scholarly journals A Modular, Non-Newtonian, Model, Library Framework (DebrisLib) for Post-Wildfire Flood Risk Management

2020 ◽  
Author(s):  
Ian E. Floyd ◽  
Alejandro Sanchez ◽  
Stanford Gibson ◽  
Gaurav Savant
Keyword(s):  
Shallow Water ◽  
Large Scale ◽  
Numerical Models ◽  
Geophysical Flows ◽  
Two Dimensional ◽  
Flow Conditions ◽  
Newtonian Flow ◽  
Flume Experiments ◽  
Model Framework ◽  
Newtonian Model

Abstract. Wildfires increase flow and sediment load through removal of vegetation, alteration of soils, decreasing infiltration, and production of ash commonly generating a wide variety of geophysical flows (i.e., hyperconcentrated flows, mudflows, debris flows, etc.). Numerical modellers have developed a variety of Non-Newtonian algorithms to simulate each of these processes, and therefore, it can be difficult to understand the assumptions and limitations in any given model or replicate work. This diversity in the processes and approach to non-Newtonian simulations makes a modular computation library approach advantageous. A computational library consolidates the algorithms for each process and discriminates between these processes and algorithms with quantitative non-dimensional thresholds. This work presents a flexible numerical library framework (DebrisLib) to simulate large-scale, post-wildfire, non-Newtonian geophysical flows using both kinematic wave and shallow-water models. DebrisLib is derived from a variety of non-Newtonian closure approaches that predict a range of non-Newtonian flow conditions. It is a modular code designed to operate with any Newtonian, shallow-water parent code architecture. This paper presents the non-Newtonian model framework and demonstrates its effectiveness by calling it from two very different modelling frameworks developed by the U.S. Army Corp of Engineers (USACE), specifically, within the one-dimensional and two-dimensional Hydrologic Engineering Centre River Analysis System (HEC-RAS) and two-dimensional Adaptive Hydraulics (AdH) numerical models. The development and linkage-architecture were verified and validated using two non-Newtonian flume experiments selected to represent a range of non-Newtonian flow conditions (i.e., hyperconcentrated flow, mudflow, debris flow) commonly associated with post-wildfire flooding.

Post-Wildfire Numerical Modeling for Flood Risk Management

2020 ◽  
Author(s):  
Ian Floyd ◽  
Stanford Gibson ◽  
Gaurav Savant ◽  
Alejandro Sanchez ◽  
Ronald Heath
Keyword(s):  
Shallow Water ◽  
Debris Flows ◽  
Large Scale ◽  
Numerical Models ◽  
The United States ◽  
Water Model ◽  
Sediment Runoff ◽  
Two Dimensional ◽  
Model Framework ◽  
Model Library

<p>The number and intensity of large wildfires in is a growing concern in the United States.  Over the past decade, the National Interagency Fire Centre (NSTC, 2015) reported increases of large fires in every western state in the arid and semi-arid western U.S.  Wildfires, remove vegetation, reduce organic soil horizons to ash, extirpate microbial communities, alters soil structure, and potential development of hydrophobic soils.  These processes all increase water and sediment runoff. Post-wildfire environments can cause a spectrum of hydrologic and sedimentation responses ranging from no response to catastrophic floods and deadly debris flows. Numerical modellers have developed a variety of Newtonian and non-Newtonian shallow-water algorithms to simulate each of these physical processes – making it difficult to model the range of post-wildfire flood conditions and understand model assumption and limitations. This makes a modular non-Newtonian computation library advantageous. This work presents a flexible, numerical model, library framework ‘DebrisLib’ to simulate large-scale, post-wildfire non-Newtonian flows using diverse shallow-water parents code architecture. This work presents the non-Newtonian model framework effectiveness by linking it with two different modelling frameworks, specifically the diffusive-wave one-dimensional and two-dimensional Hydrologic Engineering Center River Analysis System (HEC-RAS), and shallow-water two-dimensional Adaptive Hydraulics (AdH) numerical models. The model library was verified and validated using three flume experiments for mud flows, hyperconcentrated flows, and debris flows under steady and unsteady flow conditions. Additionally the shallow-water model library framework linked with the 1D Hydrologic Engineering Centre Hydrologic Modelling System (HEC-HMS) successfully predicted the 2018 post-wildfire flooding and debris flows following the 2017 Thomas Fire near Santa Barbara, California.</p>

