Simulation of braided river elevation model time series with multiple-point statistics

Pirot, Guillaume; Straubhaar, Julien; Renard, Philippe

doi:10.1016/j.geomorph.2014.01.022

Cited by 34 publications

(41 citation statements)

References 40 publications

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“…The unknown error in the CRPS estimation may lead to the wrong choice of the best forecast. Although meteorological vocabulary is used, this situation can occur in other fields of geosciences too, for instance when conditional simulations are used to sample from a probability distribution and choose between competing techniques or settings (Emery and Lantuéjoul 2006;Pirot et al 2014;Yin et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Estimation of the Continuous Ranked Probability Score with Limited Information and Applications to Ensemble Weather Forecasts

Zamo

Naveau

2017

Math Geosci

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The continuous ranked probability score (CRPS) is a much used measure of performance for probabilistic forecasts of a scalar observation. It is a quadratic measure of the difference between the forecast cumulative distribution function (CDF) and the empirical CDF of the observation. Analytic formulations of the CRPS can be derived for most classical parametric distributions, and be used to assess the efficiency of different CRPS estimators. When the true forecast CDF is not fully known, but represented as an ensemble of values, the CRPS is estimated with some error. Thus, using the CRPS to compare parametric probabilistic forecasts with ensemble forecasts may be misleading due to the unknown error of the estimated CRPS for the ensemble. With simulated data, the impact of the type of the verified ensemble (a random sample or a set of quantiles) on the CRPS estimation is studied. Based on these simulations, recommendations are issued to choose the most accurate CRPS estimator according to the type of ensemble. The interest of these recommendations is illustrated with real ensemble weather forecasts. Also, relationships between several estimators of the CRPS are demonstrated and used to explain the differences of accuracy between the estimators.

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Section: Introductionmentioning

confidence: 99%

Estimation of the Continuous Ranked Probability Score with Limited Information and Applications to Ensemble Weather Forecasts

Zamo

Naveau

2017

Math Geosci

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“…The successive topographies are simulated conditionally to the previous state with the Direct Sampling (DS) Multiple-Point Statistics (MPS) algorithm (Mariethoz et al, 2010) following the method developed by Pirot et al (2014). The same DS parameters presented in Pirot et al (2014) are used here.…”

Section: Pseudo Genetic Aglorithmmentioning

confidence: 99%

“…The same DS parameters presented in Pirot et al (2014) are used here. The training data set is composed of successive Digital Elevation Models of an analog braided river, the Waimakariri River, New Zealand, acquired by LIDAR at different time steps (Lane et al, 2003).…”

Section: Pseudo Genetic Aglorithmmentioning

confidence: 99%

Influence of conceptual model uncertainty on contaminant transport forecasting in braided river aquifers

Pirot

Renard

Huber

et al. 2015

Journal of Hydrology

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Keywords:Uncertainty Contaminant transport Modeling Braided river Aquifer Groundwater s u m m a r y Hydrogeologist are commonly confronted to field data scarcity. An interesting way to compensate this data paucity, is to use analog data. Then the questions of prediction accuracy and uncertainty assessment when using analog data shall be raised. These questions are investigated in the current paper in the case of contaminant transport forecasting in braided river aquifers. In using analog data from the literature, multiple unconditional geological realizations are produced following different geological conceptual models (Multi-Gaussian, Object-based, Pseudo-Genetic). These petrophysical realizations are tested in a contaminant transport problem based on the MADE-II tracer experiment dataset. The simulations show that reasonable contaminant transport predictions can be achieved using analog data. The initial concentration conditions and location regarding the conductivity heterogeneity field have a stronger influence on the plume behavior than the resulting equivalent permeability. The results also underline the necessity to include a wide variety of geological conceptual models and not to restrain parameter space exploration within each concept as long as no field data allows for conceptual model or parameter value falsification.

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“…Application of DS to real data is limited in literature at present (Jha et al 2013;Mariethoz and Renard 2010;Meerschman et al 2014;Pirot et al 2014) and developmental advancements are being published: bunch-pasting DS (Rezaee et al 2013); and fast DS (Abdollahifard and Faez 2014). The work presented here explores the use of…”

Section: Mps Geophysics and Groundwater Modellingmentioning

confidence: 99%

Integrating aerial geophysical data in multiple-point statistics simulations to assist groundwater flow models

et al. 2015

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The process of accounting for heterogeneity has made significant advances in statistical research, primarily in the framework of stochastic analysis and the development of multiple-point statistics (MPS). Among MPS techniques, the direct sampling (DS) method is tested to determine its ability to delineate heterogeneity from aerial magnetics data in a regional sandstone aquifer intruded by low-permeability volcanic dykes in Northern Ireland, UK. The use of two two-dimensional bivariate training images aids in creating spatial probability distributions of heterogeneities of hydrogeological interest, despite relatively 'noisy' magnetics data (i.e. including hydrogeologically irrelevant urban noise and regional geologic effects). These distributions are incorporated into a hierarchy system where previously published density function and upscaling methods are applied to derive regional distributions of equivalent hydraulic conductivity tensor K. Several K models, as determined by several stochastic realisations of MPS dyke locations, are computed within groundwater flow models and evaluated by comparing modelled heads with field observations. Results show a significant improvement in model calibration when compared to a simplistic homogeneous and isotropic aquifer model that does not account for the dyke occurrence evidenced by airborne magnetic data. The best model is obtained when normal and reverse polarity dykes are computed separately within MPS simulations and when a probability threshold of 0.7 is applied. The presented stochastic approach also provides improvement when compared to a previously published deterministic anisotropic model based on the unprocessed (i.e. noisy) airborne magnetics. This demonstrates the potential of coupling MPS to airborne geophysical data for regional groundwater modelling.

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Simulation of braided river elevation model time series with multiple-point statistics

Cited by 34 publications

References 40 publications

Estimation of the Continuous Ranked Probability Score with Limited Information and Applications to Ensemble Weather Forecasts

Estimation of the Continuous Ranked Probability Score with Limited Information and Applications to Ensemble Weather Forecasts

Influence of conceptual model uncertainty on contaminant transport forecasting in braided river aquifers

Integrating aerial geophysical data in multiple-point statistics simulations to assist groundwater flow models

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