Distribution of the number of particles in the final state of hadron-nucleus collisions

Recently, Liou, Mueller and Munier have argued that proton-nucleus collisions at the LHC may give access to the full statistics of the event-by-event fluctuations of the gluon density in the proton. Indeed, the number of particles produced in an event in rapidity slices in the fragmentation region of the proton may, under some well-defined assumptions, be directly related to the number of gluons which have a transverse momentum larger than the nuclear saturation scale present in the proton at the time of the interaction with the nucleus. A first calculation of the probability distribution of the number of gluons in a hadron was performed, using the color dipole model. In this talk, we review this proposal, and present preliminary numerical calculations which support the analytical results obtained so far.Comment: 6 pages, 2 figures. Talk presented at DIS 201

LINEAR APPROXIMATION OF OPEN-CHANNEL FLOW ROUTING WITH BACKWATER EFFECT

International audienceThis paper proposes a new model for linear flow routing in open-channels. The proposed model, called LBLR for Linear Backwater Lag and Route, is a first order with delay model that explicitly takes into account two parameters which are usually neglected: 1) the downstream boundary condition and 2) the nonuniform flow conditions, both of which are shown to have a strong influence on the flow dynamics. The model parameters are obtained analytically from the pool characteristics (geometry, friction, discharge and downstream boundary condition). A frequency domain approach is used to compute the frequency response of the linearized Saint-Venant equations. This model is then approximated by a first order plus delay model using the moment matching method. The proposed model is shown to perform better than existing models when the flow is affected by backwater and/or by different downstream boundary conditions from the one corresponding to uniform flow

Implementation and sensitivity analysis of the Dam-Reservoir OPeration model (DROP v1.0) over Spain

The prediction of water resource evolution is considered to be a major challenge for the coming century, particularly in the context of climate change and increasing demographic pressure. Water resources are directly linked to the continental water cycle, and the main processes modulating changes can be represented by global hydrological models. However, anthropogenic impacts on water resources, and in particular the effects of dams-reservoirs on river flows, are still poorly known and generally neglected in coupled land surface–river routing models. This paper presents a parameterized reservoir model, DROP (Dam-Reservoir OPeration), based on Hanasaki's scheme to compute monthly releases given inflows, water demands and the management purpose. With its significantly anthropized river basins, Spain has been chosen as a study case for which simulated outflows and water storage variations are evaluated against in situ observations over the period 1979–2014. Using a default configuration of the reservoir model, results reveal its positive contribution in representing the seasonal cycle of discharge and storage variation, specifically for large-storage capacity irrigation reservoirs. Based on a bounded version of the Nash–Sutcliffe efficiency (NSE) index, called C2M, the overall outflow representation is improved by 43 % in the median. For irrigation reservoirs, the improvement rate reaches 80 %. A comprehensive sensitivity analysis of DROP model parameters was conducted based on the performance of C2M on outflows and volumes using the Sobol method. The results show that the most influential parameter is the threshold coefficient describing the demand-controlled release level. The analysis also reveals the parameters that need to be focused on in order to improve river flow or reservoir water storage modeling by highlighting the difference in the individual effects of the parameters and their interactions depending on whether one focuses on outflows or volume mean seasonal patterns. The results of this generic reservoir scheme show promise for modeling present and future reservoir impacts on the continental hydrology within global land surface–river routing models.</p

Assessment of pluri-annual and decadal changes in terrestrial water storage predicted by global hydrological models in comparison with the GRACE satellite gravity mission

The GRACE (Gravity Recovery And Climate Experiment) satellite gravity mission enables global monitoring of the mass transport within the Earth's system, leading to unprecedented advances in our understanding of the global water cycle in a changing climate. This study focuses on the quantification of changes in terrestrial water storage with respect to the temporal average based on an ensemble of GRACE solutions and two global hydrological models. Significant changes in terrestrial water storage are detected at pluri-annual and decadal timescales in GRACE satellite gravity data that are generally underestimated by global hydrological models though consistent with precipitation. The largest differences (more than 20 cm in equivalent water height) are observed in South America (Amazon, São Francisco and Paraná River basins) and tropical Africa (Congo, Zambezi and Okavango River basins). Smaller but significant (a few centimetres) differences are observed worldwide. While the origin of such differences is unknown, part of it is likely to be climate-related and at least partially due to inaccurate predictions of hydrological models. Pluri-annual to decadal changes in the terrestrial water cycle may indeed be overlooked in global hydrological models due to inaccurate meteorological forcing (e.g. precipitation), unresolved groundwater processes, anthropogenic influences, changing vegetation cover and limited calibration/validation datasets. Significant differences between GRACE satellite measurements and hydrological model predictions have been identified, quantified and characterised in the present study. Efforts must be made to better understand the gap between methods at both pluri-annual and decadal timescales, which challenges the use of global hydrological models for the prediction of the evolution of water resources in changing climate conditions.</p

