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• A statistical model of flood elasticity under changing conditions was derived. • The model was applied in a typical tropical monsoon basin of Thailand. • The flood peaks are expected to increase due to deforestation and climate change. • The absolute value of storm-flood elasticity is larger for shorter return periods. • Climate change tends to dominate future flood changes over deforestation. Storms and the resultant floods have caused considerable fatalities and have raised increasing global concerns in the context of climate change and socioeconomic development. The relationships between storms and floods have been explored as storm-flood elasticity, but the shifts of the storm and flood peak distributions under changing conditions have not been sufficiently considered. In this study, a novel statistical model that reflects the relationship between storm distribution and flood distribution under changing conditions has been developed. Due to its concise structure, the statistical model can be easily used to explicitly derive the storm-flood elasticity and quantify the future flood responses to changing climatic and land surface conditions. The statistical model is then applied in a typical tropical monsoon basin in Southeast Asia, the Upper Chao Phraya River Basin (UCPRB), which underwent significant climate change and deforestation. The shifts of the storm and flood frequency curves are modeled via GAMLSS with the aid of wet season dew point and forest cover ratio, and the curves derived from statistical models prove to be consistent with the results from the more computationally intensive process-based model. By examining flood elasticity including storm-flood elasticity and forest-flood elasticity under changing conditions, the response of flood peak to storm peak and forest cover change is expected to weaken as the return period increases. Future flood peaks are expected to change substantially under most emission scenarios, and the changes can be mostly attributed to climate change rather than deforestation. The dominance of climate change over deforestation strengthens in the long-term future and is more evident for shorter return periods, highlighting the indispensable role of climate change mitigation in reducing future flood risks in the UCPRB. The analytical framework developed by this study can also be applied in other climate regions besides tropical regions, which could help to provide insights for future changes in floods and their relationship with climatic and land surface characteristics under changing conditions. [ABSTRACT FROM AUTHOR]

[Display omitted] • CO 2 fluxes were measured in three subtropical mangroves for 16 site years. • VPD stress inhibits mangrove productivity during both exposed and inundated periods. • Meteorological factors and VPD have interactive effects on mangrove productivity. • Tides have independent effects on mangrove productivity through salinity changes. • The threshold effect range of VPD stress on mangrove productivity is 2.50–2.95 kPa. Subtropical mangroves have great potential to sequester atmospheric carbon dioxide (CO 2) and thus significantly contribute to climate change mitigation. Meanwhile, the carbon cycling processes in subtropical mangroves are vulnerable to the changing climatic conditions, such as the warming-induced vapor pressure deficit (VPD) increases. However, the impacts of VPD on net ecosystem production (NEP) in subtropical mangroves remain poorly understood due to a lack of detailed assessment of NEP responses to VPD among different mangrove forests over a long-term observational period. In this study, we deployed eddy-covariance systems to measure net ecosystem CO 2 exchange at three subtropical mangrove forests for 16 site-years, comprising two natural and one artificial forests. We employed a state-of-the-art data-driven modeling approach (i.e., Shapley additive explanations (SHAP) framework based on extreme gradient boosting model), which enabled us to explore the interactive effects of meteorological and tidal factors (e.g. salinity) with VPD on the mangrove NEP. We revealed that air temperature, global solar radiation (GR) and wind speed have significant interactions on the response of NEP to VPD stress in subtropical mangroves. For instance, when GR was high, the SHAP interaction values of VPD and GR on NEP decreased with increasing VPD, but when GR was low, the trends were the opposite. However, instead of identifying interactive effects between tidal salinity and VPD on mangrove NEP, we came across potential independent influence of salinity on the same. SHAP analysis was also able to disentangle the impact of VPD from other abiotic drivers. Thus, we evaluated the threshold effect of VPD stress on NEP loss in subtropical mangroves and observed a range of 2.50–2.95 kPa. Above this range, VPD stress leveled off. The subtropical mangrove responses to VPD should be therefore considered in the dynamic global vegetation models to increase the accuracy in carbon cycle simulations in the future. [ABSTRACT FROM AUTHOR]

