# Date(s): 2/7/2022
# Project: Carli Creek Water Quality Assessment Project
# Created For: Pollutants, medians, OWQC, and Intern'l BMP database
# Name: Chris Desiderati
###
setwd("C:/Users/irish/Documents/ACADEMIC/GRAD SCHOOL/Project_Carli/R")
getwd()
library(tidyverse) #activate tidyverse
library(lubridate) #activate lubridate to deal with time 
library(dplyr) #to transform data
#### Finding Peak reductions 
SS1<-read.csv("Site1.csv")
SS1$DateTime<-mdy_hm(SS1$DateTime)
SS3<-read.csv("Site3.csv")
SS3$DateTime<-mdy_hm(SS3$DateTime)
SS4<-read.csv("Site4.csv")
SS4$DateTime<-mdy_hm(SS4$DateTime)
SS13<-SS1%>%
  left_join(SS3,by="DateTime")
SS13<-SS13%>%
  rename(Site.1=Flow.x)%>%
  rename(Site.3=Flow.y)%>%
  rename(Date=DateTime)
str(SS13)
SS13$Date<-ymd(SS13$Date)
SS13%>% # Percent Peak Flow reductions during defined time-intervals of study period
  filter(Date>as_datetime("2021-01-29 12:00:00")&Date<as_datetime("2021-01-30 12:00:00"))%>%
  drop_na()%>%
  summarize(MaxSite1=max(Site.1),MaxSite3=max(Site.3))%>%
  mutate(Reduction=((MaxSite1)-(MaxSite3))/MaxSite1*100)

#### Stats of Field Parameters ###
df0<-read.csv("CarliCW_050521.csv")
df0 %>%
  group_by(Sample.Pt.Descr) %>%
  summarise_at(c("COND_FLD","PH_FLD","DO_FLD","TEMP_FLD"),mean)
df0 %>%
  group_by(Sample.Pt.Descr) %>%
  summarise_at(c("COND_FLD","PH_FLD","DO_FLD","TEMP_FLD"),median)
df0 %>%
  group_by(Sample.Pt.Descr) %>%
  summarise_at(c("COND_FLD","PH_FLD","DO_FLD","TEMP_FLD"),sd)
df0 %>%
  group_by(Sample.Pt.Descr) %>%
  summarise_at(c("COND_FLD","PH_FLD","DO_FLD","TEMP_FLD"),min)
df0 %>%
  group_by(Sample.Pt.Descr) %>%
  summarise_at(c("COND_FLD","PH_FLD","DO_FLD","TEMP_FLD"),max)

#### Stats of Solids ####
df0 %>%
  group_by(Sample.Pt.Descr) %>%
  summarise(across(c("TSS","TDS","TS","HARDNESS"),list(mean=mean,median=median,sd=sd,min=min,max=max)))%>%
  write.csv("SolidsStats.csv",row.names=T)

#### Stats of E. coli####
df0 %>%
  group_by(Sample.Pt.Descr) %>%
  summarise(across(c("COLILERT"),list(median=median,sd=sd,min=min,max=max)))%>%
  write.csv("EcoliStats.csv",row.names=T)

#### Stats of Nutrients ####
df0 %>%
  group_by(Sample.Pt.Descr) %>%
  summarise(across(c("NH3","NO3NO2","TPO4"),list(mean=mean,median=median,sd=sd,min=min,max=max)))%>%
  write.csv("NutsStats.csv",row.names=T)

#### Stats of Metals ####
df0 %>%
  group_by(Sample.Pt.Descr) %>%
  summarise(across(c("CD","CU","PB","ZN","HG"),list(mean=mean,median=median,sd=sd,min=min,max=max)))%>%
  write.csv("TotalM+Stats.csv",row.names=T)
df0 %>%
  group_by(Sample.Pt.Descr) %>%
  summarise(across(c("CD_DISS","CU_DISS","PB_DISS","ZN_DISS"),list(mean=mean,median=median,sd=sd,min=min,max=max)))%>%
  write.csv("DissM+Stats.csv",row.names=T)