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Reduced snow storage has been associated with lower river low flows in mountainous catchments, exacerbating summer hydrological droughts. However, the impacts of changing snow storage on summer low flows in low-elevation, snow-affected catchments has not yet been investigated. To address this knowledge gap, the dominant hydroclimate predictors of summer low flows were first identified through correlation analysis in 12 tributary catchments of the St. Lawrence River in the Canadian province of Quebec. The correlation results show that summer low flow is most sensitive to summer rainfall, while maximum snow water equivalent (SWE) is the dominant winter preconditioning factor of low flows, particularly at the end of summer. The multivariate sensitivity of summer low flow to hydroclimate predictors was then quantified by multilevel regression analysis, considering also the effect of catchment biophysical attributes. Accumulated rainfall since snow cover disappearance was found to be the prime control on summer low flow, as expected for the humid climate of Quebec. Maximum SWE had a secondary but significant positive influence on low flow, sometimes on the same order as the negative effect of evapotranspiration losses. As a whole, our results show that in these low elevation catchments, thicker winter snowpacks that last longer and melt slower in the spring are conducive to higher low flows in the following summer. More rugged and forested catchments with coarser soils were found to have higher summer low flows than flatter agricultural catchments with compacted clayed soils. This emphasizes the role of soils and geology on infiltration, aquifer recharge and related river baseflow in summer. Further climate warming and snowpack depletion could reduce future summer low flow, exacerbating hydrological droughts and impacting ecosystems integrity and ecological services.

Climate anomalies, such as floods and droughts, as well as gradual temperature changes have been shown to adversely affect economies and societies. Although studies find that climate change might increase global inequality by widening disparities across countries, its effects on within-country income distribution have been little investigated, as has the role of rainfall anomalies. Here, we show that extreme levels of precipitation exacerbate within-country income inequality. The strength and direction of the effect depends on the agricultural intensity of an economy. In high-agricultural-intensity countries, climate anomalies that negatively impact the agricultural sector lower incomes at the bottom end of the distribution and generate greater income inequality. Our results indicate that a 1.5-SD increase in precipitation from average values has a 35-times-stronger impact on the bottom income shares for countries with high employment in agriculture compared to countries with low employment in the agricultural sector. Projections with modeled future precipitation and temperature reveal highly heterogeneous patterns on a global scale, with income inequality worsening in high-agricultural-intensity economies, particularly in Africa. Our findings suggest that rainfall anomalies and the degree of dependence on agriculture are crucial factors in assessing the negative impacts of climate change on the bottom of the income distribution.

Background Given the important role that municipalities must play in adapting to climate change, it is more than ever essential to measure their progress in this area. However, measuring municipalities’ adaptation progress presents its share of difficulties especially when it comes to comparing (on similar dimensions and over time) the situation of different municipal entities and to linking adaptation impacts to local actions. Longitudinal studies with recurring indicators could capture changes occurring over time, but the development of such indicators requires great emphasis on methodological and psychometric aspects, such as measurement validity. Therefore, this study aimed to develop and validate an index of adaptation to heatwaves and flooding at the level of municipal urbanists and urban planners. Methods A sample of 139 officers working in urbanism and urban planning for municipal entities in the province of Quebec (Canada) completed an online questionnaire. Developed based on a literature review and consultation of representatives from the municipal sector, the questionnaire measured whether the respondent’s municipal entity did or did not adopt the behaviors that are recommended in the scientific and gray literature to adapt to heatwaves and flooding. Results Results of the various metrological analyses (indicator reliability analysis, first order confirmatory factor analysis, concurrent validity analysis, and nomological validity assessment analysis) confirmed the validity of the index developed to measure progress in climate change adaptation at the municipal level. The first dimension of the index corresponds to preliminary measures that inform and prepare stakeholders for action (i.e., groundwork adaptation initiatives), whereas the second refers to measures that aim to concretely reduce vulnerability to climate change, to improve the adaptive capacity or the resilience of human and natural systems (i.e., adaptation actions). Conclusion The results of a series of psychometric analyses showed that the index has good validity and could properly measure the adoption of actions to prepare for adaptation as well as adaptation actions per se. Municipal and government officials can therefore consider using it to monitor and evaluate adaptation efforts at the municipal level.

Abstract Risk management has reduced vulnerability to floods and droughts globally 1,2 , yet their impacts are still increasing 3 . An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data 4,5 . On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change 3 .

Right after a devastating multi-year drought, a number of flood events with unprecedented spatial extent hit different parts of Iran over the 2-week period of March 17th to April 1st, 2019, causing a human disaster and substantial loss of assets and infrastructure across urban and rural areas. Here, we investigate natural (e.g., rainfall, snow accumulation/melt, soil moisture) and anthropogenic drivers (e.g., deforestation, urbanization, and management practices) of these events using a range of ground-based data and satellite observations. These drivers can range from exceptionally extreme rainfall intensities, to cascades of several extreme and moderate events, and various anthropogenic interventions that exacerbated flooding. Our results reveal strong compounding impacts of natural drivers and anthropogenic triggers in escalating flood risks to unprecedented levels. We argue that a new form of floods, i.e. anthropogenic floods, is becoming more common and should be recognized during the “Anthropocene”. This specific form of floods refers to high to extreme streamflow/runoff events that are primarily caused, or largely exacerbated, by anthropogenic drivers. We demonstrate how the growing risk of anthropogenic floods can be assessed using a wide range of climatic and non-climatic satellite and in-situ data.