Contribution à une meilleure estimation des paramètres d'une crue décennale : la méthode "DELTAQIX"

L'absence ou la rareté des données hydrométriques sur les bassins ruraux nous conduit à utiliser des approches empiriques en établissant des liaisons entre les débits et les facteurs géométriques ou climatologiques des bassins versants. La méthode DELTAQIX proposée ici est une méthode intermédiaire entre deux méthodes fréquemment appliquées en France, SOCOSE et CRUPEDIX. La méthode DELTAQIX améliore l'estimation du débit instantané maximum (QIX) décennal, par la prise en compte de variables hydrologiques intermédiaires. Elle propose également une nouvelle définition d'un temps caractéristique de crue (DELTA) ainsi qu'un hydrogramme de projet en utilisant les courbes débit-durée-fréquence. (Résumé d'auteur

Research Article Solution of Two-dimensional Transient Heat Conduction in a Hollow Sphere under Harmonic boundary condition

Abstract: In this study, an analytical modeling of two dimensional heat conduction in a hollow sphere, subjected to time dependent periodic boundary condition at the inner and the outer surfaces, is performed. The thermo physical properties of the material are assumed to be isotropic and homogenous. Also, the effects of the temperature oscillations frequency on the boundaries, the thickness variation of the hollow sphere and thermo physical properties of the ambient and the sphere involved in some dimensionless numbers are studied. The results show that the obtained temperature distribution contains two characteristics, the dimensionless amplitude and the dimensionless phase difference. Comparison between the present results and the findings of the previous study as related to a twodimensional solution of the hollow sphere subjected to the simple harmonic condition shows a good agreement

Transdisciplinary approaches to local sustainability: aligning local governance and navigating spillovers with global action towards the Sustainable Development Goals

In an evolving world, effectively managing human–natural systems under uncertainty becomes paramount, particularly when targeting the United Nations 2030 Agenda for Sustainable Development Goals (SDGs). The complexity in multi-actor decision-making and multi-sectoral settings, coupled with intricate relationships and potential conflicting management approaches, makes understanding the local implications of progressing towards the global SDGs challenging. We used a transdisciplinary approach for knowledge co-production with local stakeholders to assess the impact of local action to boost sustainability in the Goulburn–Murray region, Victoria, Australia, and its alignment with global action towards the SDGs. Together, we co-developed 11 local actions geared towards achieving four locally important environmental and socioeconomic SDGs, with a particular emphasis on addressing potential ‘spillovers’—unintended effects that influence SDGs across scales. Through system dynamics modelling, we evaluated the interplay between these local actions and global scenarios, emphasising their synergies, trade-offs, and the resulting impact on SDG indicators. Key findings indicate a predominant synergy between global and local actions across most SDG indicators. However, certain areas like dairy production, riverine algal blooms, and agricultural profit displayed trade-offs. Local actions significantly impacted indicators, such as crop production, dairy output, agricultural land use, and agricultural profitability. Findings highlighted the need for complementary actions in areas, such as water availability management, skilled workforce, and salinity control. This study underscored the importance of harmonising local initiatives with global sustainability objectives and can inspire local governance to champion resilience policies that harmoniously integrate local actions with global sustainability goals, adapting to evolving uncertainty scenarios

Sources, Occurrence and Characteristics of Fluorescent Biological Aerosol Particles Measured Over the Pristine Southern Ocean.

