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• 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]

[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]

Water erosion, a notorious major threat to food security and ecosystem sustainability, is strongly conditioned by spatial and temporal scale effects. This paper systematically reviews the scale issues in runoff and sediment delivery (SIRSD) as a research field by integrating the traditional review approach and bibliometric analysis. This review summarises SIRSD's roots and the scale effect on runoff and sediment delivery. Then, we provide quantitative insights into the SIRSD domain's development history, thematic structure, geographic distribution, international cooperation, and methodologies. Findings show that: i) SIRSD arises from the gap between the non-linearity of runoff and sediment delivery across scales and our ability to measure it. Point-based and short-term measurements cannot capture the non-linearities from the spatio-temporal heterogeneities and cross-scale interactions of factors or processes. ii) Previous literature provides evidence that the spatial scaling of specific runoff (r), soil erosion (SE), sediment yield (SSY), or sediment delivery ratio (SDR) with drainage area (A) or slope length (L) exhibits contrasting patterns due to distinct mechanisms. Infiltration-excess and saturation-excess processes account for inverse and positive r - A relations, respectively. Interrill-erosion and rill-erosion cause inverse and positive SE-L relations. Hillslope-erosion and channel/bank-erosion explain inverse and positive SSY-A relations. Downstream increasing deposition and additional sediment inputs drive inverse and positive SDR-A relations. These scaling relationships can be nonlinear or complex due to spatial heterogeneities in land use, vegetation, topography, climate, lithology, and soil characteristics. Hence, applying an empirical scaling equation developed from the region with distinct environmental contexts is not recommended. Furthermore, the existing scaling patterns or equations may require updating given global climate and land use change. iii) SIRSD is a complex and multidisciplinary issue investigated by scientists from 93 countries since 1928. International research has substantially facilitated the understanding of SIRSD; still, more collaboration should focus on less-developed countries with high soil and water loss risks and urgent conservation needs, such as those in Africa and South America under cropland expansion. iv) Scale mismatch and scale break have discredited large-scale erosion and sediment assessments. Incorporating gully and bank erosion into modelling, extending the scale range of the L factor, and expanding the sediment scaling scope from watershed to slope may make a difference. Therefore, more research with nested design incorporating multiple scales is necessary for cross-scale analysis and scalable modelling. Addressing global climate change requires improving real-time urban flood forecasting and integrating downscaled climate models with hydrology, erosion, and sediment transport models. • A bibliometric review of the global SIRSD research for the first time. • SIRSD is rooted in the gap between natural nonlinearity and our measuring ability. • Scaling of specific runoff, erosion, sediment yield, and SDR has diverse patterns. • Scale mismatch and scale break discredit large-scale modelling and assessments. [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]