• Energy Research

La gestion des risques a réduit la vulnérabilité aux inondations et aux sécheresses dans le monde1,2, mais leurs impacts continuent d'augmenter3. Une meilleure compréhension des causes de l'évolution des impacts est donc nécessaire, mais a été entravée par un manque de données empiriques4,5. Sur la base d'un ensemble de données mondiales de 45 paires d'événements qui se sont produits dans la même zone, nous montrons que la gestion des risques réduit généralement les impacts des inondations et des sécheresses, mais fait face à des difficultés pour réduire les impacts d'événements sans précédent d'une ampleur jamais connue auparavant. Si le deuxième événement était beaucoup plus dangereux que le premier, son impact était presque toujours plus élevé. En effet, la gestion n'a pas été conçue pour faire face à de tels événements extrêmes : par exemple, ils ont dépassé les niveaux de conception des digues et des réservoirs. Dans deux cas de réussite, l'impact du deuxième événement, plus dangereux, a été plus faible, en raison de l'amélioration de la gouvernance de la gestion des risques et des investissements élevés dans la gestion intégrée. La difficulté observée à gérer des événements sans précédent est alarmante, étant donné que des événements hydrologiques plus extrêmes sont projetés en raison du changement climatique3. La gestión de riesgos ha reducido la vulnerabilidad a las inundaciones y sequías a nivel mundial1,2, pero sus impactos siguen aumentando3. Por lo tanto, se necesita una mejor comprensión de las causas de los impactos cambiantes, pero se ha visto obstaculizada por la falta de datos empíricos4,5. Sobre la base de un conjunto de datos global de 45 pares de eventos que ocurrieron dentro de la misma área, mostramos que la gestión de riesgos generalmente reduce los impactos de inundaciones y sequías, pero enfrenta dificultades para reducir los impactos de eventos sin precedentes de una magnitud no experimentada anteriormente. Si el segundo evento era mucho más peligroso que el primero, su impacto era casi siempre mayor. Esto se debe a que la gestión no fue diseñada para hacer frente a tales eventos extremos: por ejemplo, superaron los niveles de diseño de diques y embalses. En dos casos de éxito, el impacto del segundo evento, más peligroso, fue menor, como resultado de una mejor gobernanza de la gestión de riesgos y una alta inversión en la gestión integrada. La dificultad observada para gestionar eventos sin precedentes es alarmante, dado que se proyectan eventos hidrológicos más extremos debido al cambio climático3. Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. 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 change3. أدت إدارة المخاطر إلى تقليل التعرض للفيضانات والجفاف على مستوى العالم1,2، ومع ذلك لا تزال آثارها تتزايد3. لذلك هناك حاجة إلى فهم أفضل لأسباب تغير التأثيرات، ولكن أعيق ذلك بسبب نقص البيانات التجريبية4، 5. على أساس مجموعة بيانات عالمية مكونة من 45 زوجًا من الأحداث التي وقعت داخل نفس المنطقة، نظهر أن إدارة المخاطر تقلل عمومًا من آثار الفيضانات والجفاف ولكنها تواجه صعوبات في الحد من آثار الأحداث غير المسبوقة ذات الحجم الذي لم تشهده من قبل. إذا كان الحدث الثاني أكثر خطورة من الأول، فإن تأثيره كان دائمًا أعلى. وذلك لأن الإدارة لم تكن مصممة للتعامل مع مثل هذه الأحداث المتطرفة: على سبيل المثال، تجاوزت مستويات تصميم السدود والخزانات. في قصتي نجاح، كان تأثير الحدث الثاني، الأكثر خطورة، أقل، نتيجة لتحسين حوكمة إدارة المخاطر والاستثمار العالي في الإدارة المتكاملة. إن الصعوبة الملحوظة في إدارة الأحداث غير المسبوقة تنذر بالخطر، بالنظر إلى أنه من المتوقع حدوث المزيد من الأحداث الهيدرولوجية المتطرفة بسبب تغير المناخ3.

Finding sustainable pathways to efficiently allocate limited available water resources among increasingly competing water uses has become crucial due to climate-change-induced water shortages and increasing water demand. This has led to an urgent need for the inclusion of economic principles, models, and methods in water resources management. Although several studies have developed macro-economic models to evaluate the economic impacts of alternative water allocation strategies, many if not most ignore the hydrological boundaries of transboundary river basins. Furthermore, of those using input-output (IO) models, only a handful have applied supply-side IO models. In this paper, we present one of the first attempts to develop an inter-regional, supply-side IO modelling framework for a multi-jurisdictional, transboundary river basin to assess the direct and indirect economic impacts of water supply restrictions due to climate and policy change. Applying this framework to the Saskatchewan River Basin in Canada encompassing three provinces, we investigate the economic impacts of two different water supply restriction scenarios on the entire river basin and its sub-basins individually. We find that in the face of climate-change-induced water shortage, economic losses can be reduced by almost 50% by adopting appropriate management practices, including prioritization of water allocation, using alternative water sources, and water re-use technologies.

