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Outflow_2045.Rmd
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---
title: "Output_flow"
author: "Gustavo Facincani Dourado"
date: "6/12/2020"
output: html_document
---
```{r}
library(reshape2)
library(lfstat)
Livneh_outflow_Mer <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/merced/historical/Livneh/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,12)]%>%
filter(between(node, as.Date("1980-10-01"), as.Date("2010-09-30")))
colnames(Livneh_outflow_Mer) <- c("node", "Livneh (Historical)")
Livneh_outflow_Mer
CanESM2_outflow_Mer <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/merced/gcms/CanESM2_rcp45/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,12)]
colnames(CanESM2_outflow_Mer) <- c("node", "CanESM2")
CanESM2_outflow_Mer
#CanESM2_MIF_Mer <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/merced/gcms/CanESM2_rcp45/InstreamFlowRequirement_Min Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,2)]
#CanESM2_MIF_Mer
#CanESM2_MIF_Mer
CNRM_outflow_Mer <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/merced/gcms/CNRM-CM5_rcp45/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,12)]
colnames(CNRM_outflow_Mer) <- c("node", "CNRM-CM5")
CNRM_outflow_Mer
HadGEM2_outflow_Mer <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/merced/gcms/HadGEM2-ES_rcp45/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,12)]
colnames(HadGEM2_outflow_Mer) <- c("node", "HadGEM2-ES")
HadGEM2_outflow_Mer
MIROC5_outflow_Mer <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/merced/gcms/MIROC5_rcp45/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,12)]
colnames(MIROC5_outflow_Mer) <- c("node", "MIROC5")
MIROC5_outflow_Mer
```
```{r}
Livneh_Mer_outflow <- Livneh_outflow_Mer
Livneh_Mer_outflow <- melt(Livneh_Mer_outflow, id = "node")
Livneh_Mer_outflow
Outflow_Mer <- cbind(CanESM2_outflow_Mer, CNRM_outflow_Mer[(-1)],
HadGEM2_outflow_Mer[(-1)], MIROC5_outflow_Mer[(-1)])
Outflow_Mer
```
```{r}
Outflow_Mer1 <- melt(Outflow_Mer, id = "node")
Outflow_Mer1
Outflow_Mer2 <- rbind(Outflow_Mer1, Livneh_Mer_outflow) %>%
mutate(Month = as.factor(format(as.Date(node, format = "%B"), "%b")),
Year = water_year(node, origin = "usgs"),
Scenario = as.factor("RCP 4.5")) %>%
group_by(Year, Month, variable) %>%
dplyr::summarize(MonthlyTotal = sum(value))
# group_by(Year, Scenario, variable) %>%
# dplyr::mutate(AnnualTotal = sum(value))
Outflow_Mer2
Outflow_Mer2$variable <- factor(Outflow_Mer2$variable, levels = c("Livneh (Historical)", "HadGEM2-ES", "CanESM2", "MIROC5", "CNRM-CM5"))
Outflow_Mer2
Outflow_Mer3 <- Outflow_Mer2 %>%
group_by(Year, variable) %>%
dplyr::summarize(AnnualTotal = sum(MonthlyTotal))
Outflow_Mer3
```
```{r}
ggplot(Outflow_Mer2) +
theme_bw(base_size=12, base_family='Times New Roman') + #change font to Times New Roman, 12pt, Bold
geom_boxplot(aes( x = Month, y = MonthlyTotal, fill = variable), outlier.alpha = 0.3) + #plot monthly observed data in greenish blue
# stat_summary(aes( x = Month, y = value, fill = variable),fun.data = f, outlier.alpha = 0.3, fun.y = sum, geom = "boxplot", stat = "identity")+
#geom_line(aes(x = node, y = value)) +
scale_y_continuous(limits = c(0, NA),
expand = c(0, NA),
labels = comma) +
#scale_y_log10(breaks=c(0.1,1,10,100,1000), labels=comma)+
scale_x_discrete(limits=c("Oct","Nov","Dec", "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep"))+
