The 2008 European e-Business Readiness Index

This report shows the scores of the 2008 e-business readiness index for European enterprises. The 2008 e-business readiness index, evaluated using data from the 2007 ICT enterprise survey carried out by Eurostat, is a useful mechanism for comparing e-business adoption and use by firms in the various European countries. The e-business readiness index measures the ICT adoption by enterprises using 6 indicators and measures ICT use by enterprises using another 6 indicators. The report describes the 12 benchmark indicators and the data coverage. The index obtained with the 2007 data is compared with the index calculated from previous years. The trends of the benchmark indicators are analysed and the robustness of the index scores among countries is tested to assess the significance of country rankings.JRC.G.9-Econometrics and applied statistic

Characterization of process-oriented hydrologic model behavior with temporal sensitivity analysis for flash floods in Mediterranean catchments

This paper presents a detailed analysis of 10 flash flood events in the Mediterranean region using the distributed hydrological model MARINE. Characterizing catchment response during flash flood events may provide new and valuable insight into the dynamics involved for extreme catchment response and their dependency on physiographic properties and flood severity. The main objective of this study is to analyze flash-flood-dedicated hydrologic model sensitivity with a new approach in hydrology, allowing model outputs variance decomposition for temporal patterns of parameter sensitivity analysis. Such approaches enable ranking of uncertainty sources for nonlinear and nonmonotonic mappings with a low computational cost. Hydrologic model and sensitivity analysis are used as learning tools on a large flash flood dataset. With Nash performances above 0.73 on average for this extended set of 10 validation events, the five sensitive parameters of MARINE process-oriented distributed model are analyzed. This contribution shows that soil depth explains more than 80% of model output variance when most hydrographs are peaking. Moreover, the lateral subsurface transfer is responsible for 80% of model variance for some catchment-flood events’ hydrographs during slow-declining limbs. The unexplained variance of model output representing interactions between parameters reveals to be very low during modeled flood peaks and informs that model parsimonious parameterization is appropriate to tackle the problem of flash floods. Interactions observed after model initialization or rainfall intensity peaks incite to improve water partition representation between flow components and initialization itself. This paper gives a practical framework for application of this method to other models, landscapes and climatic conditions, potentially helping to improve processes understanding and representation

The 2006 European e-Business Readiness Index

Abstract: This report is a methodological analysis on the composite index of the information and communication technology (ICT) adoption and use by enterprises in the Europe. Efficient adoption and use of ICT is a key factor to help European enterprises to raise their productivity and competi-tiveness. The 2006 European E-Business Readiness Index, evaluated using data from the 2005 Euro-pean enterprise survey of ICT use and e-commerce by Eurostat, is a useful mechanism for compar-ing e-business adoption and use by firms in the various European countries by sector, size and coun-try. European E-business Readiness Index measures by 6 components the ICT adoption and by 6 components the ICT use. Report describes basic indicators and data coverage. General composite indicator results of 2005 data are compared with results from earlier years. Analyses include prob-ability density estimates for scores, robustness analysis, and correlation and principal component analysis. Data quality and normalisation methodology are discussed and proposals for future devel-opment of the index are presented. Total of 64 pages, with 17 Tables and 41 Figures. Further information: http://ec.europa.eu/enterprise/ict/policy/ebi/index_en.htm) Keywords: ICT, e-business, adoption, composite indicators, eEurope2005, i2010JRC.G.9-Econometrics and statistical support to antifrau

Sensitivity analysis and parameter estimation for distributed hydrological modeling: potential of variational methods

Variational methods are widely used for the analysis and control of computationally intensive spatially distributed systems. In particular, the adjoint state method enables a very efficient calculation of the derivatives of an objective function (response function to be analysed or cost function to be optimised) with respect to model inputs. In this contribution, it is shown that the potential of variational methods for distributed catchment scale hydrology should be considered. A distributed flash flood model, coupling kinematic wave overland flow and Green Ampt infiltration, is applied to a small catchment of the Thoré basin and used as a relatively simple (synthetic observations) but didactic application case. It is shown that forward and adjoint sensitivity analysis provide a local but extensive insight on the relation between the assigned model parameters and the simulated hydrological response. Spatially distributed parameter sensitivities can be obtained for a very modest calculation effort (~6 times the computing time of a single model run) and the singular value decomposition (SVD) of the Jacobian matrix provides an interesting perspective for the analysis of the rainfall-runoff relation. For the estimation of model parameters, adjoint-based derivatives were found exceedingly efficient in driving a bound-constrained quasi-Newton algorithm. The reference parameter set is retrieved independently from the optimization initial condition when the very common dimension reduction strategy (i.e. scalar multipliers) is adopted. Furthermore, the sensitivity analysis results suggest that most of the variability in this high-dimensional parameter space can be captured with a few orthogonal directions. A parametrization based on the SVD leading singular vectors was found very promising but should be combined with another regularization strategy in order to prevent overfitting