AbstractRisk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. 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 change3.

This study proposes an integrated modeling system consisting of the physically-based MIKE SHE/MIKE 11 model, a cellular automata model, and general circulation models (GCMs) scenarios to investigate the independent and combined effects of future climate and land-use/land-cover (LULC) changes on the hydrology of a river system. The integrated modelling system is applied to the Elbow River watershed in southern Alberta, Canada in conjunction with extreme GCM scenarios and two LULC change scenarios in the 2020s and 2050s. Results reveal that LULC change substantially modifies the river flow regime in the east sub-catchment, where rapid urbanization is occurring. It is also shown that the change in LULC causes an increase in peak flows in both the 2020s and 2050s. The impacts of climate and LULC change on streamflow are positively correlated in winter and spring, which intensifies their influence and leads to a significant rise in streamflow, and, subsequently, increases the vulnerability of the watershed to spring floods. This study highlights the importance of using an integrated modeling approach to investigate both the independent and combined impacts of climate and LULC changes on the future of hydrology to improve our understanding of how watersheds will respond to climate and LULC changes.

As the negative impacts of hydrological extremes increase in large parts of the world, a better understanding of the drivers of change in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is a lack of comprehensive, empirical data about the processes, interactions and feedbacks in complex human-water systems leading to flood and drought impacts. To fill this gap, we present an IAHS Panta Rhei benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area (Kreibich et al. 2017, 2019). The contained 45 paired events occurred in 42 different study areas (in three study areas we have data on two paired events), which cover different socioeconomic and hydroclimatic contexts across all continents. The dataset is unique in covering floods and droughts, in the number of cases assessed and in the amount of qualitative and quantitative socio-hydrological data contained. References to the data sources are provided in 2023-001_Kreibich-et-al_Key_data_table.xlsx where possible. Based on templates, we collected detailed, review-style reports describing the event characteristics and processes in the case study areas, as well as various semi-quantitative data, categorised into management, hazard, exposure, vulnerability and impacts. Sources of the data were classified as follows: scientific study (peer-reviewed paper and PhD thesis), report (by governments, administrations, NGOs, research organisations, projects), own analysis by authors, based on a database (e.g. official statistics, monitoring data such as weather, discharge data, etc.), newspaper article, and expert judgement. The campaign to collect the information and data on paired events started at the EGU General Assembly in April 2019 in Vienna and was continued with talks promoting the paired event data collection at various conferences. Communication with the Panta Rhei community and other flood and drought experts identified through snowballing techniques was important. Thus, data on paired events were provided by professionals with excellent local knowledge of the events and risk management practices.

AbstractGlobal sensitivity analysis (GSA) provides essential insights into the behavior of Earth and environmental systems models and identifies dominant controls of output uncertainty. Previous work on GSA, however, has typically been under the assumption that the controlling factors such as model inputs and parameters are independent, whereas, in many cases, they are correlated and their joint distribution follows a variety of forms. Although this assumption can limit the credibility of GSA and its results, very few studies in the field of water and environmental modeling address this issue. In this paper, we first discuss the significance of correlation effects in GSA and then propose a new GSA framework for properly accounting for correlations in input/parameter spaces. To this end, we extend the “variogram‐based” theory of GSA, called variogram analysis of response surfaces (VARS), and develop a new generalized star sampling technique (called gSTAR) to accommodate correlated multivariate distributions. We test the new gSTAR‐VARS method on two test functions, against a state‐of‐the‐art GSA method that handles correlation effects. We then apply gSTAR‐VARS to the HBV‐SASK model, calibrated via a Bayesian, Markov chain Monte Carlo approach, for design flood estimation in the Oldman River Basin in Canada. Results demonstrate that accounting for correlation effects can be critically important in GSA, especially in the presence of nonlinearity and interaction effects in the underlying response surfaces. The proposed method can efficiently handle correlations and different distribution types and simultaneously generate a range of sensitivity indices, such as total‐variogram effects, variance‐based total‐order effects, and derivative‐based elementary effects.