TonyLadson

# Geometric Distribution of 1% floods


# probability of 4 or fewer safe years
pgeom(4, 0.01)
# [1] 0.04900995

# probability of exactly 4 safe years and then a flood in the 5th
dgeom(4, 0.01)
#[1] 0.00960596

TonyLadson

Hydro <- function(tt, t.peak = 1, Qmin = 1, Qmax = 10, beta = 5) {
  Qmin + (Qmax - Qmin)*( (tt/t.peak) * (exp(1 - tt/t.peak)))^beta
  
}



tt.seq <- seq(0,4,0.01)

op <- par(oma = c(1, 2, 0, 0))

TonyLadson

library(ggplot)
library(grid)
library(devtools)
library(dplyr)
library(lubridate)

source_gist('cc60bbb3cbadf0e72619') # ggplot theme

# Data is stored in a data frame with the date, flow and quality code
# You'll need to provide your own data for this to work.

TonyLadson

##########################################################
#
#  Plotting Flike Output
#  see https://tonyladson.wordpress.com/2015/10/20/better-frequency-plots-from-web-based-flike/
#
############################################################



library(stringr)

TonyLadson

require(ggplot2)
require(zoo)
require(dplyr)


# MakeNames_Hydstra
# Hydstra files have names spread across 4 rows. This gist, turns the data into a single string

MakeNames_Hydstra <- function(Hydstra.csv){
  

TonyLadson

FDC <- function(Q, xnormal=TRUE, xlab='%time flow equalled or exceeded',
                ylab='flow',Qreturn=FALSE, plotFlow=FALSE, add=FALSE, alpha=0.5, ...) {
  
  # Q - flow data (vector of flow values)
  # xnormal - logical value to determine if the percentiles should be plotted in a normal (probit) scale
  # Qreturn - logical value indicating if quantiles should be returned
  # plotFlow - logical value indicating if a time series of flow should be overplotted on flow duration curve
  # add - should fdc be added to an existing plot?
  # alpha - transparency value for overplotting of flow time series
  

TonyLadson

library(dplyr)
library(ggplot2)
library(grid)
library(scales)

# download sample files from google drive

file_id <- "1a5ksZpQbuAnbC6oNEBe8RJO4Z1L2HEic"
url <- sprintf("https://docs.google.com/uc?id=%s&export=download", file_id)
wq <- read.csv(url)

TonyLadson

# Confidence intervals for the mean for non-normal data
# See https://tonyladson.wordpress.com/2016/01/11/plotting-water-quality-samples-on-a-hydrograph/


# Modified Cox function for calculating confidence intervals for the mean
# Based on Olsson, 2005
# http://www.amstat.org/publications/jse/v13n1/olsson.html

# x is a set of log-normal data

TonyLadson

# See https://tonyladson.wordpress.com/2016/02/08/envelop-curve-for-record-australian-rainfall/
# remove(list = objects())

library(XML)
library(dplyr)
library(MASS)
library(xtable)

TonyLadson

library(quantreg)
library(dplyr)
library(lubridate)
library(stringr)
library(readr)
library(ggplot2)
library(devtools)
library(splines)