scale_fill_manual(values = c("#5A5A5A", "#E69F00", "#F0E442", "#009E73", "#56B4E9")) +
labs(fill = "RCP 4.5",
title = "Merced River",
x = element_blank(),
y = "Total River Outflow (mcm/month)") + #name of x axis
theme(legend.position = "bottom",
legend.direction = "horizontal",
legend.box.margin = margin(t = -17),
plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
strip.placement = "outside",
strip.background = element_blank(),
panel.spacing.y = unit(0, "lines"))+
png("Mer_montlhy_outflow_GCMs.png", units ="in", width=8, height=5, res = 300)
```
```{r}
ggplot(Outflow_Mer2) +
theme_bw(base_size=12, base_family='Times New Roman') + #change font to Times New Roman, 12pt, Bold
geom_boxplot(aes( x = Month, y = MonthlyTotal, fill = variable), outlier.alpha = 0.3) + #plot monthly observed data in greenish blue
# stat_summary(aes( x = Month, y = value, fill = variable),fun.data = f, outlier.alpha = 0.3, fun.y = sum, geom = "boxplot", stat = "identity")+
#geom_line(aes(x = node, y = value)) +
#scale_y_continuous(limits = c(0, NA),
# expand = c(0, NA),
# labels = comma) +
scale_y_log10(breaks=c(0.1,1,10,100,1000), labels=comma)+
scale_x_discrete(limits=c("Oct","Nov","Dec", "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep"))+
scale_fill_manual(values = c("#5A5A5A", "#E69F00", "#F0E442", "#009E73", "#56B4E9")) +
labs(fill = "RCP 4.5",
title = "Merced River",
x = element_blank(),
y = "Total River Outflow (mcm/month)") + #name of x axis
theme(legend.position = "bottom",
legend.direction = "horizontal",
legend.box.margin = margin(t = -17),
plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
strip.placement = "outside",
strip.background = element_blank(),
panel.spacing.y = unit(0, "lines"))+
png("Mer_montlhy_outflow_GCMs_logscale.png", units ="in", width=8, height=5, res = 300)
```
```{r}
#annual aggreagate
ggplot(Outflow_Mer3) +
theme_bw(base_size=12, base_family='Times New Roman') + #change font to Times New Roman, 12pt, Bold
geom_violin(draw_quantiles = c(.25, .5, .75), aes( x = variable, y = AnnualTotal, fill = variable)) + #plot monthly observed data in greenish blue
#geom_line(aes(x = node, y = value)) +
scale_y_continuous(limits = c(0, NA),
expand = c(0, NA),
labels = comma) +
scale_x_discrete(limits=c("Livneh (Historical)", "HadGEM2-ES", "CanESM2", "MIROC5", "CNRM-CM5"))+
scale_fill_manual(values = c("#5A5A5A", "#E69F00", "#F0E442", "#009E73", "#56B4E9")) +
# scale_y_log10(breaks=c(-10000000,-1000000,-100000,-10000, -1000, -100, -10, 0.1,1,10,100,1000), labels=c(-10000000,-1000000,-100000,-10000, -1000, -100, -10, 0.1,1,10,100,1000))+
labs(subtitle = "RCP 4.5 Scenario",
title = "Merced River",
x = element_blank(),
y = "Total River Outflow (mcm/year)") + #name of x axis
theme(legend.position = "none",
#legend.direction = "horizontal",
#legend.box.margin = margin(t = -19),
plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
strip.placement = "outside",
strip.background = element_blank(),
panel.spacing.y = unit(0, "lines"))+
png("Mer_annual_outflow_GCMs.png", units ="in", width=8, height=5, res = 300)
```
```{r}
Livneh_Outflow_Tuo <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/tuolumne/historical/Livneh/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,8)]
Livneh_Outflow_Tuo <- Livneh_Outflow_Tuo %>%
# mutate(Livneh = rowSums(Livneh_Outflow_Tuo[c(2:5)])) %>%
filter(between(node, as.Date("1980-10-01"), as.Date("2010-09-30")))
colnames(Livneh_Outflow_Tuo) <- c("node", "Livneh (Historical)")
Livneh_Outflow_Tuo