[Display omitted] • All year climate change impact in an urban catchment is evaluated using SWMM. • Average annual runoff and seasonal extreme flows are expected to increase. • An overall increase in the number of flow events is modelled, notably in winter. • A holistic stormwater management is needed to mitigate and adapt to climate change. • The benefit of using convection-permitting climate models is evident. Urbanization coupled with climate change is expected to put pressure on the urban stormwater network. To predict and mitigate the effects of these trends, accurate modeling of urban stormwater changes is required at scales and resolutions meaningful to stormwater management. Although numerous studies have analyzed the effect of climate change on urban flooding risk using the event-based approach, none have incorporated the continuous modelling approach to investigate the whole spectrum of changes in an urban catchment. This study analyzes seasonal changes in future urban hydrological behavior using a mini-ensemble of six state-of-the-art climate model projections and a calibrated hydrological-hydraulic Storm Water Management Model (SWMM). The modelling results show future changes in seasonal and monthly hydrological behavior. The notable winter warming is the major driver in the future snow processes, resulting in considerably less snow days and an increase in the flow events frequency during the winter months. The modelling results also suggest an increase in the annual maximum hourly flow in all seasons, with the clearest trend modelled in winter. Monthly average runoff during the cold period is modelled to increase, while no clear trends are detected for the rest of the year. There is a clear added benefit in using convection-permitting regional climate models throughout the year. Overall, the climate change mitigation and adaption strategies in urban catchments should focus more on the whole spectrum of changes rather than only on urban pluvial flooding risk. These findings call for a transition from traditional to a more advanced stormwater management. [ABSTRACT FROM AUTHOR]

• Precipitation, NDVI, and LUCC dominated recipitation the spatial heterogeneity of SM. • Precipitation changes caused up to 40% of the drying up of SM. • SM anomalies at 28–289 cm mainly caused by one-month-old precipitation. • The influences of climate and vegetation were observed to decrease with soil depth. As an essential state variable of the earth's terrestrial system, soil moisture (SM) is highly significant regarding hydrological processes, agricultural production, land management in response to issues like soil erosion etc. However, the net effects of different environmental factors on the heterogeneity and variations of SM remain unclear, due to the complex interactions between variables. Indeed, investigating such effects in the highly climate-vulnerable Mongolian Plateau is imperative for water resource management and climate change adaptation. In this study, we analyzed the contributions of different environmental factors on the spatial heterogeneity and variations of SM in the Mongolian Plateau between 1982 and 2020, using a geographic detector model (GDM) and a novel nonlinear Granger causality model. The results of the GDM analysis demonstrated that precipitation and vegetation were the main controls relevant to SM heterogeneity, with their explanatory powers (Q statistics of GDM) found to be higher than 0.67. In two breakpoints—one in the early 1990′s and another in 2007—SM demonstrated a pattern of increase, then a decrease, subsequently followed by an increase (insignificant decrease in SM at 100–289 cm depth only). Precipitation was identified as the Granger causal of SM variations over 33.39–97.65% of the plateau's vegetated area, leading to the drying up of 40% of its SM. The greatest contribution to SM in 28–289 cm of the plateau was observed as coming from one-month-old precipitation, due to the lag in the manifestation of effects. Further, rising temperatures were found to have an immediate influence (2.73–5.23%) on SM in 14.61–54.90% of the whole plateau's vegetated area, an impact which was relatively high (>14%) in its northeastern wetting zone. Vegetation change posed a relatively weak effect (<2%) on SM over a limited area of the plateau (27.75–35.42%). Although lesser than the impacts of general climate changes, the contributions of climatic extremes could not be neglected, ultimately accounting for up to 10% of SM changes. In summary, this study provides new insights into the individual contributions of various environmental factors on the spatial heterogeneity and variations of SM in the Mongolian Plateau, offering vital information for policymaking regarding climate change mitigation and adaptation, sustainable use of water resources, and ecological restoration for arid and semi-arid region. [ABSTRACT FROM AUTHOR]

• Estimates of the time of emergence of climate change (ToE) for Australian rivers. • Stochastic data generation helps to better define baseline variability. • Uncertainty in ToE represented by 37 CMIP6 projections and 3 emissions scenarios. • ToE in river flows can precede ToE in precipitation by up to 50 years. • ToE substantially delayed or avoided in a low emissions pathway (SSP1-2.6). Climate change impacts on river flows are leading to substantial changes in water availability for human and natural systems. The significance of these impacts largely depends on the degree of change relative to natural variability. The 'Time of Emergence' (ToE) is the point in time (past or future) when the signal of climate change emerges from the noise of background variability. The ToE has been assessed for some climate variables but rarely streamflows. Here we investigate ToE of changes in streamflow across Australia for various characteristic periods relevant to different water management objectives. We assess the uncertainty in ToE estimates from different emissions pathways and a large ensemble of CMIP6 climate model projections. ToE is likely to occur earlier in hydrologic systems subject to low natural variability than those subject to high variability, and to systems that are vulnerable to failure over longer rather than shorter periods. There are clear regional differences in the patterns of ToE, with changes first emerging in south-west regions of Australia, followed by the south-east, then east and north. We estimate that ToE has already occurred in over 10% of sampled rivers for longer characteristic periods, primarily in south-west Australia. Importantly for planning, the results show that ToE in flows precedes ToE in precipitation by up to 50 years due to compounding effects of changes in annual precipitation, precipitation seasonality, and increasing temperatures. The number of catchments projected to have reached ToE by 2080 is heavily influenced by the trajectory of future emissions. A low emissions pathway generally consistent with aspirational goals of the Paris Climate Agreement (SSP1-2.6) substantially delays the emergence of significant hydrological change by up to 50 years, or negates emergence entirely by 2080, depending on location. Our methods can be applied to catchments globally, and our findings have implications for the prioritisation of climate adaptation efforts across different river systems and the urgency of continued action on climate change mitigation. [ABSTRACT FROM AUTHOR]

