Data-driven model order reduction using orthonormal vector fitting

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Reliability analysis of the NHx and NOy dry deposition fluxes calculated for 1992 with the DEADM model

Door middel van Monte Carlo sampling en simulatie wordt de betrouwbaarheid bepaald van de voorspellingen voor de jaargemiddelde droge NHx en NOy depositiefluxen, berekend met het depositiemodel DEADM. De berekeningen zijn uitgevoerd voor honderd 5 x 5 km gebieden in Nederland (6% van het totale gebied), op basis van NHx en NOy concentraties, oppervlakte gegevens en gepostuleerde onzekerheden in modelparameters c.q. inputs. Resultaten worden gepresenteerd in termen van verdelingen, betrouwbaarheidsintervallen en betrouwbaarheidsfactoren, zowel op de ruimtelijke schaal van 5 x 5 km gebieden als voor verzuringsgebieden en geheel Nederland. Voor de NHx depositie worden de resultaten vergeleken met de voorspellingen van het atmosferisch transportmodel OPS.By means of Monte Carlo Sampling and simulation the reliability is assessed of the predictions of yearly averaged dry NHx and NOy deposition fluxes, calculated with the deposition model DEADM. These calculations are performed for hundred 5 x 5 km receptor areas in the Netherlands (6% of the total area), based on NHx and NOy concentration data, surface characteristics and postulated uncertainties in model parameters and inputs. Results are presented in terms of probability distributions, confidence intervals and reliability factors, on the spatial scale of 5 x 5 km areas as well as for acidification areas and the national scale. The NHx results are compared with the predictions by the atmospheric transport model OPS.RIV

Rotated-Random-Scanning: een eenvoudige methode voor verzameling-theoretische modelkalibratie

Een eenvoudige methode wordt voorgesteld voor het kalibreren van modellen in slecht-gedefinieerde en informatie-arme situaties, die veelvuldig worden aangetroffen bij milieu-onderzoek. De methode volvoert een efficiente zoekaktie in de parameterruimte op basis van Monte Carlo trekkingen in combinatie met rotaties. Software is ontwikkeld, en verwante gevoeligheidsanalyse-technieken zijn voorgesteld ter reductie van het aantal te kalibreren parameters. De kalibratie-methode is gebruikt voor het kalibreren van de parameters in een bodemverzuringsmodel.A simple method is proposed for calibrating models in ill-defined and information-poor situations, which are frequently encountered in environmental applications. The method performs an efficient scan of the parameter space, based on Monte Carlo sampling in cobination with rotations. Software has been developed, and related tools have been proposed for sensitivity analysis to reduce the number of parameters to be calibrated. The calibration method is applied for calibrating the parameters of a soil-acidification model.NOP DGM/L

Reliability analysis of the NH concentrations and dry deposition flux calculated for 1992 with the OPS model

Door middel van Monte Carlo sampling en simulatie wordt de betrouwbaarheid bepaald van de voorspellingen voor de jaargemiddelde concentraties van NH3, NH4 aerosol en voor de jaartotale droge depositie van NHx, zoals deze berekend worden met het atmosferisch transportmodel OPS. De berekeningen zijn uitgevoerd voor honderd 5 x 5 km receptorgebieden in Nederland, op basis van NH3 emissiecijfers en gepostuleerde onzekerheden in modelparameters, zowel voor de situatie waarin de Nederlandse dierlijke emissie constant wordt gehouden als voor de situatie waarin deze emissie gevarieerd wordt. Resultaten worden gepresenteerd in termen van verdelingen, betrouwbaarheidsintervallen en betrouwbaarheidsfactoren, zowel op de ruimtelijke schaal van 5 x 5 km gebieden als voor verzuringsgebieden en geheel Nederland.By means of Monte Carlo Sampling and simulation the reliability is assessed of the predictions of yearly averaged concentrations of NH3, NH4 aerosol and of the yearly total dry deposition of NHx, as calculated by the atmospheric transport model OPS. These calculations are performed for hundred 5 x 5 km receptor areas in the Netherlands, based on NH3 emission data and postulated uncertainties in model parameters. Both the situations in which the emission from manure is fixed and is varied are considered. Results are presented in terms of probability distributions, confidence intervals and reliability factors, on the spatial scale of 5 x 5 km areas as well as for acidification areas and the national scale.RIV

