scholarly journals Smarticles: A Method for Identifying and Correcting Instability and Error Caused by Explicit Integration Techniques in Physically Based Simulations

2014 ◽  
Author(s):  
Susan Aileen Marano
2007 ◽  
Vol 135 (8) ◽  
pp. 2897-2913 ◽  
Author(s):  
J. B. Klemp ◽  
W. C. Skamarock ◽  
J. Dudhia

Abstract Historically, time-split schemes for numerically integrating the nonhydrostatic compressible equations of motion have not formally conserved mass and other first-order flux quantities. In this paper, split-explicit integration techniques are developed that numerically conserve these properties by integrating prognostic equations for conserved quantities represented in flux form. These procedures are presented for both terrain-following height and hydrostatic pressure (mass) vertical coordinates, two potentially attractive frameworks for which the equation sets and integration techniques differ significantly. For each set of equations, the linear dispersion equation for acoustic/gravity waves is derived and analyzed to determine which terms must be solved in the small (acoustic) time steps and how these terms are represented in the time integration to achieve stability. Efficient techniques for including numerical filters for acoustic and external modes are also presented. Simulations for several idealized test cases in both the height and mass coordinates are presented to demonstrate that these integration techniques appear robust over a wide range of scales, from subcloud to synoptic.


1971 ◽  
Vol 2 (3) ◽  
pp. 146-166 ◽  
Author(s):  
DAVID A. WOOLHISER

Physically-based, deterministic models, are considered in this paper. Physically-based, in that the models have a theoretical structure based primarily on the laws of conservation of mass, energy, or momentum; deterministic in the sense that when initial and boundary conditions and inputs are specified, the output is known with certainty. This type of model attempts to describe the structure of a particular hydrologic process and is therefore helpful in predicting what will happen when some change occurs in the system.


2019 ◽  
Vol 19 (11) ◽  
pp. 2477-2495
Author(s):  
Ronda Strauch ◽  
Erkan Istanbulluoglu ◽  
Jon Riedel

Abstract. We developed a new approach for mapping landslide hazards by combining probabilities of landslide impacts derived from a data-driven statistical approach and a physically based model of shallow landsliding. Our statistical approach integrates the influence of seven site attributes (SAs) on observed landslides using a frequency ratio (FR) method. Influential attributes and resulting susceptibility maps depend on the observations of landslides considered: all types of landslides, debris avalanches only, or source areas of debris avalanches. These observational datasets reflect the detection of different landslide processes or components, which relate to different landslide-inducing factors. For each landslide dataset, a stability index (SI) is calculated as a multiplicative result of the frequency ratios for all attributes and is mapped across our study domain in the North Cascades National Park Complex (NOCA), Washington, USA. A continuous function is developed to relate local SI values to landslide probability based on a ratio of landslide and non-landslide grid cells. The empirical model probability derived from the debris avalanche source area dataset is combined probabilistically with a previously developed physically based probabilistic model. A two-dimensional binning method employs empirical and physically based probabilities as indices and calculates a joint probability of landsliding at the intersections of probability bins. A ratio of the joint probability and the physically based model bin probability is used as a weight to adjust the original physically based probability at each grid cell given empirical evidence. The resulting integrated probability of landslide initiation hazard includes mechanisms not captured by the infinite-slope stability model alone. Improvements in distinguishing potentially unstable areas with the proposed integrated model are statistically quantified. We provide multiple landslide hazard maps that land managers can use for planning and decision-making, as well as for educating the public about hazards from landslides in this remote high-relief terrain.


1998 ◽  
Vol 26 ◽  
pp. 174-178 ◽  
Author(s):  
Peter Gauer

A physically based numerical model of drifting and blowing snow in three-dimensional terrain is developed. The model includes snow transport by saltation and suspension. As an example, a numerical simulation for an Alpine ridge is presented and compared with field measurements.


2021 ◽  
pp. 126268
Author(s):  
Menberu B. Meles ◽  
Dave C. Goodrich ◽  
Hoshin V. Gupta ◽  
I. Shea Burns ◽  
Carl L. Unkrich ◽  
...  

Geosciences ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 35
Author(s):  
Luca Schilirò ◽  
José Cepeda ◽  
Graziella Devoli ◽  
Luca Piciullo

In Norway, shallow landslides are generally triggered by intense rainfall and/or snowmelt events. However, the interaction of hydrometeorological processes (e.g., precipitation and snowmelt) acting at different time scales, and the local variations of the terrain conditions (e.g., thickness of the surficial cover) are complex and often unknown. With the aim of better defining the triggering conditions of shallow landslides at a regional scale we used the physically based model TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope stability) in an area located in upper Gudbrandsdalen valley in South-Eastern Norway. We performed numerical simulations to reconstruct two scenarios that triggered many landslides in the study area on 10 June 2011 and 22 May 2013. A large part of the work was dedicated to the parameterization of the numerical model. The initial soil-hydraulic conditions and the spatial variation of the surficial cover thickness have been evaluated applying different methods. To fully evaluate the accuracy of the model, ROC (Receiver Operating Characteristic) curves have been obtained comparing the safety factor maps with the source areas in the two periods of analysis. The results of the numerical simulations show the high susceptibility of the study area to the occurrence of shallow landslides and emphasize the importance of a proper model calibration for improving the reliability.


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