A critical layer dominated by non-parallel effects in a rotating barotropic flow

1983 ◽  
Vol 388 (1795) ◽  
pp. 293-310 ◽  
Keyword(s):  
Large Scale ◽  
Transverse Velocity ◽  
Reynolds Numbers ◽  
Geophysical Flows ◽  
Critical Layer ◽  
Flow Conditions ◽  
Barotropic Flow

The critical layer of perturbations to slowly modulating strong rectified currents induced by vorticity sources in a quasi-geostrophic barotrophic flow is investigated. For r ≫ Re -3/2 and r ≫ δ 2 which correspond to realistic geophysical conditions, the critical layer is dominated by the advection of the perturbation’s vorticity by the weak transverse velocity of the basic state and not by the traditional viscous or nonlinear balance. The Ekman, Rossby and Reynolds numbers of the flow are E , Ro and Re respectively and r = E ½ / Ro , while δ is the parameter of nonlinearity. The width of the critical layer is O ( r 1/6 ) which can be quite thick for relevant flow conditions. This suggests that non-parallel effects play an important role in the dynamics of large scale geophysical flows.

Quasi-two-dimensional properties of a single shallow-water vortex with high initial Reynolds numbers

2010 ◽  
Vol 665 ◽  
pp. 274-299 ◽  
Author(s):  
D.-G. SEOL ◽  
G. H. JIRKA
Keyword(s):  
Reynolds Number ◽  
Shallow Water ◽  
Coherent Structures ◽  
Large Scale ◽  
Reynolds Numbers ◽  
Surface Velocity ◽  
Mode Analysis ◽  
Two Dimensional ◽  
Vortex System ◽  
Decay Model

The evolution and dynamics of a shallow-water vortex system with high initial Reynolds numbers are investigated experimentally without background rotation. A single vortex is generated by rotating a water mass at the centre of an experimental tank using a bottomless cylinder with internal sectors. The surface velocity field is observed via particle image velocimetry. The experimentally observed vorticity fields indicate that strong shallowness (the ratio of the cylinder diameter to the water depth) and high Reynolds number contribute to the formation of large-scale coherent structures in the form of a tripolar vortex system. The shallow-water vortices with high initial Reynolds numbers experience the transition from turbulent to laminar regimes in their decay process. The proposed first-order vortex decay model predicts that a shallow-water vortex decays as t−1 in the initial turbulent stage and as e−t in the later laminar stage due to horizontal diffusion and bottom friction. The estimated transition time scale from the turbulent to laminar stage increases with initial vortex Reynolds number and with shallowness. By taking the vortex expansion into consideration, the second-order vortex decay model is also presented. The azimuthally ensemble-averaged data elucidate effects of the vortex instabilities and of turbulent energy transfer on the formation of large-scale coherent flow structures. Normal mode analysis of the vortex systems is conducted to study the effect of shallowness and Reynolds number on the generation of two-dimensional large-scale coherent structures. The results show that the perturbation wavenumber of mode 2 is the fastest-growing instability in shallow-water conditions, and its effect depends on initial Reynolds number and shallowness.

scholarly journals SIMULATION OF SANDFILL BUILDING STAGES WITH NUMERICAL FLOW MODELS

1986 ◽  
Vol 1 (20) ◽  
pp. 75
Author(s):  
G.J. Bosselaar ◽  
R.A.H. Thabet ◽  
A.J.G.M. Van Roermund ◽  
L. Bijlsma
Keyword(s):  
Large Scale ◽  
Numerical Models ◽  
Flow Patterns ◽  
Two Dimensional ◽  
Integrated Models ◽  
Flow Models ◽  
Test Models ◽  
Physical Scale ◽  
Scale Models ◽  
Closure Operations

The paper describes the application of two dimensional vertically integrated models (WAQUA system) , the results being used for the calculation of sandlosses during sandfill closure operations. Investigations with test models, physical scale models as well as numerical models, are presented to prove that the WAQUA system is not only suitable for large scale applications, but also for the simulation of detailed flow patterns.

scholarly journals Data assimilation of two-dimensional geophysical flows with a Variational Ensemble Kalman Filter

2014 ◽  
Vol 1 (1) ◽  
pp. 403-446 ◽  
Author(s):  
Z. Mussa ◽  
I. Amour ◽  
A. Bibov ◽  
T. Kauranne
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Shallow Water ◽  
Ensemble Kalman Filter ◽  
Geophysical Flows ◽  
Water Model ◽  
Test Case ◽  
Two Dimensional ◽  
Shallow Water Model ◽  
Model Bias