Rotated-Random-Scanning: een eenvoudige methode voor verzameling-theoretische modelkalibratie

A simple method is proposed for calibrating models in ill-defined and information-poor situations, which are frequently encountered in environmental applications. The method performs an efficient scan of the parameter space, based on Monte Carlo sampling in cobination with rotations. Software has been developed, and related tools have been proposed for sensitivity analysis to reduce the number of parameters to be calibrated. The calibration method is applied for calibrating the parameters of a soil-acidification model.Een eenvoudige methode wordt voorgesteld voor het kalibreren van modellen in slecht-gedefinieerde en informatie-arme situaties, die veelvuldig worden aangetroffen bij milieu-onderzoek. De methode volvoert een efficiente zoekaktie in de parameterruimte op basis van Monte Carlo trekkingen in combinatie met rotaties. Software is ontwikkeld, en verwante gevoeligheidsanalyse-technieken zijn voorgesteld ter reductie van het aantal te kalibreren parameters. De kalibratie-methode is gebruikt voor het kalibreren van de parameters in een bodemverzuringsmodel

The role of sensitivity analysis and identifiability analysis in model calibration

Abstract niet beschikbaarModel calibration is usually an important part of the modelling process. A well structured approach of this activity, supported by general guidelines and techniques, will be especially beneficial of practical applications. Particularly the study of the sensitivity and the identifiability of the parameters (e.g. model coeffients, initial conditions) has to be a relevant part of model calibration. Such a study can reveal potential problems already during the early stages of the model calibration process, and can offer useful suggestions to prevent their occurrence. It will also be useful in post-calibration studies, e.g. when analysing the problems of unsuccessful calibration runs. Several simple methods are suggested for performing these analysis for a general class of calibration problems. The advantages and disadvantages of these methodes are briefly discussed. In particular attention is given to the problem of local versus global analyses in the parameter space.Stuurgroep Verzurin

Model calibration for regionalisation studies. Two methods to estimate distribution functions of model parameters, based on Monte-Carlo sampling

Abstract niet beschikbaarIn this report two techniques for regional calibration of mathematical models are discussed. Regional calibration is concerned with rescaling the model from a local (site) level to a regional level. This is typically done by assigning probability distributions to the unknown parameters, which reflect their (regional) spatial variability in an adequate way. Due to insufficient availability of data on the local level, the calibration of the parameters is performed on the regional level by matching the (simulated) distribution of the model outputs with the distribution of the measurement data. The discussed techniques, Bin Filling (BF) and Weighted Frequency Matching, are based on Monte Carlo sampling and simulation in combination with a reweighing of the sampled values to accomplish an optimal match between the distributions of the model results and the measurement data. The characteristic features of the presented techniques are discussed and their utility is indicated. In addition some guidelines are presented for an appropriate use of the methods which have been implemented aas software for general use.Stuurgroep Verzuring (in het kader van het Additioneel Programma Verzuring 3-de fase

UNCSAM 1.1: Een Software pakket voor gevoeligheids- en onzekerheids- analyse. Gebruikershandleiding

Abstract niet beschikbaarSensitivity and uncertainty analysis are generally recognized as important and indispensable parts of the modelling process. The easy availability of tools for performing these analyses contributes substantially to a reliable and efficient development, assessment and application of mathematical models. For this reason a comprehensive and flexible software package UNCSAM has been developed at the RIVM for performing sensitivity and uncertainty analysis on a large variety of models. UNCSAM combines a Monte Carlo based approach (sampling and simulation) with regression- and correlation analysis, to obtain a clear picture of the sensitivities and uncertainties and their main contributors. The package is developed in ANSI standard Fortran 77, embedded in an ANSI-C shell for dynamic memory allocation, and can be installed on a variety of devices. The manual describes the scope, installation and use of UNSCAM, release version 1.1.RIV