Global Sensitivity Analysis: An Approach Based on the Contribution to the Sample Mean Plot

The contribution to the sample mean plot, originally proposed by Sinclair (1993), is revived and further developed as practical tool for global sensitivity analysis. The potentials of this simple and versatile graphical tool are discussed. Beyond the qualitative assessment provided by this approach, a statistical test is proposed for sensitivity analysis. A case study that simulates the transport of radionu- clides through the geosphere from an underground disposal vault containing nuclear waste (OECD 1993) is considered as a benchmark. The new approach is tested against a very efficient sensitivity analysis method based on state dependent parameter meta-modelling (Ratto et al. 2007).JRC.G.9-Econometrics and statistical support to antifrau

Sensitivity Analysis and Parameter Estimation for Distributed Hydrological Modeling: Potential of Variational Methods

Variational methods are widely used for the analysis and control of computationally intensive spatially distributed systems. In particular, the adjoint state method enables a very efficient calculation of the derivatives of an objective function (response function to be analysed or cost function to be optimised) with respect to model inputs. In this contribution, it is shown that the potential of variational methods for distributed catchment scale hydrology should be considered. A distributed flash flood model, coupling kinematic wave overland flow and Green Ampt infiltration, is applied to a small catchment of the Thor´e basin and used as a relatively simple (synthetic observations) but didactic application case. It is shown that forward and adjoint sensitivity analysis provide a local but extensive insight on the relation between the assigned model parameters and the simulated hydrological response. Spatially distributed parameter sensitivities can be obtained for a very modest calculation effort (6 times the computing time of a single model run) and the singular value decomposition (SVD) of the Jacobian matrix provides an interesting perspective for the analysis of the rainfall-runoff relation. For the estimation of model parameters, adjoint-based derivatives were found exceedingly efficient in driving a bound-constrained quasi-Newton algorithm. The reference parameter set is retrieved independently from the optimization initial condition when the very common dimension reduction strategy (i.e. scalar multipliers) is adopted. Furthermore, the sensitivity analysis results suggest that most of the variability in this high-dimensional parameter space can be captured with a few orthogonal directions. A parametrization based on the SVD leading singular vectors was found very promising but should be combined with another regularization strategy in order to prevent overfitting.JRC.G.9-Econometrics and applied statistic

Analyse de Sensibilité et Estimation de Paramètres pour la Modélisation Hydrologique : Potentiel et Limitations des Méthodes Variationnelles - Sensitivity Analysis and Parameter Estimation for Hydrological Modelling: Potential and Limitations of Variational Methods

The rainfall-runoff transformation is characterized by the complexity of the involved processes and by the limited observability of the atmospheric forcing, catchment properties and hydrological response. It is therefore essential to understand, analyse and reduce the uncertainty inherent to hydrological modelling (sensitivity and uncertainty analysis, data assimilation). Variational methods are widely used in other scientific disciplines (ex. Meteorology, oceanography) facing the same challenges. In this work, they were applied to hydrological models characterised by different modelling paradigms (reductionist vs. systemic) and runoff generation mechanisms (infiltration-excess vs. saturation excess). The potential and limitations of variational methods for catchment hydrology are illustrated with MARINE from the Toulouse Fluids Mechanics Institute (IMFT) and two models (event based flood model and continuous water balance model) based on TOPMODEL concepts developed at the Laboratory of Environmental Hydrology (LTHE). Forward and adjoint sensitivity analysis provide a local but extensive insight of the relation between model inputs and prognostic variables. The gradient of a performance measure (characterising the misfit with observations), calculated with the adjoint model, efficiently drives a bound-constrained quasi-newton optimization algorithm for the estimation of model parameters. The results obtained are very encouraging and plead for an extensive use of the variational approach to understand and corroborate the processes described in hydrological models but also estimate the model control variables (calibration of model parameters and state estimation using data assimilation).JRC.G.9-Econometrics and statistical support to antifrau

Analyse de sensibilité et estimation de paramètres pour la modélisation hydrologique : potentiel et limitations des méthodes variationnelles