Abstract. The Variational Ensemble Kalman Filter (VEnKF), a recent data assimilation method that combines a variational assimilation of the Bayesian estimation problem with an ensemble of forecasts, is demonstrated in two-dimensional geophysical flows using a Quasi-Geostrophic (QG) model and a shallow water model. Using a synthetic experiment, a two layer QG model with model bias is solved on a cylindrical 40 x 20 domain. The performance of VEnKF on the QG model with increasing ensemble size is compared with the classical Extended Kalman Filter (EKF). It is shown that although convergence can be achieved with just 20 ensemble members, increasing the number of members results in a better estimate that approaches the one produced by EKF. In the second test case, a 2-D shallow water model is described using a real dam-break experiment. The VEnKF algorithm was used to assimilate observations obtained from a modified laboratory dam-break experiment with a two-dimensional setup of sensors at the downstream end. The wave meters are placed parallel to the direction of the flow alongside the flume walls to capture both cross flow and stream flow. In both test cases, VEnKF was able to predict genuinely two-dimensional flow patterns when the sensors had a two-dimensional geometry and was stable against model bias in the first test case. In the second test case, the experiments are complemented with an empirical study of the impact of observation interpolation on the stability of the VEnKF filter. In this study, a novel Courant–Friedrichs–Lewy type filter stability condition is observed that relates ensemble variance to the time interpolation distance between observations. The results of the two experiments shows that VEnKF is a good candidate for data assimilation problems and can be implemented in higher dimensional nonlinear models.

scholarly journals SEMI-IMPLICIT NUMERICAL SCHEMA IN SHALLOW WATER EQUATION

2017 ◽  
Vol 17 (2) ◽  
pp. 102
Author(s):  
Safwandi Safwandi ◽  
Syamsul Rizal ◽  
Tarmizi Tarmizi
Keyword(s):  
New York ◽  
Shallow Water ◽  
Shallow Water Equations ◽  
Numerical Solutions ◽  
Numerical Models ◽  
Shallow Water Equation ◽  
Two Dimensional ◽  
Numerical Schemes ◽  
Spectral Difference ◽  
Spectral Difference Method

Abstract. A two-dimensional shallow water equation integrated on depth water based on finite differential methods. Numerical solutions with different methods consist of explicit, implicit and semi-implicit schemes. Different methods of shallow water equations expressed in numerical schemes. For bottom-friction is described in semi-implicitly. This scheme will be more flexible for initial values and boundary conditions when compared to the explicit schemes.  Keywords: 2D numerical models, shallow water equations, explicit and semi-implicit schema.Reference Hassan, H. S., Ramadan, K. T., Hanna, S. N. 2010. Numerical Solution of the Rotating Shallow Water Flows with Topography Using the Fractional Steps Method, Scie.Res,App.Math. (1):104-117. Omer, S, Kursat, K. 2011. High-Order Accurate Spectral Difference Method For Shallow Water Equations. IJRRAS6. Vol. 6. No. 1. Kampf, J. 2009. Ocean Modelling for Beginners. Springer Heidelberg Dordrecht. London, New York. Wang, Z. L., Geng, Y. F. 2013. Two-Dimensional Shallow Water Equations with Porosity and Their Numerical scheme on Unstructured Grids. J. Water Science and Engineering. Vol. 6, No. 1, 91-105. Saiduzzaman, Sobuj. 2013. Comparison of Numerical Schemes for Shallow Water Equation. Global J. of Sci. Fron. Res. Math. and Dec. Sci. Vol. 13 (4). Sari, C. I., Surbakti, H., Fauziyah., Pola Sebaran Salinatas dengan Model Numerik Dua Dimensi di Muara Sungai Musi. Maspari J. Vol. 5 (2): 104-110. Bunya, B., Westerink, J. J. dan Shinobu, Y. 2004. Discontinuous Boundary Implementation for the Shallow Water Equations. Int. J. Numer. Meth. Fluids 2005 (47): 1451–1468. 