Implementation of a Differential Flatness Based Controller on an Open Channel Using a SCADA System

International audienceWith a population of more than 6 billion people, food production from agriculture must be raised to meet increasing demand. While irrigated agriculture provides 40% of the total food production, it represents 80% of the freshwater consumption worldwide. In summer and drought conditions, efficient management of scarce water resources becomes crucial. The majority of irrigation canals are managed manually, however, with large water losses leading to low water efficiency. This article focuses on the development of algorithms that could contribute to more efficient management of irrigation canals that convey water from a source, generally a dam or reservoir located upstream, to water users. We also describe the implementation of an algorithm for real-time irrigation operation using a supervision, control, and data acquisition (SCADA) system with an automatic centralized controller. Irrigation canals can be viewed and modeled as delay systems since it takes time for the water released at the upstream end to reach the user located downstream. We thus present an open-loop controller that can deliver water at a given location at a specified time. The development of this controller requires a method for inverting the equations that describe the dynamics of the canal in order to parameterize the controlled input as a function of the desired output. The Saint-Venant equations [1] are widely used to describe water discharge in a canal. Since these equations are not easy to invert, we consider a simplified model, called the Hayami model. We then use differential flatness to invert the dynamics of the system and to design an open-loop controller

Effect of selection on ancestry: an exactly soluble case and its phenomenological generalization

We consider a family of models describing the evolution under selection of a population whose dynamics can be related to the propagation of noisy traveling waves. For one particular model, that we shall call the exponential model, the properties of the traveling wave front can be calculated exactly, as well as the statistics of the genealogy of the population. One striking result is that, for this particular model, the genealogical trees have the same statistics as the trees of replicas in the Parisi mean-field theory of spin glasses. We also find that in the exponential model, the coalescence times along these trees grow like the logarithm of the population size. A phenomenological picture of the propagation of wave fronts that we introduced in a previous work, as well as our numerical data, suggest that these statistics remain valid for a larger class of models, while the coalescence times grow like the cube of the logarithm of the population size.Comment: 26 page

Remote Sensing Data Assimilation with a Chained Hydrologic-hydraulic Model for Flood Forecasting

A chained hydrologic-hydraulic model is implemented using predicted runoff from a large-scale hydrologic model (namely ISBA-CTRIP) as inputs to local hydrodynamic models (TELEMAC-2D) to issue forecasts of water level and flood extent. The uncertainties in the hydrological forcing and in friction parameters are reduced by an Ensemble Kalman Filter that jointly assimilates in-situ water levels and flood extent maps derived from remote sensing observations. The data assimilation framework is cycled in a real-time forecasting configuration. A cycle consists of a reanalysis and a forecast phase. Over the analysis, observations up to the present are assimilated. An ensemble is then initialized from the last analyzed states and issued forecasts for next 36 hr. Three strategies of forcing data for this forecast are investigated: (i) using CTRIP runoff for reanalysis and forecast, (ii) using observed discharge for analysis, then CTRIP runoff for forecast and (iii) using observed discharge for reanalysis and keep a persistent discharge value for forecast. It was shown that the data assimilation strategy provides a reliable reanalysis in hindcast mode. The combination of observed discharge and CTRIP runoff provides the most accurate results. For all strategies, the quality of the forecast decreases as the lead time increases. When the errors in CTRIP forcing are non-stationary, the forecast capability may be reduced. This work demonstrates that the forcing provided by a hydrologic model, while imperfect, can be efficiently used as input to a hydraulic model to issue reanalysis and forecasts, thanks to the assimilation of in-situ and remote sensing observations.Comment: 13 pages, 14 figures. Submitted to the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensin

Quasi-stationary regime of a branching random walk in presence of an absorbing wall

A branching random walk in presence of an absorbing wall moving at a constant velocity $v$ undergoes a phase transition as the velocity $v$ of the wall varies. Below the critical velocity $v_c$, the population has a non-zero survival probability and when the population survives its size grows exponentially. We investigate the histories of the population conditioned on having a single survivor at some final time $T$. We study the quasi-stationary regime for $v<v_c$ when $T$ is large. To do so, one can construct a modified stochastic process which is equivalent to the original process conditioned on having a single survivor at final time $T$. We then use this construction to show that the properties of the quasi-stationary regime are universal when $v\to v_c$. We also solve exactly a simple version of the problem, the exponential model, for which the study of the quasi-stationary regime can be reduced to the analysis of a single one-dimensional map.Comment: 2 figures, minor corrections, one reference adde