The rainfall-runoff transformation is characterized by the complexity of the involved processes and by the limited observability of the atmospheric forcing, catchment properties and hydrological response. It is therefore essential to understand, analyse and reduce the uncertainty inherent to hydrological modelling (sensitivity and uncertainty analysis, data assimilation). Variational methods are widely used in other scientific disciplines (ex. Meteorology, oceanography) facing the same challenges. In this work, they were applied to hydrological models characterised by different modelling paradigms (reductionist vs. systemic) and runoff generation mechanisms (infiltration-excess vs. saturation excess). The potential and limitations of variational methods for catchment hydrology are illustrated with MARINE from the Toulouse Fluids Mechanics Institute (IMFT) and two models (event based flood model and continuous water balance model) based on TOPMODEL concepts developed at the Laboratory of Environmental Hydrology (LTHE). Forward and adjoint sensitivity analysis provide a local but extensive insight of the relation between model inputs and prognostic variables. The gradient of a performance measure (characterising the misfit with observations), calculated with the adjoint model, efficiently drives a bound-constrained quasi-newton optimization algorithm for the estimation of model parameters. The results obtained are very encouraging and plead for an extensive use of the variational approach to understand and corroborate the processes described in hydrological models but also estimate the model control variables (calibration of model parameters and state estimation using data assimilation).Comme tout évènement géophysique, la transformation de la pluie en débit dans les rivières est caractérisée par la complexité des processus engagés et par l'observation partielle, parfois très limitée, de la réponse hydrologique du bassin versant ainsi que du forçage atmosphérique auquel il est soumis. Il est donc essentiel de comprendre, d'analyser et de réduire les incertitudes inhérentes à la modélisation hydrologique (analyse de sensibilité, assimilation de données, propagation d'incertitudes). Les méthodes variationnelles sont très largement employées au sein d'autres disciplines (ex. météorologie, océanographie ...) confrontés aux mêmes challenges. Dans le cadre de ce travail, nous avons appliqué ce type de méthodes à des modèles représentant deux types de fonctionnement des hydrosystèmes à l'échelle du bassin versant. Le potentiel et les limitations de l'approche variationnelle pour la modélisation hydrologique sont illustrés avec un modèle faisant du ruissellement par dépassement de la capacité d'infiltration le processus prépondérant pour la genèse des écoulements superficiels (MARINE) ainsi qu'avec un modèle basé sur le concept des zones contributives d'aire variable (TOPMODEL). L'analyse de sensibilité par linéarisation ou basée sur la méthode de l'état adjoint permet une analyse locale mais approfondie de la relation entre les facteurs d'entrée de la modélisation et les variables pronostiques du système. De plus, le gradient du critère d'ajustement aux observations calculé par le modèle adjoint permet guider de manière très efficace un algorithme de descente avec contraintes de bornes pour l'estimation des paramètres. Les résultats obtenus sont très encourageants et plaident pour une utilisation accrue de l'approche variationnelle afin d'aborder les problématiques clés que sont l'analyse de la physique décrite dans les modèles hydrologiques et l'estimation des variables de contrôle (calibration des paramètres et mise à jour de l'état par assimilation de données)

Analyse de sensibilité et estimation de paramètres pour la modélisation hydrologique : potentiel et limitations des méthodes variationnelles

The rainfall-runoff transformation is characterized by the complexity of the involved processes and by the limited observability of the atmospheric forcing, catchment properties and hydrological response. It is therefore essential to understand, analyse and reduce the uncertainty inherent to hydrological modelling (sensitivity and uncertainty analysis, data assimilation). Variational methods are widely used in other scientific disciplines (ex. Meteorology, oceanography) facing the same challenges. In this work, they were applied to hydrological models characterised by different modelling paradigms (reductionist vs. systemic) and runoff generation mechanisms (infiltration-excess vs. saturation excess). The potential and limitations of variational methods for catchment hydrology are illustrated with MARINE from the Toulouse Fluids Mechanics Institute (IMFT) and two models (event based flood model and continuous water balance model) based on TOPMODEL concepts developed at the Laboratory of Environmental Hydrology (LTHE). Forward and adjoint sensitivity analysis provide a local but extensive insight of the relation between model inputs and prognostic variables. The gradient of a performance measure (characterising the misfit with observations), calculated with the adjoint model, efficiently drives a bound-constrained quasi-newton optimization algorithm for the estimation of model parameters. The results obtained are very encouraging and plead for an extensive use of the variational approach to understand and corroborate the processes described in hydrological models but also estimate the model control variables (calibration of model parameters and state estimation using data assimilation).Comme tout évènement géophysique, la transformation de la pluie en débit dans les rivières est caractérisée par la complexité des processus engagés et par l'observation partielle, parfois très limitée, de la réponse hydrologique du bassin versant ainsi que du forçage atmosphérique auquel il est soumis. Il est donc essentiel de comprendre, d'analyser et de réduire les incertitudes inhérentes à la modélisation hydrologique (analyse de sensibilité, assimilation de données, propagation d'incertitudes). Les méthodes variationnelles sont très largement employées au sein d'autres disciplines (ex. météorologie, océanographie ...) confrontés aux mêmes challenges. Dans le cadre de ce travail, nous avons appliqué ce type de méthodes à des modèles représentant deux types de fonctionnement des hydrosystèmes à l'échelle du bassin versant. Le potentiel et les limitations de l'approche variationnelle pour la modélisation hydrologique sont illustrés avec un modèle faisant du ruissellement par dépassement de la capacité d'infiltration le processus prépondérant pour la genèse des écoulements superficiels (MARINE) ainsi qu'avec un modèle basé sur le concept des zones contributives d'aire variable (TOPMODEL). L'analyse de sensibilité par linéarisation ou basée sur la méthode de l'état adjoint permet une analyse locale mais approfondie de la relation entre les facteurs d'entrée de la modélisation et les variables pronostiques du système. De plus, le gradient du critère d'ajustement aux observations calculé par le modèle adjoint permet guider de manière très efficace un algorithme de descente avec contraintes de bornes pour l'estimation des paramètres. Les résultats obtenus sont très encourageants et plaident pour une utilisation accrue de l'approche variationnelle afin d'aborder les problématiques clés que sont l'analyse de la physique décrite dans les modèles hydrologiques et l'estimation des variables de contrôle (calibration des paramètres et mise à jour de l'état par assimilation de données)