In this study, we investigate the occurrence of primary biological aerosol particles (PBAP) over all sectors of the Southern Ocean (SO) based on a 90-day data set collected during the Antarctic Circumnavigation Expedition (ACE) in austral summer 2016-2017. Super-micrometer PBAP (1-16 µm diameter) were measured by a wide band integrated bioaerosol sensor (WIBS-4). Low (3σ) and high (9σ) fluorescence thresholds are used to obtain statistics on fluorescent and hyper-fluorescent PBAP, respectively. Our focus is on data obtained over the pristine ocean, that is, more than 200 km away from land. The results indicate that (hyper-)fluorescent PBAP are correlated to atmospheric variables associated with sea spray aerosol (SSA) particles (wind speed, total super-micrometer aerosol number concentration, chloride and sodium concentrations). This suggests that a main source of PBAP over the SO is SSA. The median percentage contribution of fluorescent and hyper-fluorescent PBAP to super-micrometer SSA was 1.6% and 0.13%, respectively. We demonstrate that the fraction of (hyper-)fluorescent PBAP to total super-micrometer particles positively correlates with concentrations of bacteria and several taxa of pythoplankton measured in seawater, indicating that marine biota concentrations modulate the PBAP source flux. We investigate the fluorescent properties of (hyper-)fluorescent PBAP for several events that occurred near land masses. We find that the fluorescence signal characteristics of particles near land is much more variable than over the pristine ocean. We conclude that the source and concentration of fluorescent PBAP over the open ocean is similar across all sampled sectors of the SO

Asynchronous Decentralized Task Allocation for Dynamic Environments

This work builds on a decentralized task allocation algorithm for networked agents communicating through an asynchronous channel, by extending the Asynchronous Consensus-Based Bundle Algorithm (ACBBA) to account for more real time implementation issues resulting from a decentralized planner. This paper specfically talks to the comparisons between global and local convergence in asynchronous consensus algorithms. Also a feature called asynchronous replan is introduced to ACBBA's functionality that enables e ffcient updates to large changes in local situational awareness. A real-time software implementation using multiple agents communicating through the user datagram protocol (UDP) validates the proposed algorithm.United States. Air Force (grant FA9550-08-1-0086)United States. Air Force Office of Scientific Research (grant FA9550-08-1-0086)Aurora Flight Sciences Corp. (SBIR - FA8750-10-C-0107

Fermions and Loops on Graphs. I. Loop Calculus for Determinant

This paper is the first in the series devoted to evaluation of the partition function in statistical models on graphs with loops in terms of the Berezin/fermion integrals. The paper focuses on a representation of the determinant of a square matrix in terms of a finite series, where each term corresponds to a loop on the graph. The representation is based on a fermion version of the Loop Calculus, previously introduced by the authors for graphical models with finite alphabets. Our construction contains two levels. First, we represent the determinant in terms of an integral over anti-commuting Grassman variables, with some reparametrization/gauge freedom hidden in the formulation. Second, we show that a special choice of the gauge, called BP (Bethe-Peierls or Belief Propagation) gauge, yields the desired loop representation. The set of gauge-fixing BP conditions is equivalent to the Gaussian BP equations, discussed in the past as efficient (linear scaling) heuristics for estimating the covariance of a sparse positive matrix.Comment: 11 pages, 1 figure; misprints correcte

Eight Archetypes of Sustainable Development Goal (SDG) Synergies and Trade‐Offs

Achieving the Sustainable Development Goals (SDGs) is contingent on managing complex interactions that create synergies and trade-offs between different goals. It is, therefore, important to improve our understanding of them, their underlying causal drivers, future behaviors, and policy implications. Prominent methods of interaction analysis that focus on modeling or data-driven statistical correlation are often insufficient for giving an integrated view of interaction drivers and their complexity. These methods are also usually too technically complex and heavily data-driven to provide decision-makers with simple practical tools and easily actionable and understandable results. Here, we introduce a flexible and practical systemic approach, termed archetype analysis, that generalizes a number of recurring interaction patterns among the SDGs with unique drivers, behaviors, and policy implications. We review eight interaction archetypes as thinking aids to analyze some of the important synergies and trade-offs, supported by several empirical examples related to the SDGs (e.g., poverty, food, well-being, water, energy, housing, climate, and land use) to demonstrate how they can be operationalized in practice. The interaction archetypes are aimed to help researchers and policymakers as a diagnostic tool to identify fundamental mechanisms of barriers or policy resistance to SDG progress, a comparative tool to enhance knowledge transfer between different cases with similar drivers, and a prospective tool to design synergistic policies for sustainable development

