In dCraigJones/rSSOAP: rSSOAP

source("../../R/clean.R")
source("../../R/shape.R")
source("../../R/isolate.R")
source("../../R/model.R")
source("../../R/draw.R")
source("../../R/util.R")

load("../../data/hourly_rain.RData")
load("../../data/hourly_flow.RData")
# 
library(dplyr)
library(zoo)
library(lubridate)
library(vars)
library(imputeTS)
library(stringr)
library(tidyr)
library(ggplot2); theme_set(theme_bw())

Workflow:

Load Data

• date, defined
• flow, defined
• rain, defined

Scrub Data

• scrub, cleaned

Dry-Weather Flow

• gwi
• gwi_model
• bsf
• bsf_model

Wet-Weather Flow

• rdi
• rdi_model

Final Model

• model
• residual
• error

Example

Load Data

# convert hourly data to daily data
rain_ <- hourly_rain %>%
  filter(station=="BUCKMN") %>%
  mutate(date=lubridate::date(datetime)) %>%
  group_by(date) %>%
  summarize(rain=sum(rainfall_in, na.rm=TRUE))


tmp <- hourly_flow %>%
  filter(str_detect(location, "Tow")) %>%
  mutate(date=date(datehour)) %>%
  filter(date>mdy("10/5/2018")) %>% 
  filter(date<mdy("01/01/2020")) %>%
  na.omit(flow) %>%
  group_by(date) %>%
  summarize(df=sum(flow, na.rm=TRUE)) %>%
  left_join(rain_, by="date")

date <- tmp$date
flow <- tmp$df
rain <- tmp$rain

df <- data.frame(date=date, flow=flow, rain=rain)

Scrub Data

df$scrub <- remove_outliers(df$flow)

Dry-Weather Flow

df$gwi <- isolate_daily_gwi(df$date, df$scrub, df$rain)
uh.3 <- shape_daily_hydrograph(df$date, df$gwi, df$rain, 14, 0.25, 1)
df$gwi_model <- model_hydrograph(df$rain, uh.3)

df$bsf <- df$scrub - df$gwi_model
df$bsf_model <- isolate_daily_bsf(df$date, df$bsf, df$rain)

Wet-Weather Flow

df$rdi <- df$scrub - df$bsf_model - df$gwi_model
uh.2 <- shape_daily_hydrograph(df$date, df$rdi, df$rain, 7, 0.25, 10)
df$rdi_model <- model_hydrograph(df$rain, uh.2)

Final Model

df$model <- df$bsf + df$gwi + df$rdi
df$residual <- df$model-df$scrub
df$error <- df$residual/df$scrub

draw_model_qaqc(df)

plot(uh.2, type="n")
lines(uh.2)
lines(uh.3)

rain_ <- hourly_rain %>%
  filter(station=="BUCKMN")


tmp <- hourly_flow %>%
  filter(str_detect(location, "Tow")) %>%
  mutate(date=date(datehour)) %>%
  filter(date>mdy("10/5/2018")) %>% 
  filter(date<mdy("01/01/2020")) %>%
  left_join(rain_, by=c("datehour"="datetime")) %>%
  left_join(df, by="date")


date <- tmp$datehour
flow <- tmp$flow.x-tmp$gwi_model/1440*60-tmp$rdi_model/1440*60
rain <- tmp$rainfall_in

hf <- data.frame(date=date, flow=flow, rain=rain)

plot(date, flow, type="l", col=rgb(0.25,0.25,0.25,0.25))
abline(h=0)
lines(date, rain*500, lwd=2, col="blue")

# consider calculating GWI from night-time flow.
# next step is to extract diurnal pattern

dCraigJones/rSSOAP documentation built on Aug. 12, 2022, 10:11 p.m.