Analyse de sensibilité et estimation de paramètres pour la modélisation hydrologique : potentiel et limitations des méthodes variationnelles

The rainfall-runoff transformation is characterized by the complexity of the involved processes and by the limited observability of the atmospheric forcing, catchment properties and hydrological response. It is therefore essential to understand, analyse and reduce the uncertainty inherent to hydrological modelling (sensitivity and uncertainty analysis, data assimilation). Variational methods are widely used in other scientific disciplines (ex. Meteorology, oceanography) facing the same challenges. In this work, they were applied to hydrological models characterised by different modelling paradigms (reductionist vs. systemic) and runoff generation mechanisms (infiltration-excess vs. saturation excess). The potential and limitations of variational methods for catchment hydrology are illustrated with MARINE from the Toulouse Fluids Mechanics Institute (IMFT) and two models (event based flood model and continuous water balance model) based on TOPMODEL concepts developed at the Laboratory of Environmental Hydrology (LTHE). Forward and adjoint sensitivity analysis provide a local but extensive insight of the relation between model inputs and prognostic variables. The gradient of a performance measure (characterising the misfit with observations), calculated with the adjoint model, efficiently drives a bound-constrained quasi-newton optimization algorithm for the estimation of model parameters. The results obtained are very encouraging and plead for an extensive use of the variational approach to understand and corroborate the processes described in hydrological models but also estimate the model control variables (calibration of model parameters and state estimation using data assimilation).Comme tout évènement géophysique, la transformation de la pluie en débit dans les rivières est caractérisée par la complexité des processus engagés et par l'observation partielle, parfois très limitée, de la réponse hydrologique du bassin versant ainsi que du forçage atmosphérique auquel il est soumis. Il est donc essentiel de comprendre, d'analyser et de réduire les incertitudes inhérentes à la modélisation hydrologique (analyse de sensibilité, assimilation de données, propagation d'incertitudes). Les méthodes variationnelles sont très largement employées au sein d'autres disciplines (ex. météorologie, océanographie ...) confrontés aux mêmes challenges. Dans le cadre de ce travail, nous avons appliqué ce type de méthodes à des modèles représentant deux types de fonctionnement des hydrosystèmes à l'échelle du bassin versant. Le potentiel et les limitations de l'approche variationnelle pour la modélisation hydrologique sont illustrés avec un modèle faisant du ruissellement par dépassement de la capacité d'infiltration le processus prépondérant pour la genèse des écoulements superficiels (MARINE) ainsi qu'avec un modèle basé sur le concept des zones contributives d'aire variable (TOPMODEL). L'analyse de sensibilité par linéarisation ou basée sur la méthode de l'état adjoint permet une analyse locale mais approfondie de la relation entre les facteurs d'entrée de la modélisation et les variables pronostiques du système. De plus, le gradient du critère d'ajustement aux observations calculé par le modèle adjoint permet guider de manière très efficace un algorithme de descente avec contraintes de bornes pour l'estimation des paramètres. Les résultats obtenus sont très encourageants et plaident pour une utilisation accrue de l'approche variationnelle afin d'aborder les problématiques clés que sont l'analyse de la physique décrite dans les modèles hydrologiques et l'estimation des variables de contrôle (calibration des paramètres et mise à jour de l'état par assimilation de données)