Knowledge co-production for decision-making in human-natural systems under uncertainty

Decision-making under uncertainty is important for managing human-natural systems in a changing world. A major source of uncertainty is linked to the multi-actor settings of decisions with poorly understood values, complex relationships, and conflicting management approaches. Despite general agreement across disciplines on co-producing knowledge for viable and inclusive outcomes in a multi-actor context, there is still limited conceptual clarity and no systematic understanding on what co-production means in decision-making under uncertainty and how it can be approached. Here, we use content analysis and clustering to systematically analyse 50 decision-making cases with multiple time and spatial scales across 26 countries and in 9 different sectors in the last decade to serve two aims. The first is to synthesise the key recurring strategies that underpin high quality decision co-production across many cases of diverse features. The second is to identify important deficits and opportunities to leverage existing strategies towards flourishing co-production in support of decision-making. We find that four general strategies emerge centred around: promoting innovation for robust and equitable decisions; broadening the span of co-production across interacting systems; fostering social learning and inclusive participation; and improving pathways to impact. Additionally, five key areas that should be addressed to improve decision co-production are identified in relation to: participation diversity; collaborative action; power relationships; governance inclusivity; and transformative change. Characterising the emergent strategies and their key areas for improvement can help guide future works towards more pluralistic and integrated science and practice

Sources and nature of ice-nucleating particles in the free troposphere at Jungfraujoch in winter 2017

Primary ice formation in mixed-phase clouds is initiated by a minute subset of the ambient aerosol population, called ice-nucleating particles (INPs). The knowledge about their atmospheric concentration, composition, and source in cloud-relevant environments is still limited. During the 2017 joint INUIT/CLACE (Ice Nuclei research UnIT/CLoud–Aerosol Characterization Experiment) field campaign, observations of INPs as well as of aerosol physical and chemical properties were performed, complemented by source region modeling. This aimed at investigating the nature and sources of INPs. The campaign took place at the High-Altitude Research Station Jungfraujoch (JFJ), a location where mixed-phase clouds frequently occur. Due to its altitude of 3580 m a.s.l., the station is usually located in the lower free troposphere, but it can also receive air masses from terrestrial and marine sources via long-range transport. INP concentrations were quasi-continuously detected with the Horizontal Ice Nucleation Chamber (HINC) under conditions representing the formation of mixed-phase clouds at −31 ∘C. The INP measurements were performed in parallel to aerosol measurements from two single-particle mass spectrometers, the Aircraft-based Laser ABlation Aerosol MAss Spectrometer (ALABAMA) and the laser ablation aerosol particle time-of-flight mass spectrometer (LAAPTOF). The chemical identity of INPs is inferred by correlating the time series of ion signals measured by the mass spectrometers with the time series of INP measurements. Moreover, our results are complemented by the direct analysis of ice particle residuals (IPRs) by using an ice-selective inlet (Ice-CVI) coupled with the ALABAMA. Mineral dust particles and aged sea spray particles showed the highest correlations with the INP time series. Their role as INPs is further supported by source emission sensitivity analysis using atmospheric transport modeling, which confirmed that air masses were advected from the Sahara and marine environments during times of elevated INP concentrations and ice-active surface site densities. Indeed, the IPR analysis showed that, by number, mineral dust particles dominated the IPR composition (∼58 %), and biological and metallic particles are also found to a smaller extent (∼10 % each). Sea spray particles are also found as IPRs (17 %), and their fraction in the IPRs strongly varied according to the increased presence of small IPRs, which is likely due to an impact from secondary ice crystal formation. This study shows the capability of combining INP concentration measurements with chemical characterization of aerosol particles using single-particle mass spectrometry, source region modeling, and analysis of ice residuals in an environment directly relevant for mixed-phase cloud formation.</p