On the asymptotic behavior of flood peak distributions – theoretical results

International audienceThis paper presents some analytical results and numerical illustrations on the asymptotic properties of flood peak distributions obtained through derived flood frequency approaches. It confirms and extends the results of previous works: i.e. the shape of the flood peak distributions are asymptotically controlled by the rainfall statistical properties, given limited and reasonable assumptions concerning the rainfall-runoff process. This previous result is partial so far: only two types of rainfall intensity distributions have been considered (extreme value distributions of types I and II), and the impact of the rainfall spatial heterogeneity has not been studied. From a practical point of view, it provides a general framework for analysis of the outcomes of previous works based on derived flood frequency approaches and leads to some proposals for the estimation of very large return-period flood quantiles. This paper, focussed on asymptotic distribution properties, does not propose any new approach for the extrapolation of flood frequency distribution to estimate intermediate return period flood quantiles. Nevertheless, the large distance between frequent flood peak values and the asymptotic values as well as the simulations conducted in this paper help quantifying the ill condition of the problem of flood frequency distribution extrapolation: it illustrates how large the range of possibilities for the shapes of flood peak distributions is

Over-parameterisation, a major obstacle to the use of artificial neural networks in hydrology?

International audienceRecently Feed-Forward Artificial Neural Networks (FNN) have been gaining popularity for stream flow forecasting. However, despite the promising results presented in recent papers, their use is questionable. In theory, their "universal approximator? property guarantees that, if a sufficient number of neurons is selected, good performance of the models for interpolation purposes can be achieved. But the choice of a more complex model does not ensure a better prediction. Models with many parameters have a high capacity to fit the noise and the particularities of the calibration dataset, at the cost of diminishing their generalisation capacity. In support of the principle of model parsimony, a model selection method based on the validation performance of the models, "traditionally" used in the context of conceptual rainfall-runoff modelling, was adapted to the choice of a FFN structure. This method was applied to two different case studies: river flow prediction based on knowledge of upstream flows, and rainfall-runoff modelling. The predictive powers of the neural networks selected are compared to the results obtained with a linear model and a conceptual model (GR4j). In both case studies, the method leads to the selection of neural network structures with a limited number of neurons in the hidden layer (two or three). Moreover, the validation results of the selected FNN and of the linear model are very close. The conceptual model, specifically dedicated to rainfall-runoff modelling, appears to outperform the other two approaches. These conclusions, drawn on specific case studies using a particular evaluation method, add to the debate on the usefulness of Artificial Neural Networks in hydrology. Keywords: forecasting; stream-flow; rainfall-runoff; Artificial Neural Network

Testing of aircraft passenger seat cushion materials. Full scale, test description and results, volume 1

Eight different seat cushion configurations were subjected to full-scale burn tests. Each cushion configuration was tested twice for a total of sixteen tests. Two different fire sources were used. They consisted of one liter of Jet A fuel for eight tests and a radiant energy source with propane flame for eight tests. Both fire sources were ignited by a propane flame. During each test, data were recorded for smoke density, cushion temperatures, radiant heat flux, animal response to combustion products, rate of weight loss of test specimens, cabin temperature, and for the type and content of gas within the cabin atmosphere. When compared to existing passenger aircraft seat cushions, the test specimens incorporating a fire barrier and those fabricated from advanced materials, using improved construction methods, exhibited significantly greater fire resistance

Some Global Aspects of Duality is String Theory

We explore some of the global aspects of duality transformations in String Theory and Field Theory. We analyze in some detail the equivalence of dual models corresponding to different topologies at the level of the partition function and in terms of the operator correspondence for abelian duality. We analyze the behavior of the cosmological constant under these transformations. We also explore several examples of non-abelian duality where the classical background interpretation can be maintained for the original and the dual theories. In particular we construct a non-abelian dual of $SL(2,R)$ which turns out to be a three-dimensional black holeComment: 31pp. One figure available upon request. CERN-TH-6991/6

Uncertainties on mean areal precipitation: assessment and impact on streamflow simulations

