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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]

• Nationwide streamflow projections for Australia informed by CMIP5 and CMIP6. • Vast majority of CMIP5 and CMIP6 GCMs project less winter rainfall across Australia. • Lower winter rainfall translates to a significant reduction in annual runoff. • Modelled median projection of runoff shows a 50% reduction in far southwest Australia. • Modelled median projection of runoff shows a 20% reduction in far southeast Australia. Projections of streamflow under future climate are essential for developing adaptation strategies in the water and related sectors. This paper presents nationwide streamflow projections for Australia informed by climate change signals in CMIP6 GCMs and compares the projections with those from CMIP5 GCMs. The modelled future runoff projections driven by CMIP5 and CMIP6 GCMs are relatively similar for far southern Australia. The median projection is a 50% reduction in mean annual runoff in far southwest Australia and 20% reduction in far southeast Australia by 2046–2075 relative to 1976–2015 under the high SSP5-8.5/RCP8.5 global warming scenario. The vast majority of CMIP5 and CMIP6 GCMs project less winter rainfall across Australia. As most of the runoff in far southern Australia occurs in winter and spring, the lower winter rainfall translates to a significant reduction in annual runoff. It is therefore prudent to plan and manage for a reduction in future water resources, particularly in the densely populated and important agricultural regions in southeast Australia. There is less agreement between GCMs in the summer rainfall projection, with the CMIP6 GCMs generally projecting a wetter future (or smaller decrease in rainfall) than the CMIP5 GCMs. The modelled median projection for mean annual runoff is a 10% reduction in the south-east coast, 5% reduction in the north-east coast and little change in northern Australia. More GCMs project an increase rather than a decrease in the interannual variability of rainfall, and this would further amplify multi-year hydrological droughts. [ABSTRACT FROM AUTHOR]

• Analysis of 17 years of stream hydrochemistry for an upland catchment in Scotland. • Low flows dominated by weathering products, high flows by soil/atmospheric solutes. • Determinand concentrations were typically correlated with stream water age. • 2018 & 2022 droughts changed the stream to more chemodynamic behaviour. • Associated ecosystem services likely to be impacted with ongoing climate changes. We used data from 17 years of routine stream flow sampling to characterise hydrochemical dynamics in the Girnock Burn, an internationally important long-term catchment monitoring site. We combined hydrochemical time series analysis with hydrological modelling to understand short- and long-term dynamics in relation to dominant runoff processes. Isotopic tracer data employed within the model enabled flux tracking of water as it transited the catchment, facilitating water age estimates. The stream drains an upland 31 km2 catchment with complex topography and variable geology, which influences soil distributions; peaty soils dominate valley bottoms which receive drainage from more permeable podzolic soils on steeper slopes. Short-term hydrochemical dynamics largely reflect the relative dominance of hydrological sources: summer low flows are dominated by alkaline groundwater high in weathering products (Ca2+, Mg2+, SiO 2) whilst high flows generated by overland flow from peaty soils are more acidic, DOC enriched, and dominated by atmospheric solutes (Na+, Cl-, SO 4 2-). Baseflows are dominated by older groundwater (>∼3years) in contrast to storm runoff dominated by younger (<∼0.5 years), near-surface, waters. Usual seasonal distributions of stream flows, with high flows in winter and summer low flows, result in strong seasonality in most solutes. However, coupled effects of hydroclimatic variability and catchment heterogeneity dictates marked scatter in flow-concentration relationships for most determinands. A long-term decreasing trend was evident for SO 4 2-concentrations, reflecting continuing effects of reductions in atmospheric deposition of pollutants from coal burning. Reductions in large storm event frequency post-2016 and protracted periods of low flows in the droughts of 2018 and 2022 have resulted in the catchment becoming dominated by low flows, derived from older groundwater with more alkaline chemistry for longer periods. Changing climatic conditions and stream flow responses seem likely to continue to cause changes in stream water quality and associated ecosystem services of the Girnock Burn and similar upland catchments. [ABSTRACT FROM AUTHOR]

[Display omitted] • Climate change affects the stormwater quality due to variation in climatic parameters. • Scientific interventions with strong database should be geared up in developing nations. • Emerging pollutants needs more attention by undertaking systematic research. • Groundwater recharge with stormwater may raise groundwater level and reduce pollution. The problem of water logging and deteriorating water quality of surface water bodies has been witnessed in and around the urban centers owing to rapid population growth, urbanization, industrialization and climate variability. The stormwater runoff management is the need of the hour, and with increasing public and political awareness and rapid economic growth, it is receiving due attention. In the climate-change scenario, it needs to be addressed with scientific interventions as changes in pattern of precipitation affects the runoff volume and movement of pollutants including nutrients. This paper discussed and critically reviewed the stormwater runoff characterization, modelling, relationship between runoff and water quality, first flush phenomena, runoff treatment in changing climate scenarios. Researchers have used regional climate models (RCMs) to project future precipitation and then incorporated in various hydrologic and hydraulic models such as SWMM, SWAT, HSPF, SUSTAIN and MUSIC etc to study the impact of climate change and its adaptation. The flooding and water quality problem can be combatted with adopting green infrastructure practices. Many works on stormwater management have been carried out in developed countries, but efforts need to be geared up in the developing countries, particularly for runoff characterization and effective management. Emerging pollutants need to be paid more attention by undertaking systematic research. Future studies should include measurements and quantification of ecosystem services and integration of stormwater management into environmental policy. This review suggests intriguing future research avenues at the nexus of stormwater management and ecological services. [ABSTRACT FROM AUTHOR]

