoff but also explored the interactions between factors and the direct and indirect effects of factors on runoff. This study introduces innovative methods for the attribution analysis of runoff changes, offering valuable insights crucial for the ecological sustainable development of water resources in arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

[Display omitted] • The impact of the uncertainties on the attribution of runoff changes was quantified. • A method was improved to analyze non-monotonic trends in wet, normal, and dry years. • The breakpoint was the main uncertainty source for runoff change attribution. Quantifying the contributions of climate change (CC) and human activities (HAs), which are important drivers of the hydrological cycle, to runoff change by CC and HAs under uncertainty is crucial for water resource management, especially in karst basins. In this study, we adopted the climate elasticity method to assess the impacts of CC and HAs on runoff change in Chengbi River Basin during 1970–2019. Furthermore, the main sources of uncertainty (Budyko formula, breakpoint, and underlying surface characteristics) in runoff change attribution were quantified via analysis of variance method. The improved innovative trend analysis based on the Fisher optimal partition method was first used for the non-monotonic trend analysis. The groundwater storage change obtained through the abcd model was used to obtain the effective precipitation for the Budyko hypothesis. The results indicated that the runoff and precipitation exhibited an increasing trend in wet and normal years, whereas they exhibited a decreasing trend in dry years after 1995 compared with 1970–1994. Furthermore, potential evapotranspiration exhibited no significant trend. The climate elasticity method based on the Budyko formula was effective, and the Choudhury-Yang formula was found to be more suitable than the Fu formula for the basin. The impact of water storage change was not negligible, and water storage change needs to be considered in runoff change attribution. Effective precipitation played a dominant role in runoff change, with a mean contribution rate of 87.85%, whereas the mean contribution rates of potential evapotranspiration and underlying surface characteristics were 22.55% and −10.40%, respectively. The breakpoint was the main source of uncertainties in runoff change attribution and demonstrated the highest contribution to the uncertainties (85.93%). The simultaneous breakpoint of the runoff coefficient was suggested as a reference to determine the confident breakpoint of runoff. The findings of this study are expected to provide a scientific basis for water resource management and contribute to the development of the climate elasticity method. [ABSTRACT FROM AUTHOR]