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Model Behaviour (model + behaviour)
Selected AbstractsThe behaviour of soil process models of ammonia volatilization at contrasting spatial scalesEUROPEAN JOURNAL OF SOIL SCIENCE, Issue 6 2008R. Corstanje Summary Process models are commonly used in soil science to obtain predictions at a spatial scale that is different from the scale at which the model was developed, or the scale at which information on model inputs is available. When this happens, the model and its inputs require aggregation or disaggregation to the application scale, and this is a complex problem. Furthermore, the validity of the aggregated model predictions depends on whether the model describes the key processes that determine the process outcome at the target scale. Different models may therefore be required at different spatial scales. In this paper we develop a diagnostic framework which allows us to judge whether a model is appropriate for use at one or more spatial scales both with respect to the prediction of variations at those scale and in the requirement for disaggregation of the inputs. We show that spatially nested analysis of the covariance of predictions with measured process outcomes is an efficient way to do this. This is applied to models of the processes that lead to ammonia volatilization from soil after the application of urea. We identify the component correlations at different scales of a nested scheme as the diagnostic with which to evaluate model behaviour. These correlations show how well the model emulates components of spatial variation of the target process at the scales of the sampling scheme. Aggregate correlations were identified as the most pertinent to evaluate models for prediction at particular scales since they measure how well aggregated predictions at some scale correlate with aggregated values of the measured outcome. There are two circumstances under which models are used to make predictions. In the first case only the model is used to predict, and the most useful diagnostic is the concordance aggregate correlation. In the second case model predictions are assimilated with observations which should correct bias in the prediction, and errors in the variance; the aggregate correlations would be the most suitable diagnostic. [source] Wavelet analysis of the scale- and location-dependent correlation of modelled and measured nitrous oxide emissions from soilEUROPEAN JOURNAL OF SOIL SCIENCE, Issue 1 2005A. E. Milne Summary We used the wavelet transform to quantify the performance of models that predict the rate of emission of nitrous oxide (N2O) from soil. Emissions of N2O and other soil variables that influence emissions were measured on soil cores collected at 256 locations across arable land in Bedfordshire, England. Rate-limiting models of N2O emissions were constructed and fitted to the data by functional analysis. These models were then evaluated by wavelet variance and wavelet correlations, estimated from coefficients of the adapted maximal overlap discrete wavelet transform (AMODWT), of the fitted and measured emission rates. We estimated wavelet variances to assess whether the partition of the variance of modelled rates of N2O emission between scales reflected that of the data. Where the relative distribution of variance in the model is more skewed to coarser scales than is the case for the observation, for example, this indicates that the model predictions are too smooth spatially, and fail adequately to represent some of the variation at finer scales. Scale-dependent wavelet correlations between model and data were used to quantify the model performance at each scale, and in several cases to determine the scale at which the model description of the data broke down. We detected significant changes in correlation between modelled and predicted emissions at each spatial scale, showing that, at some scales, model performance was not uniform in space. This suggested that the influence of a soil variable on N2O emissions, important in one region but not in another, had been omitted from the model or modelled poorly. Change points usually occurred at field boundaries or where soil textural class changed. We show that wavelet analysis can be used to quantify aspects of model performance that other methods cannot. By evaluating model behaviour at several scales and positions wavelet analysis helps us to determine whether a model is suitable for a particular purpose. [source] Diagnostic evaluation of conceptual rainfall,runoff models using temporal clusteringHYDROLOGICAL PROCESSES, Issue 20 2010N. J. de Vos Abstract Given the structural shortcomings of conceptual rainfall,runoff models and the common use of time-invariant model parameters, these parameters can be expected to represent broader aspects of the rainfall,runoff relationship than merely the static catchment characteristics that they are commonly supposed to quantify. In this article, we relax the common assumption of time-invariance of parameters, and instead seek signature information about the dynamics of model behaviour and performance. We do this by using a temporal clustering approach to identify periods of hydrological similarity, allowing the model parameters to vary over the clusters found in this manner, and calibrating these parameters simultaneously. The diagnostic information inferred from these calibration results, based on the patterns in the parameter sets of the various clusters, is used to enhance the model