CanES_Outflow_Tuo <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/tuolumne/gcms/CanESM2_rcp45/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,8)]
#CanES_Outflow_Tuo <- CanES_Outflow_Tuo %>%
# mutate(CanESM2 = rowSums(CanES_Outflow_Tuo[c(2:5)]))
colnames(CanES_Outflow_Tuo) <- c("node", "CanESM2")
CanES_Outflow_Tuo
CNRM_Outflow_Tuo <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/tuolumne/gcms/CNRM-CM5_rcp45/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,8)]
#CNRM_Outflow_Tuo <- CNRM_Outflow_Tuo %>%
# mutate(`CNRM-CM5` = rowSums(CNRM_Outflow_Tuo[c(2:5)]))
colnames(CNRM_Outflow_Tuo) <- c("node", "CNRM-CM5")
CNRM_Outflow_Tuo
HadGEM_Outflow_Tuo <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/tuolumne/gcms/HadGEM2-ES_rcp45/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,8)]
#HadGEM_Outflow_Tuo <- HadGEM_Outflow_Tuo %>%
# mutate(`HadGEM2-ES` = rowSums(HadGEM_Outflow_Tuo[c(2:5)]))
colnames(HadGEM_Outflow_Tuo) <- c("node", "HadGEM2-ES")
HadGEM_Outflow_Tuo
MIROC_Outflow_Tuo <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/tuolumne/gcms/MIROC5_rcp45/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,8)]
#MIROC_Outflow_Tuo <- MIROC_Outflow_Tuo %>%
# mutate(MIROC5 = rowSums(MIROC_Outflow_Tuo[c(2:5)]))
colnames(MIROC_Outflow_Tuo) <- c("node", "MIROC5")
MIROC_Outflow_Tuo
```
```{r}
Livneh_Tuo_Outflow <- Livneh_Outflow_Tuo
Livneh_Tuo_Outflow <- melt(Livneh_Tuo_Outflow, id = "node")
Livneh_Tuo_Outflow
Outflow_Tuo <- cbind(CanES_Outflow_Tuo, CNRM_Outflow_Tuo[-1],
HadGEM_Outflow_Tuo[-1], MIROC_Outflow_Tuo[-1])
Outflow_Tuo
Outflow_Tuo2 <- melt(Outflow_Tuo, id = "node")
Outflow_Tuo2
```
```{r}
Outflow_Tuo2 <- rbind(Outflow_Tuo2, Livneh_Tuo_Outflow) %>%
mutate(Month = as.factor(format(as.Date(node, format = "%B"), "%b")),
Year = water_year(node, origin = "usgs"),
Scenario = as.factor("RCP 4.5")) %>%
group_by(Year, Month, variable) %>%
dplyr::summarize(MonthlyTotal = sum(value))
Outflow_Tuo2
Outflow_Tuo2$variable <- factor(Outflow_Tuo2$variable, levels = c("Livneh (Historical)", "HadGEM2-ES", "CanESM2", "MIROC5", "CNRM-CM5"))
Outflow_Tuo2
Outflow_Tuo3 <- Outflow_Tuo2 %>%
group_by(Year, variable) %>%
dplyr::summarize(AnnualTotal = sum(MonthlyTotal))
Outflow_Tuo3
```
```{r}
#Merced annual generation
#Gen_Mer2 %>%
# filter(variable == "CanESM2") %>%
ggplot(Outflow_Tuo2) +
theme_bw(base_size=12, base_family='Times New Roman') + #change font to Times New Roman, 12pt, Bold
geom_boxplot(aes( x = Month, y = MonthlyTotal, fill = variable), outlier.alpha = 0.3) + #plot monthly observed data in greenish blue
# geom_line(aes(x = node, y = value)) +
#scale_y_continuous(limits = c(0, NA),
# expand = c(0, NA),
# labels = comma) +
scale_y_log10(breaks=c(0, 0.1,1,10,100,1000), labels=comma)+
scale_x_discrete(limits=c("Oct","Nov","Dec", "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep"))+
scale_fill_manual(values = c("#5A5A5A", "#E69F00", "#F0E442", "#009E73", "#56B4E9")) +
labs(fill = "RCP 4.5",
title = "Tuolumne River",
x = element_blank(),
y = "Total River Outflow (mcm/month)") + #name of x axis
theme(legend.position = "bottom",
legend.direction = "horizontal",
legend.box.margin = margin(t = -17),
plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
strip.placement = "outside",
strip.background = element_blank(),
panel.spacing.y = unit(0, "lines"))+
png("Tuo_outflow_GCMs_logscale.png", units ="in", width=8, height=5, res = 300)
```
```{r}
#annual aggreagate
ggplot(Outflow_Tuo3) +
