Flood modeling by 2D shallow water equation

Last update: Nov 30, 2022

hydraulicmodel

Flood modeling by 2D shallow water equation. Refer to Hunter et al (2005), Bates et al. (2010).

Diffusive wave approximation

$\frac{\partial h ^{i, j}}{\partial t} = \frac{Q_x^{i-1, j} - Q_x^{i, j} Q_y^{i, j-1} - Q_y^{i, j}}{\Delta x \Delta y}$

$Q_x^{i, j} = \frac{h_{flow}^{5/3}}{n} \left( \frac{h^{i-1, j} - h^{i, j}}{\Delta x} \right) ^{1/2} \Delta y$

$Q_y^{i, j} = \frac{h_{flow}^{5/3}}{n} \left( \frac{h^{i-1, j} - h^{i, j}}{\Delta y} \right) ^{1/2} \Delta x$

Local inertail approaximation

$\frac{\partial h ^{i, j}}{\partial t} = \frac{Q_x^{i-1, j} - Q_x^{i, j} Q_y^{i, j-1} - Q_y^{i, j}}{\Delta x \Delta y}$

$q_{t \Delta t} = \frac{q_t - gh_{flow, t} \Delta t \frac{\partial h_t}{\partial x}} {1 g n^2 \Delta t q_t / h_{flow, t}^{7/3}}$

Time steps in two methods

Diffusive wave approximation

$\Delta t = \frac{\Delta x^2}{4} min \left( \frac{2n}{h_{flow}^{5/3}}|\frac{\partial h}{\partial x}|^{1/2}, \frac{2n}{h_{flow}^{5/3}}|\frac{\partial h}{\partial y}|^{1/2} \right)$

Local inertial approximation

$\Delta t = \alpha \frac{\Delta x}{\sqrt{g (h-z)_{max}}}$

Implementation of these two approximation for simulating the flood in Mobara city on October 25, 2019

Setting of the domain and boundary conditions

Results of the maximum inundation area calculated by the diffusive wave approximation, compared with the flood extent reported by Chiba Office

Results of the inundation range considering the flood recession by the local inertial approximation, compared with the flood extent estimated by Geospatial Information Authority of Japan (GSI).

Flood modeling by 2D shallow water equation

Related tags

Overview

hydraulicmodel

Diffusive wave approximation

Local inertail approaximation

Time steps in two methods

Implementation of these two approximation for simulating the flood in Mobara city on October 25, 2019

Evolution of flood volume

Owner

Data Intelligence Applications - Online Product Advertising and Pricing with Context Generation

ICLR 2022 Paper submission trend analysis

MidTerm Project for the Data Analysis FT Bootcamp, Adam Tycner and Florent ZAHOUI

Exploratory data analysis

Churn prediction with PySpark

INFO-H515 - Big Data Scalable Analytics

Python script to automate the plotting and analysis of percentage depth dose and dose profile simulations in TOPAS.

EOD Historical Data Python Library (Unofficial)

High Dimensional Portfolio Selection with Cardinality Constraints

🧪 Panel-Chemistry - exploratory data analysis and build powerful data and viz tools within the domain of Chemistry using Python and HoloViz Panel.

Data collection, enhancement, and metrics calculation.

This mini project showcase how to build and debug Apache Spark application using Python

cLoops2: full stack analysis tool for chromatin interactions

Spectacular AI SDK fuses data from cameras and IMU sensors and outputs an accurate 6-degree-of-freedom pose of a device.

MotorcycleParts DataAnalysis python

Analyzing Earth Observation (EO) data is complex and solutions often require custom tailored algorithms.

Incubator for useful bioinformatics code, primarily in Python and R

Data Competition: automated systems that can detect whether people are not wearing masks or are wearing masks incorrectly

Using Python to scrape some basic player information from www.premierleague.com and then use Pandas to analyse said data.

Hue Editor: Open source SQL Query Assistant for Databases/Warehouses