TonyLadson’s gists

TonyLadson / ARF_Calculator.R

Last active December 17, 2021 02:41

	#
	# This is a Shiny web application. You can run the application by clicking
	# the 'Run App' button above.
	#
	# Find out more about building applications with Shiny here:
	#
	# http://shiny.rstudio.com/
	#

	library(shiny)

TonyLadson / Get_tidy_preburst_losses.R

Created March 29, 2020 21:51

Function to get pre-burst and loss information from the data hub. See https://tonyladson.wordpress.com/2020/03/23/tidy-pre-burst-data/

	Get_tidy_prebust_losses <- function(lat, lon){

	require(RCurl)
	require(stringr)
	require(tidyverse)
	require(glue)

	# Functions_____________________________________________________________________________

	# Function to get the text file from the data hub for a latitude and longitude

TonyLadson / Get_losses.R

Last active March 29, 2020 21:40

Function to return initial and continuing loss from the data hub for a given latitude and longitude

TonyLadson / Get_tidy_preburst.R

Last active March 24, 2020 01:00

Function to get preburst data from the data hub and convert it into a tidy format. See https://tonyladson.wordpress.com/2020/03/23/tidy-pre-burst-data/

	Get_tidy_prebust <- function(lat, lon){

	require(RCurl)
	require(stringr)
	require(tidyverse)
	require(glue)

	# Functions_____________________________________________________________________________

	# Function to get the text file from the data hub for a latitude and longitude

TonyLadson / Get_preburst.R

Last active March 20, 2020 04:51

Function to scrape the data hub and return information on pre-burst rainfall, see https://tonyladson.wordpress.com/2020/03/16/scraping-the-data-hub/

	# lat and lon must be latitude and longitude of some point on Australia, latitude must be negative

	Get_preburst <- function(percentile = c(50, 10, 25, 75, 90), type = c("depth", "ratio"), lat, lon){

	require(tidyverse)
	require(stringr)
	require(glue)
	require(RCurl)

	# Check inputs--------------------

TonyLadson / WP_treemap.R

Last active September 3, 2019 22:39

Making a treemap for hydrological purposes. See the blog https://tonyladson.wordpress.com/2019/09/02/using-a-treemap-to-show-gauged-areas/

	library(treemap)
	library(tidyverse)



	wp <- tribble(~catchment, ~sub_catchment, ~area,
	'Bunyip', 'Gauged', 697,
	'Bunyip', 'Ungauged', 479,
	'Lang Lang', 'Gauged', 272,
	'Lang Lang', 'Ungauged', 151,

TonyLadson / Burst_IL.R

Last active March 30, 2020 00:25

Distribution of burst initial loss https://tonyladson.wordpress.com/2019/08/13/the-distribution-of-burst-initial-loss/


	# Burst initial loss = storm initial loss - preburst rainfall


	# Storm initial loss ------------------------------------------------------


	# emprical distribution of initial loss
	# From ARR Table Table 5.3.13
	# http://book.arr.org.au.s3-website-ap-southeast-2.amazonaws.com

TonyLadson / Pre-burst.R

Last active August 6, 2019 23:06

Distribution of pre-burst rainfall. See the blog https://tonyladson.wordpress.com/2019/08/06/the-distribution-of-pre-burst-rainfall/

	# Data from the ARR data hub for Toomuc Creek

	pre_burst <- tribble(~perc, ~depth, ~ ratio,
	10,0,0,
	25,0,0,
	50,1.5, 0.029,
	75,13.3, 0.256,
	90,38.4, 0.739)

TonyLadson / Loss_pdf.R

Last active August 1, 2019 22:29

Calculating an empirical probability density plot for Initial and Continuing Loss. See https://tonyladson.wordpress.com/2019/07/30/the-distribution-of-losses-ii/

	library(tidyverse)
	library(pracma)
	library(here)


	loss_std <- structure(list(Percentile = c(100, 90, 80, 70, 60, 50, 40, 30,
	20, 10, 0), IL = c(0.14, 0.39, 0.53, 0.68, 0.85, 1, 1.2, 1.4,
	1.71, 2.26, 3.19), CL = c(0.15, 0.35, 0.48, 0.61, 0.79, 1, 1.24,
	1.5, 1.88, 2.48, 3.85), prob = c(0, 0.1, 0.2, 0.3, 0.4, 0.5,
	0.6, 0.7, 0.8, 0.9, 1)), class = c("tbl_df", "tbl", "data.frame"

TonyLadson / Loss.R

Last active August 1, 2019 22:30

Distribution of Initial and continuing losses. Gist to support a blog https://tonyladson.wordpress.com/2019/07/23/the-distribution-of-losses/

	# Generating initial loss values from the standardised initial losses from ARR
	# Book 5
	# Chapter 3.6.1
	# Table 5.3.13

	# The original source of this is Nathan et al. (2003)
	# Nathan, R.J., Weinmann, P.E. and Hill, P.I. (2003), Use of a Monte-Carlo Simulation to
	# estimate the Expected Probability of large to extreme floods, Proceedings of the 28th
	# International Hydrology and Water Resources Symposium, pp: 1105-1112, 10-14 November,
	# Wollongong.

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