theme_bw(base_size=12, base_family='Times New Roman') + #change font to Times New Roman, 12pt, Bold
geom_violin(draw_quantiles = c(.25, .5, .75), aes( x = variable, y = AnnualTotal, fill = variable)) + #plot monthly observed data in greenish blue
#geom_line(aes(x = node, y = value)) +
scale_y_continuous(limits = c(0, NA),
expand = c(0, NA),
labels = comma) +
# scale_y_log10(breaks=c(-10000000,-1000000,-100000,-10000, -1000, -100, -10, 0.1,1,10,100,1000), labels=c(-10000000,-1000000,-100000,-10000, -1000, -100, -10, 0.1,1,10,100,1000))+
scale_x_discrete(limits=c("Livneh (Historical)", "HadGEM2-ES", "CanESM2", "MIROC5", "CNRM-CM5"))+
scale_fill_manual(values = c("#5A5A5A", "#E69F00", "#F0E442", "#009E73", "#56B4E9")) +
labs(subtitle = "RCP 4.5 Scenario",
title = "Tuolumne River",
x = element_blank(),
y = "Total River Outflow (mcm/year)") + #name of x axis
theme(legend.position = "none",
#legend.direction = "horizontal",
#legend.box.margin = margin(t = -19),
plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
strip.placement = "outside",
strip.background = element_blank(),
panel.spacing.y = unit(0, "lines"))+
png("Tuo_Outflow_GCMs2.png", units ="in", width=8, height=5, res = 300)
```
```{r}
Livneh_Outflow_Stn <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/stanislaus/historical/Livneh/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,4)]
Livneh_Outflow_Stn <-Livneh_Outflow_Stn %>%
# mutate(Livneh = rowSums(Livneh_Outflow_Stn[c(2:11)])) %>%
filter(between(node, as.Date("1980-10-01"), as.Date("2010-09-30")))
colnames(Livneh_Outflow_Stn) <- c("node", "Livneh (Historical)")
Livneh_Outflow_Stn
CanES_Outflow_Stn <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/stanislaus/gcms/CanESM2_rcp45/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,4)]
#CanES_Outflow_Stn <- CanES_Outflow_Stn %>%
# mutate(CanESM2 = rowSums(CanES_Outflow_Stn[c(2:11)]))
colnames(CanES_Outflow_Stn) <- c("node", "CanESM2")
CanES_Outflow_Stn
CNRM_Outflow_Stn <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/stanislaus/gcms/CNRM-CM5_rcp45/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,4)]
#CNRM_Outflow_Stn <- CNRM_Outflow_Stn %>%
# mutate(`CNRM-CM5` = rowSums(CNRM_Outflow_Stn[c(2:11)]))
colnames(CNRM_Outflow_Stn) <- c("node", "CNRM-CM5")
CNRM_Outflow_Stn
HadGEM_Outflow_Stn <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/stanislaus/gcms/HadGEM2-ES_rcp45/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,4)]
#HadGEM_Outflow_Stn <- HadGEM_Outflow_Stn %>%
# mutate(`HadGEM2-ES` = rowSums(HadGEM_Outflow_Stn[c(2:11)]))
colnames(HadGEM_Outflow_Stn) <- c("node", "HadGEM2-ES")
HadGEM_Outflow_Stn
MIROC_Outflow_Stn <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/stanislaus/gcms/MIROC5_rcp45/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1, 4)]
#MIROC_Outflow_Stn <- MIROC_Outflow_Stn %>%
# mutate(MIROC5 = rowSums(MIROC_Outflow_Stn[c(2:11)]))
colnames(MIROC_Outflow_Stn) <- c("node", "MIROC5")
MIROC_Outflow_Stn
```
```{r}
Livneh_Stn_Outflow <- Livneh_Outflow_Stn
Livneh_Stn_Outflow <- melt(Livneh_Stn_Outflow, id = "node")
Livneh_Stn_Outflow
Outflow_Stn <- cbind(CanES_Outflow_Stn, CNRM_Outflow_Stn[-1],
HadGEM_Outflow_Stn[-1], MIROC_Outflow_Stn[-1])
Outflow_Stn
Outflow_Stn2 <- melt(Outflow_Stn, id = "node")
Outflow_Stn2
```
```{r}
Outflow_Stn2 <- rbind(Outflow_Stn2, Livneh_Stn_Outflow) %>%
mutate(Month = as.factor(format(as.Date(node, format = "%B"), "%b")),
Year = water_year(node, origin = "usgs"),
