Deep Huber quantile regression networks

Typical machine learning regression applications aim to report the mean or the median of the predictive probability distribution, via training with a squared or an absolute error scoring function. The importance of issuing predictions of more functionals of the predictive probability distribution (quantiles and expectiles) has been recognized as a means to quantify the uncertainty of the prediction. In deep learning (DL) applications, that is possible through quantile and expectile regression neural networks (QRNN and ERNN respectively). Here we introduce deep Huber quantile regression networks (DHQRN) that nest QRNNs and ERNNs as edge cases. DHQRN can predict Huber quantiles, which are more general functionals in the sense that they nest quantiles and expectiles as limiting cases. The main idea is to train a deep learning algorithm with the Huber quantile regression function, which is consistent for the Huber quantile functional. As a proof of concept, DHQRN are applied to predict house prices in Australia. In this context, predictive performances of three DL architectures are discussed along with evidential interpretation of results from an economic case study.Comment: 31 pages, 9 figure

Creating Community for Early-Career Geoscientists:Student involvement in geoscience unions: A case study from hydrology

The American Geophysical Union (AGU) and the European Geosciences Union (EGU) play central roles in nurturing the next generation of geoscientists. Students and young scientists make up about one-quarter of the unions’ active memberships [American Geophysical Union, 2013; European Geosciences Union, 2014], creating a major opportunity to include a new generation of geoscientists as more active contributors to the organizations’ activities, rather than merely as consumers

Prioritization and selection of climate change adaptation measures: a review of the literature

Adaptation to climate change is key to reduce associated risks and develop climate resilient communities. Adaptation measures should be designed for both current and future impacts of climate change. Nevertheless, the inherent uncertainty in climate change and its impacts, and also the intrinsic complexity in climate change adaptation process present challenges in developing, planning, and effective implementation of appropriate adaptation strategies in many countries. Despite the improvements, it is due to these challenges that the planned adaptation to climate change still has not reached the desired levels. In particular, there are key issues and knowledge gaps associated with climate change related decision-making. For example, although generic frameworks for the assessment of climate change risks and vulnerability are available in certain EU member countries (e.g., United Kingdom, Netherlands, Denmark, Germany, Norway), there is a gap in developing a common methodology for the prioritization and selection of adaptation measures. The methods which are most widely used for prioritizing (and selecting) adaption measures are Benefit Cost Analysis (BCA), Cost Effectiveness Analysis (CEA), Multi-Criteria Analysis (MCA), and expert judgment. While each method has its advantages and disadvantages, their applicability in inter-regional, cross-sectoral, cross-border, multilevel, and multi-actor cases are rather limited. At present, a systematic and comprehensive methodology which is capable of taking into account the characteristics of the case-of-concern in terms of the constraints at hand such as insufficient local resources or site-specific vulnerabilities is absent. The principles of no-regret, low-regret, and win-win are often employed in identification of appropriate adaptation measures as a first step. The purpose of this study is to provide a critical review of the current primary approaches and methods for prioritization and selection of climate change adaptation measures

The role of young professionals in driving the integration of early warning ystems

Early warning systems (EWSs) help society to prepare for, and respond to, all types of disasters, including those related to hydrometeorological hazards. They save lives and minimize potential economic and environmental damages. Several international initiatives at the regional and global levels address early warning systems. The Sendai Framework for Disaster Risk Reduction 2015–20306 specifically highlights the need to “substantially increase the availability of and access to multi-hazard early warning systems and disaster-risk information and assessments to the people by 2030.” It urges efforts to make forecasting and EWSs more efficient, integrated and sustainable7,8. The WMO governance reform too emphasizes the importance of delivering integrated multi-hazard and impact-based services through EWSs that are scientific and people-centred. In this context, what is the role of young professionals – who would be mid-career by 2030 – in the design and implementation of integrated multi-hazard and impact-based EWS?Peer ReviewedPostprint (published version

The Role of Young Professionals in Driving the Integration of Early Warning Systems

Early warning systems (EWSs) help society to prepare for, and respond to, all types of disasters, including those related to hydrometeorological hazards. They save lives and minimize potential economic and environmental damages. Several international initiatives at the regional and global levels address early warning systems. The Sendai Framework for Disaster Risk Reduction 2015–20306 specifically highlights the need to “substantially increase the availability of and access to multi-hazard early warning systems and disaster-risk information and assessments to the people by 2030.” It urges efforts to make forecasting and EWSs more efficient, integrated and sustainable 7,8. The WMO governance reform too emphasizes the importance of delivering integrated multi-hazard and impact-based services through EWSs that are scientific and people-centred. In this context, what is the role of young professionals – who would be mid-career by 2030 – in the design and implementation of integrated multi-hazard and impact-based EWS

The Role of Young Professionals in Driving the Integration of Early Warning Systems

International audienc

AN EDUCATIONAL PERSPECTIVE ON FLOOD RISK MANAGEMENT

Flood risk management (FRM) has emerged as a key concern posing significant engineering and societal challenges in all around the world. Management of and adaptation to increased flood risk is therefore essential, and requires development of sustainable and effective FRM strategies that embrace a holistic and integrated approach. This approach emphasizes the necessity to address research on and practice in FRM in an interdisciplinary fashion. Accordingly, the field of FRM incorporates a variety of disciplines and subjects including meteorology, hydrology, climatology, water resources, hydraulics, hydroinformatics, forecasting and early warning, climate change, decisionmaking (under uncertainty), spatial planning, risk perception and communication, risk governance (e.g. institutional framework and policy development), and socioeconomics

A hydrologist's guide to open science

Open, accessible, reusable, and reproducible hydrologic research can have a significant positive impact on the scientific community and broader society. While more individuals and organizations within the hydrology community are embracing open science practices, technical (e.g., limited coding experience), resource (e.g., open access fees), and social (e.g., fear of weaknesses being exposed or ideas being scooped) challenges remain. Furthermore, there are a growing number of constantly evolving open science tools, resources, and initiatives that can be overwhelming. These challenges and the ever-evolving nature of the open science landscape may seem insurmountable for hydrologists interested in pursuing open science. Therefore, we propose the general “Open Hydrology Principles” to guide individual and community progress toward open science for research and education and the “Open Hydrology Practical Guide” to improve the accessibility of currently available tools and approaches. We aim to inform and empower hydrologists as they transition to open, accessible, reusable, and reproducible research. We discuss the benefits as well as common open science challenges and how hydrologists can overcome them. The Open Hydrology Principles and Open Hydrology Practical Guide reflect our knowledge of the current state of open hydrology; we recognize that recommendations and suggestions will evolve and expand with emerging open science infrastructures, workflows, and research experiences. Therefore, we encourage hydrologists all over the globe to join in and help advance open science by contributing to the living version of this document and by sharing open hydrology resources in the community-supported repository (https://open-hydrology.github.io, last access: 1 February 2022).Water Resource