• Snowmelt Runoff Model well simulates monthly streamflow in a cold-arid headwater catchment. • Meltwater runoff and rainfall runoff contribute to 42% and 31% of streamflow, respectively. • Total runoff and rainfall runoff are respectively controlled by snow cover and precipitation. • Meltwater runoff is jointly controlled by precipitation, ET, and NDVI. Streamflow is increasingly vulnerable to climate change over cold-arid regions. To understand the underlying mechanisms of streamflow changes, it is essential to distinguish streamflow components and identify their drivers due to various meltwater and rainfall runoff processes. This study combines the conceptual temperature-index Snowmelt Runoff Model (SRM) and wavelet coherence analysis to unravel the impacts of environmental factors on streamflow and its components over the semiarid-and-cold headwater catchment of the Manas River in Northwest China during 2001–2015. Our results show that SRM reproduces monthly observed streamflow with determination coefficients of > 0.91, Nash-Sutcliffe Efficiency of > 0.82, and absolute relative error of < 5 % during SRM calibration (2001–2007) and validation (2008–2015) periods. The meltwater runoff and rainfall runoff contribute to 42 % and 31 % of the total streamflow, respectively. The wavelet-based spectral analysis, partial wavelet coherency analysis, and multiple-wavelet coherence together demonstrate that total streamflow (rainfall runoff) is predominantly influenced by snow cover area (precipitation) at a scale of 32 (4–16) months. But the meltwater runoff is simultaneously controlled by precipitation, potential evapotranspiration, and normalized difference vegetation index on scales of 4–16 and > 32 months. Our study provides technical support for streamflow partitioning and controlling factors identification, and has implication to sustainable water resources management in cold and arid regions. [ABSTRACT FROM AUTHOR]

[Display omitted] • Ten multi-model combination methods (MMCMs) are created from 29 models in 50 basins. • MMCMs improve some performance indicators, especially the Granger-Ramanathan method. • MMCMs do not improve performance in reproducing distributions of hydrological signatures. • Application with series of targeted signatures does not improve MMCM performance. • MMCM performance is improved by selecting more robust candidate models for ensembles. Multi-model combination (averaging) methods (MMCMs) are used to improve the accuracy of hydrological (precipitation-runoff) outputs in simulation or forecasting/prediction modes. In this paper, we examined if the application of MMCMs can improve model performance in reproducing distributions of hydrological signatures, such as annual maxima or minima of varying durations. To this end, ten MMCMs were applied to 29 bucket-type models to simulate runoff in 50 high-latitude catchments. The MMCMs were evaluated by comparing the resulting simulated flows to the reference (i.e., best-performing) individual model, considering various commonly used performance indicators, as well as model performance in reproducing the distributions of signatures. Additionally, we analysed whether (1) the selection of the candidate models, or (2) targeting specific signatures, such as annual maxima or minima, can improve performance of the model combinations. The results suggest that the application of MMCMs can improve accuracy of runoff simulations in terms of traditional performance indicators, but fails to improve performance in reproducing the distributions of signatures. Neither excluding poor-performing models nor applying the MMCMs with the targeted signatures, improves this aspect of model performance. These findings clearly reveal the need for further research aiming at enhancing model performance in reproducing the distributions of hydrological signatures, which is essential for climate-change impact studies. [ABSTRACT FROM AUTHOR]

• Understanding future change with the aspects of runoff and hydroclimatic conditions. • Source region of Yangtze River will be warmer and wetter in the future. • Runoff will increase by around 15% with highly spatial heterogeneity. Exploring the future hydroclimatic conditions of source region of Yangtze River (SRYaR), an alpine affected by climate change significantly, is essential for basin water resources management and development ss global climate change intensifies and the process of climate warming and humidification in Northwest China. This study proposed a practical framework for assessing water resource response to the context of climate changes in alpine catchments from the respective of both runoff and hydroclimatic conditions. Utilizing Grid-RCCC-WBM driven by corrected climatic forcing from the global climate models, this study estimate the prospective overall warmer and wetter pattern in the source region of Yangtze River. The key results indicated that: (1) Under all future scenarios, both temperature and precipitation within the catchment exhibit a significant upward trend. Projections from multi-model ensembles (MME) suggest that during the mid-term period (2041–2060, MT), temperatures are expected to rise by [0.74 °C, 3.08 °C] compared to the baseline period (1995–2014), with precipitation changes ranging from [4.8%, 21.4%]. (2) Future runoff within the catchment exhibits a consistent increase, with a linear trend rate of 1.1 mm/decade. runoff changes in MT compared to the baseline period vary from [−5.1%, 33.7%]. Runoff decreases in the northern part of the catchment, while notable increases occur in the southeastern and western regions. (3) In the future, the ratio of catchment evaporation capacity to precipitation decreases in comparison to the baseline period with an augmentation in soil moisture, enhancing its capacity for water retention and reducing the conversion of precipitation to evaporation, resulting a wetting trend of the catchment. (4) The future snowpack in the catchment continues to decrease, with a significant reduction in both the proportion of snowfall relative to total precipitation and the proportion of snowmelt runoff relative to total runoff, the risk of water resources crisis in the watershed is escalating. [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]