structure. This approach shows how diagnostic model evaluation can be used to combine information from the data and the functioning of the hydrological model in a useful manner. Copyright © 2010 John Wiley & Sons, Ltd. [source] On the effects of triangulated terrain resolution on distributed hydrologic model responseHYDROLOGICAL PROCESSES, Issue 11 2005Enrique R. Vivoni Abstract Distributed hydrologic models based on triangulated irregular networks (TIN) provide a means for computational efficiency in small to large-scale watershed modelling through an adaptive, multiple resolution representation of complex basin topography. Despite previous research with TIN-based hydrology models, the effect of triangulated terrain resolution on basin hydrologic response has received surprisingly little attention. Evaluating the impact of adaptive gridding on hydrologic response is important for determining the level of detail required in a terrain model. In this study, we address the spatial sensitivity of the TIN-based Real-time Integrated Basin Simulator (tRIBS) in order to assess the variability in the basin-averaged and distributed hydrologic response (water balance, runoff mechanisms, surface saturation, groundwater dynamics) with respect to changes in topographic resolution. Prior to hydrologic simulations, we describe the generation of TIN models that effectively capture topographic and hydrographic variability from grid digital elevation models. In addition, we discuss the sampling methods and performance metrics utilized in the spatial aggregation of triangulated terrain models. For a 64 km2 catchment in northeastern Oklahoma, we conduct a multiple resolution validation experiment by utilizing the tRIBS model over a wide range of spatial aggregation levels. Hydrologic performance is assessed as a function of the terrain resolution, with the variability in basin response attributed to variations in the coupled surface,subsurface dynamics. In particular, resolving the near-stream, variable source area is found to be a key determinant of model behaviour as it controls the dynamic saturation pattern and its effect on rainfall partitioning. A relationship between the hydrologic sensitivity to resolution and the spatial aggregation of terrain attributes is presented as an effective means for selecting the model resolution. Finally, the study highlights the important effects of terrain resolution on distributed hydrologic model response and provides insight into the multiple resolution calibration and validation of TIN-based hydrology models. Copyright © 2005 John Wiley & Sons, Ltd. [source] Optimal use of high-resolution topographic data in flood inundation modelsHYDROLOGICAL PROCESSES, Issue 3 2003P. D. Bates Abstract In this paper we explore the optimum assimilation of high-resolution data into numerical models using the example of topographic data provision for flood inundation simulation. First, we explore problems with current assimilation methods in which numerical grids are generated independent of topography. These include possible loss of significant length scales of topographic information, poor representation of the original surface and data redundancy. These are resolved through the development of a processing chain consisting of: (i) assessment of significant length scales of variation in the input data sets; (ii) determination of significant points within the data set; (iii) translation of these into a conforming model discretization that preserves solution quality for a given numerical solver; and (iv) incorporation of otherwise redundant sub-grid data into the model in a computationally efficient manner. This processing chain is used to develop an optimal finite element discretization for a 12 km reach of the River Stour in Dorset, UK, for which a high-resolution topographic data set derived from airborne laser altimetry (LiDAR) was available. For this reach, three simulations of a 1 in 4 year flood event were conducted: a control simulation with a mesh developed independent of topography, a simulation with a topographically optimum mesh, and a further simulation with the topographically optimum mesh incorporating the sub-grid topographic data within a correction algorithm for dynamic wetting and drying in fixed grid models. The topographically optimum model is shown to represent better the ,raw' topographic data set and that differences between this surface and the control are hydraulically significant. Incorporation of sub-grid topographic data has a less marked impact than getting the explicit hydraulic calculation correct, but still leads to important differences in model behaviour. The paper highlights the need for better validation data capable of discriminating between these competing approaches and begins to indicate what the characteristics of such a data set should be. More generally, the techniques developed here should prove useful for any data set where the resolution exceeds that of the model in which it is to be used. Copyright © 2002 John Wiley & Sons, Ltd. [source] Non-local damage model based on displacement averagingINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 1 2005M. Jirásek Abstract Continuum damage models describe the changes of material stiffness and strength, caused by the evolution of defects, in the framework of continuum mechanics. In many materials, a fast evolution of defects leads to stress,strain laws with softening, which creates serious mathematical and numerical problems. To regularize the model behaviour, various