International audienceThis paper investigates the influence of mean areal rainfall estimation errors on a specific case study: the use of lumped conceptual rainfall-runoff models to simulate the flood hydrographs of three small to medium-sized catchments of the upper Loire river. This area (3200 km2) is densely covered by an operational network of stream and rain gauges. It is frequently exposed to flash floods and the improvement of flood forecasting models is then a crucial concern. Particular attention has been drawn to the development of an error model for rainfall estimation consistent with data in order to produce realistic streamflow simulation uncertainty ranges. The proposed error model combines geostatistical tools based on kriging and an autoregressive model to account for temporal dependence of errors. It has been calibrated and partly validated for hourly mean areal precipitation rates. Simulated error scenarios were propagated into two calibrated rainfall-runoff models using Monte Carlo simulations. Three catchments with areas ranging from 60 to 3200 km2 were tested to reveal any possible links between the sensitivity of the model outputs to rainfall estimation errors and the size of the catchment. The results show that a large part of the rainfall-runoff (RR) modelling errors can be explained by the uncertainties on rainfall estimates, especially in the case of smaller catchments. These errors are a major factor limiting accuracy and sharpness of rainfallrunoff simulations, and thus their operational use for flood forecasting

Assessment of the susceptibility of roads to flooding based on geographical information – test in a flash flood prone area (the Gard region, France)

International audienceIn flash flood prone areas, roads are often the first assets affected by inundations which make rescue operations difficult and represent a major threat to lives: almost half of the victims are car passengers trapped by floods. In the past years, the Gard region (France) road management services have realized an extensive inventory of the known road sub- mersions that occurred during the last 40 years. This inven- tory provided an unique opportunity to analyse the causes of road flooding in an area frequently affected by severe flash floods. It will be used to develop a road submersion suscep- tibility rating method, representing the first element of a road warning system.This paper presents the results of the analysis of this data set. A companion paper will show how the proposed road susceptibility rating method can be combined with dis- tributed rainfall-runoff simulations to provide accurate road submersion risk maps.The very low correlation between the various possible ex- planatory factors and the susceptibility to flooding measured by the number of past observed submersions implied the use of particular statistical analysis methods based on the general principals of the discriminant analysis.The analysis led to the definition of four susceptibility classes for river crossing road sections. Validation tests con- firmed that this classification is robust, at least in the con- sidered area. One major outcome of the analysis is that the susceptibility to flooding is rather linked to the location of the road sections than to the size of the river crossing structure (bridge or culvert)

Feynman Path Integral on the Noncommutative Plane

We formulate Feynman path integral on a non commutative plane using coherent states. The propagator for a free particle exhibits UV cut-off induced by the parameter of non commutativity.Comment: 7pages, latex 2e, no figures. Accepted for publication on J.Phys.

A path integral derivation of χy\chi_y-genus

The formula for the Hirzebruch $\chi_y$-genus of complex manifolds is a consequence of the Hirzebruch-Riemann-Roch formula. The classical index formulae for Todd genus, Euler number, and Signature correspond to the case when the complex variable $y=$ 0, -1, and 1 respectively. Here we give a {\it direct} derivation of this nice formula based on supersymmetric quantum mechanics.Comment: 5 page

Evolution of the Illegal Substances Market and Substance Users' Social Situation and Health during the COVID-19 Pandemic.

The outbreak of the COVID-19 pandemic and the measures taken for tackling it had the potential to lead to deep modifications in the supply of illegal drugs and to impact substance users' health and social situation. To investigate this, we used mixed methods, i.e., quantitative data collected with a brief questionnaire from substance users receiving opioid agonist treatment in a treatment centre in Switzerland (N = 49), and qualitative data obtained using semi-structured phone interviews among a sub-group of participants (N = 17). We repeated data collection twice over four weeks to investigate trends over time (N = 51 and 14 at wave 2). Findings consistently showed the limited impact of the COVID-19 outbreak on the illegal substance market. Over the two waves, the supply, price and purity of three main illegal substances did not significantly vary. Substance use was estimated as usual by most, trending toward a decrease. The impact of the pandemic on participants' social situation and health was appraised as low to medium. Nevertheless, a minority of participants reported higher impact and multivariate analyses showed a more important impact for those who were female, younger, and not using multiple substances. This process was implemented quickly and provided an understanding of the short-term impact of the pandemic on drug markets and users