• Innovate a BaPMI method for macro-scale distributed hydrologic modeling. • Apply it to a typical large cold-region watershed, Athabasca River Basin in Canada. • Verify feasibility & advantages in characterizing macro-scale cold-region hydrology. • Quantify parametric & hyperparametric sensitivities for facilitating its applications. • Reveal variabilities of climate-driven cross-scale uppermost hydro-variational effects. At macroscales (e.g., large river basins, nations, continents, or the globe), hydro-hazard mitigation under climate change requires accurate, applicable hydrologic models, especially over cold regions of complicated hydroclimatic relations. As an effort to address such a challenge, we innovate a macroscale distributed hydro-modeling method, Bayesian principal-monotonicity inference (BaPMI), based on climate classification, representative-grids selection, statistical hydrology, surrogates-based Bayesian optimization, and variance-based sensitivity analyses. The method is applied to a typical large cold-region watershed, i.e., Athabasca River Basin in Canada, and reveals a series of findings such as the following representatives. BaPMI shows promising skills in quantitatively characterizing macroscale cold-region hydrology under overall impacts of heterogeneous climates. Bayesian optimization of which hyperparameters are insensitive decreases hydro-modeling computational time by up to 96.3% and, together with climate classification, largely enhances BaPMI applicability while ensuring modeling accuracies. Individual BaPMI hydro-model parameters can explain over ¾ of the variation of hydro-modeling accuracies and, due to their interaction, joint calibration is required for avoiding underestimation of the impacts. Climatic conditions dominating cross-scale uppermost hydrologic variations consist of night temperature (40%), day temperature (38%), and precipitation (22%) for all catchments; all river flows along the mainstem are associated with upstream climatic events such as glacier melts. Climatic impacts decline from upstream to downstream and from summer, spring, winter to autumn; this may relate to tempo-spatial heterogeneity of soil, vegetation, geology, human interference and other non-climatic factors. Without this study, macroscale distributed hydrologic modeling would lack one advanced method (i.e., BaPMI) that can immunize against effects of data uncertainty, subjective judgement and climatic collinearity, adapt to complicated hydroclimatic relations and diverse hydro-variable(s) distributions, reveal cross-scale uppermost hydrologic variations and, through inexpensive computations, enhance hydro-modeling accuracies to avoid climatic-impact underestimation. The findings of this study could facilitate BaPMI applications and advance macroscale (cold-region) hydrology. [ABSTRACT FROM AUTHOR]

• Streamflow components change divergently across various permafrost rivers. • Generally, higher percentile flows have increased more than lower percentile flows. • Low flows in most rivers increase while high flows exhibit both increase and decrease. • Low flows are more sensitive to warming and less sensitive to rainfall than high flows. • The results suggest increased deep groundwater contributions to river discharge. Cryohydrological processes in the Eurasian Arctic and Qinghai-Tibet Plateau (QTP) permafrost regions have been changing rapidly, yet the details of the river runoff changes are still obscure. Here we use multidecadal natural daily discharge data to compute annual flow duration curves (FDCs) and percentile flows for 20 Eurasian Arctic and QTP river basins with permafrost underlain. We provide detailed trends of various percentile flows that almost all runoff components change variably, either with the distinct magnitude or opposite direction or both. We demonstrate that the lower flows increase monotonically faster than higher flows. Most low flows increase while the high flows show spatial heterogeneity with both increased and decreased trends observed. The portion of deep and total groundwater flow in total discharge increases, with the deep groundwater flow increases faster. Interestingly, the river runoff components respond differently to climatic change factors. The low flows, mainly sustained by groundwater, are more sensitive to warming than high flows, while the high flows are more sensitive to precipitation than low flows. Our results may suggest an increased subsurface hydrological connectivity under the warming climate and thawing permafrost. We show that FDCs have the potential to reveal the long-term runoff components change. Future climatic change may alter the shapes and distributions of FDCs since the asynchronous changes of runoff components, which have important implications for cold region river management and mitigation under climatic change. [ABSTRACT FROM AUTHOR]