generalized continuum theories have been proposed. Integral-type non-local damage models are often based on weighted spatial averaging of a strain-like quantity. This paper explores an alternative formulation with averaging of the displacement field. Damage is assumed to be driven by the symmetric gradient of the non-local displacements. It is demonstrated that an exact equivalence between strain and displacement averaging can be achieved only in an unbounded medium. Around physical boundaries of the analysed body, both formulations differ and the non-local displacement model generates spurious damage in the boundary layers. The paper shows that this undesirable effect can be suppressed by an appropriate adjustment of the non-local weight function. Alternatively, an implicit gradient formulation could be used. Issues of algorithmic implementation, computational efficiency and smoothness of the resolved stress fields are discussed. Copyright © 2005 John Wiley & Sons, Ltd. [source] Assimilation of radar-derived rain rates into the convective-scale model COSMO-DE at DWDTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 634 2008K. Stephan Abstract To improve very-short-range forecasts particularly in convective situations, a version of the COSMO-Model (formerly known as LM) which simulates deep convection explicitly (horizontal grid length: 2.8 km) has been developed and is now run operationally at DWD. This model uses a prognostic type of precipitation scheme accounting for the horizontal drift of falling hydrometeors. To initialise convective-scale events, the latent heat nudging (LHN) approach has been adopted for the assimilation of surface precipitation rates derived from radar reflectivity data. It is found that a conventional LHN scheme designed for larger-scale models with diagnostic treatment of precipitation does not perform well and leads to strong overestimation of precipitation when applied to the convective-scale model with a prognostic treatment of precipitation. As illustrated here, surface precipitation and vertically integrated latent heating are far less correlated horizontally and temporally in such a model than with diagnostic precipitation, and this implies a violation of the basic assumption of LHN. Several revisions to the LHN scheme have therefore been developed in view of the characteristic model behaviour so as to re-enhance the validity of the basic assumption and to reduce greatly the overestimation of precipitation during assimilation. With the revised scheme, the model is able to simulate the precipitation patterns in good agreement with radar observations during the assimilation and the first hours of the forecast. The scheme also has a positive impact on screen-level parameters and on the longer-term climatology of the model. Extending the temporal impact of the radar observations further into the free forecast will be the focus of future research. Copyright © 2008 Royal Meteorological Society [source] Diagnosis of climate models in terms of transient climate response and feedback response timeATMOSPHERIC SCIENCE LETTERS, Issue 1 2008David G. Andrews Abstract Climate models have traditionally been characterised by their climate sensitivity (equilibrium response to a doubling of CO2) and their ocean heat uptake. Together these determine a third property: the transient climate response to a linear increase in radiative forcing. A fourth property, the feedback response time is introduced here and shown to provide a complementary diagnostic of climate model behaviour. In particular, it demonstrates that the discrepancy between recent climate observations and the general circulation models in the ,IPCC ensemble' primarily arises because the models are undersampling the range of transient climate responses consistent with recent attributable greenhouse warming. Copyright © 2007 Royal Meteorological Society [source] Modelling of paste flows subject to liquid phase migrationINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 10 2007M. J. Patel Abstract Particulate pastes undergoing extrusion can exhibit differential velocities between the solid and liquid phases, termed liquid phase migration (LPM). This is observed experimentally but understanding and predictive capacity for paste and extruder design is limited. Most models for LPM feature one-dimensional analyses. Here, a two-dimensional finite element model based on soil mechanics approaches (modified Cam-Clay) was developed where the liquid and the solids skeleton are treated separately. Adaptive remeshing routines were developed to overcome the significant mesh distortion arising from the large strains inherent in extrusion. Material data to evaluate the model's behaviour were taken from the literature. The predictive capacity of the model is evaluated for different ram velocities and die entry angles (smooth walls). Results are compared with experimental findings in the literature and good qualitative agreement is found. Key results are plots of pressure contributions and extrudate liquid fraction against ram displacement, and maps of permeability, liquid velocity and voids ratio. Pore liquid pressure always dominates extrusion pressure. The relationship between extrusion geometry, ram speed and LPM is complex. Overall, for a given geometry, higher ram speeds give less migration. Pastes flowing into conical entry dies give different voids ratio distributions and do not feature static zones. Copyright © 2007 John Wiley & Sons, Ltd. [source] | |||||||||||||