Quantile-based downscaling of rainfall extremes: Notes on methodological functionality, associated uncertainty and application in practice - Hassanzadeh, Elmira; Nazemi, Ali; Adamowski, Jan; Nguyen, Truong-Huy; Van-Nguyen, Van-Thanh (Advances in Water Resources, 2019)

A Stochastic Data‐Driven Ensemble Forecasting Framework for Water Resources: A Case Study Using Ensemble Members Derived From a Database of Deterministic Wavelet‐Based Models - Quilty, John; Adamowski, Jan; Boucher, Marie‐Amélie (Water Resources Research, 2019)
Abstract In water resources applications (e.g., streamflow, rainfall‐runoff, urban water demand [UWD], etc.), ensemble member selection and ensemble member weighting are two difficult yet important tasks in the development of ensemble forecasting systems. We propose and test a stochastic data‐driven ensemble forecasting framework that uses archived deterministic forecasts as input and results in probabilistic water resources forecasts. In addition to input data and (ensemble) model output uncertainty, the proposed approach integrates both ensemble member selection and weighting uncertainties, using input variable selection and data‐driven methods, respectively. Therefore, it does not require one to perform ensemble member selection and weighting separately. We applied the proposed forecasting framework to a previous real‐world case study in Montreal, Canada, to forecast daily UWD at multiple lead times. Using wavelet‐based forecasts as input data, we develop the Ensemble Wavelet‐Stochastic Data‐Driven Forecasting Framework, the first multiwavelet ensemble stochastic forecasting framework that produces probabilistic forecasts. For the considered case study, several variants of Ensemble Wavelet‐Stochastic Data‐Driven Forecasting Framework, produced using different input variable selection methods (partial correlation input selection and Edgeworth Approximations‐based conditional mutual information) and data‐driven models (multiple linear regression, extreme learning machines, and second‐order Volterra series models), are shown to outperform wavelet‐ and nonwavelet‐based benchmarks, especially during a heat wave (first time studied in the UWD forecasting literature). , Key Points A stochastic data‐driven ensemble framework is introduced for probabilistic water resources forecasting Ensemble member selection and weighting uncertainties are explicitly considered alongside input data and model output uncertainties Wavelet‐based model outputs are used as input to the framework for an urban water demand forecasting study outperforming benchmark methods

Estimates of gridded relative changes in 24-h extreme rainfall intensities based on pooled frequency analysis - Requena, Ana I.; Burn, Donald H.; Coulibaly, Paulin (Journal of Hydrology, 2019)

Strategies for integrating water management and spatial planning: Organising for spatial quality in the Dutch “Room for the River” program - Busscher, T.; Van Den Brink, M.; Verweij, S. (Journal of Flood Risk Management, 2019)
In response to extreme flood events and an increasing awareness that traditional flood control measures alone are inadequate to deal with growing flood risks, spatial flood risk management strategies have been introduced. These strategies do not only aim to reduce the probability and consequences of floods, they also aim to improve local and regional spatial qualities. To date, however, research has been largely ignorant as to how spatial quality, as part of spatial flood risk management strategies, can be successfully achieved in practice. Therefore, this research aims to illuminate how spatial quality is achieved in planning practice. This is done by evaluating the configurations of policy instruments that have been applied in the Dutch Room for the River policy program to successfully achieve spatial quality. This policy program is well known for its dual objective of accommodating higher flood levels as well as improving the spatial quality of the riverine areas. Based on a qualitative comparative analysis, we identified three successful configurations of policy instruments. These constitute three distinct management strategies: the “program‐as‐guardian”, the “project‐as‐driver,” and “going all‐in” strategies. These strategies provide important leads in furthering the development and implementation of spatial flood risk management, both in the Netherlands and abroad.
Keywords: Ouvrage_Collectif_Numéro1

Are We Adapting to Floods? Evidence from Global Flooding Fatalities - Miao, Qing (Risk Analysis, 2019)
Abstract There has been a growing interest in understanding whether and how people adapt to extreme weather events in a changing climate. This article presents one of the first empirical analyses of adaptation to flooding on a global scale. Using a sample of 97 countries between 1985 and 2010, we investigate the extent and pattern of flood adaptation by estimating the effects of a country's climatological risk, recent flood experiences, and socioeconomic characteristics on its flood‐related fatalities. Our results provide mixed evidence on adaptation: countries facing greater long‐term climatological flooding risks do not necessarily adapt better and suffer fewer fatalities; however, after controlling for the cross‐country heterogeneity, we find that more recent flooding shocks have a significant and negative effect on fatalities from subsequent floods. These findings may suggest the short‐term learning dynamics of adaptation and potential inefficacy of earlier flood control measures, particularly those that promote increased exposure in floodplains. Our findings provide important implications for climate adaptation policy making and climate modeling.

Instruments for Strategies to Face Floods through Prevention, Mitigation, and Preparation in Europe: The Age of Alignment - Gralepois, Mathilde (Facing Hydrometeorological Extreme Events, 2019)
Keywords: Ouvrage_Collectif_Numéro1

Governance Challenges Facing Hydrometeorological Extreme Events - La Jeunesse, Isabelle; Larrue, Corinne (Facing Hydrometeorological Extreme Events, 2019)
Keywords: Ouvrage_Collectif_Numéro1

Psychosocial vulnerability and demographic characteristics in extreme flash floods: The case of Mandra 2017 flood in Greece - Speis, Phoebe-Demeter; Andreadakis, Emmanuel; Diakakis, Michalis; Daidassi, Evanthia; Sarigiannis, Georgios (International Journal of Disaster Risk Reduction, 2019)
Keywords: Ouvrage_Collectif_Numéro1