The SERGHEI model and its core shallow water solver

2021 ◽  
Author(s):  
Mario Morales-Hernández ◽  
Ilhan Özgen-Xian ◽  
Daniel Caviedes-Voullième
Keyword(s):  
Shallow Water ◽  
Large Scale ◽  
Programming Model ◽  
Small Scale ◽  
System Modelling ◽  
Earth System ◽  
Model Framework ◽  
Hydrological Simulation ◽  
Spatiotemporal Scales ◽  
Earth System Modelling

<p>The Simulation Environment for Geomorphology, Hydrodynamics and Ecohydrology in Integrated form (SERGHEI) model framework is a multi-dimensional, multi-domain and multi-physics model framework. It is designed to provide a modelling environment for hydrodynamics, ecohydrology, morphodynamics, and, importantly, interactions and feedbacks among such processes, at different levels of complexity and across spatiotemporal scales. SERGHEI is in essence, a terrestrial landscape simulator based on a hydrodynamics core, designed with an outlook towards Earth System Modelling applications. Consequently, efficient mathematical and numerical formulations, as well as HPC implementations are at its core. SERGHEI intends to enable large scale and high resolution problems, which will allow to acknowledge and simulate emergent behaviours rising from the small-scale interactions and feedbacks between different environmental processes, that often manifest at larger spatiotemporal scales.</p><p>At the core of the technical innovation in SERGHEI is its HPC implementation, built from scratch on the Kokkos programming model and C++ library. This approach facilitates portability from personal computers to Tier-0 HPC systems, including GPU-based and heterogeneous systems. This is achieved by relying on Kokkos handling memory models, thread management and computational policies for the required backend programming models. In particular, using Kokkos, SERGHEI can be compiled for multiple CPUs and GPUs using a combination of OpenMP, MPI, and CUDA.</p><p>In this contribution, we introduce the SERGHEI model framework, and specially its first operational module for solving shallow water equations (SERGHEI-SWE). This module is designed to be applicable to hydrological, environmental and consequently Earth System Modelling problems, but also to classical engineering problems such as fluvial or urban flood modelling. We also provide a first showcase of the applicability of the SERGHEI-SWE solver to several well-known benchmarks, and the performance of the solver on large-scale hydrological simulation and flooding problems. We also show and discuss the scaling properties of the solver (on several Tier-0 systems)  and sketch out its current and future development.</p>

scholarly journals Two-Dimensional Shallow-Water Model with Porosity for Urban Flood Modeling

Proceedings ◽  
2018 ◽  
Vol 2 (20) ◽  
pp. 1307
Author(s):  
Malika Benslimane ◽  
Saâdia Benmamar ◽  
André Paquier
Keyword(s):  
Shallow Water ◽  
Shallow Water Equations ◽  
Urban Areas ◽  
Large Scale ◽  
Momentum Equation ◽  
Water Model ◽  
Finite Volume Scheme ◽  
Two Dimensional ◽  
Flood Modeling ◽  
Urban Flood

In the world, floods are at the forefront of natural hazard. Urban areas are often at risk of flooding and just as often unprepared for management. Flood modeling is nowadays a very important topic in the theme of water, it inevitably involves the numerical resolution of the shallow water equations derived from the Navier Stocks equations governing flows. Two-dimensional shallow water models with porosity appear as an interesting path for the large-scale modeling of floodplains with urbanized areas. The porosity accounts for the reduction in storage and in the exchange sections due to the presence of buildings and other structures in the floodplain. The introduction of a porosity into the two-dimensional shallow water equations leads to modified expressions for the fluxes and source terms. An extra source term appears in the momentum equation. The developed solution method consists in solving the two-dimensional shallow water equations with porosity via a finite volume scheme solving the conservative form of the equations which can be reduced to a calculation of flux through an edge, a problem that can be approached by a one-dimensional problem in the normal direction at the edge (Riemann problem).

scholarly journals A Novel Machine Learning Strategy Based on Two-Dimensional Numerical Models in Financial Engineering

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Qingzhen Xu
Keyword(s):  
Machine Learning ◽  
Stock Market ◽  
Large Scale ◽  
Numerical Solutions ◽  
Learning Strategy ◽  
Numerical Models ◽  
Relevant Information ◽  
Future Trend ◽  
Two Dimensional ◽  
Stock Market Index

Machine learning is the most commonly used technique to address larger and more complex tasks by analyzing the most relevant information already present in databases. In order to better predict the future trend of the index, this paper proposes a two-dimensional numerical model for machine learning to simulate major U.S. stock market index and uses a nonlinear implicit finite-difference method to find numerical solutions of the two-dimensional simulation model. The proposed machine learning method uses partial differential equations to predict the stock market and can be extensively used to accelerate large-scale data processing on the history database. The experimental results show that the proposed algorithm reduces the prediction error and improves forecasting precision.

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