Scenario = as.factor("RCP 4.5")) %>%
group_by(Year, Month, variable) %>%
dplyr::summarize(MonthlyTotal = sum(value))
Outflow_Stn2
Outflow_Stn2$variable <- factor(Outflow_Stn2$variable, levels = c("Livneh (Historical)", "HadGEM2-ES", "CanESM2", "MIROC5", "CNRM-CM5"))
Outflow_Stn2
Outflow_Stn3 <- Outflow_Stn2 %>%
group_by(Year, variable) %>%
dplyr::summarize(AnnualTotal = sum(MonthlyTotal))
Outflow_Stn3
```
```{r}
ggplot(Outflow_Stn2) +
theme_bw(base_size=12, base_family='Times New Roman') + #change font to Times New Roman, 12pt, Bold
geom_boxplot(aes( x = Month, y = MonthlyTotal, fill = variable), outlier.alpha = 0.3) + #plot monthly observed data in greenish blue
#geom_line(aes(x = node, y = value)) +
# scale_y_continuous(limits = c(0, NA),
# expand = c(0, NA),
# labels = comma) +
# scale_x_discrete(limits=c("Oct","Nov","Dec", "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep"))+
scale_fill_manual(values = c("#5A5A5A", "#E69F00", "#F0E442", "#009E73", "#56B4E9")) +
scale_y_log10(breaks=c(0, 0.1,1,10,100,1000), labels=comma)+
labs(fill = "RCP 4.5",
title = "Stanislaus River",
x = element_blank(),
y = "Total River Outflow (mcm/month)") + #name of x axis
theme(legend.position = "bottom",
legend.direction = "horizontal",
legend.box.margin = margin(t = -17),
plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
strip.placement = "outside",
strip.background = element_blank(),
panel.spacing.y = unit(0, "lines"))+
png("Stn_outflow_GCMs_logscale.png", units ="in", width=8, height=5, res = 300)
```
```{r}
ggplot(Outflow_Stn2) +
theme_bw(base_size=12, base_family='Times New Roman') + #change font to Times New Roman, 12pt, Bold
geom_boxplot(aes( x = Month, y = MonthlyTotal, fill = variable), outlier.alpha = 0.3) + #plot monthly observed data in greenish blue
#geom_line(aes(x = node, y = value)) +
scale_y_continuous(limits = c(0, NA),
expand = c(0, NA),
labels = comma) +
# scale_x_discrete(limits=c("Oct","Nov","Dec", "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep"))+
scale_fill_manual(values = c("#5A5A5A", "#E69F00", "#F0E442", "#009E73", "#56B4E9")) +
#scale_y_log10(breaks=c(0, 0.1,1,10,100,1000), labels=comma)+
labs(fill = "RCP 4.5",
title = "Stanislaus River",
x = element_blank(),
y = "Total River Outflow (mcm/month)") + #name of x axis
theme(legend.position = "bottom",
legend.direction = "horizontal",
legend.box.margin = margin(t = -17),
plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
strip.placement = "outside",
strip.background = element_blank(),
panel.spacing.y = unit(0, "lines"))+
png("Stn_outflow_GCMs.png", units ="in", width=8, height=5, res = 300)
```
```{r}
#annual aggreagate
ggplot(Outflow_Stn3) +
theme_bw(base_size=12, base_family='Times New Roman') + #change font to Times New Roman, 12pt, Bold
geom_violin(draw_quantiles = c(.25, .5, .75), aes( x = variable, y = AnnualTotal, fill = variable)) + #plot monthly observed data in greenish blue
#geom_line(aes(x = node, y = value)) +
scale_y_continuous(limits = c(0, NA),
expand = c(0, NA),
labels = comma) +
# scale_y_log10(breaks=c(-10000000,-1000000,-100000,-10000, -1000, -100, -10, 0.1,1,10,100,1000), labels=c(-10000000,-1000000,-100000,-10000, -1000, -100, -10, 0.1,1,10,100,1000))+
scale_x_discrete(limits=c("Livneh (Historical)", "HadGEM2-ES", "CanESM2", "MIROC5", "CNRM-CM5"))+
scale_fill_manual(values = c("#5A5A5A", "#E69F00", "#F0E442", "#009E73", "#56B4E9")) +
labs(subtitle = "RCP 4.5 Scenario",
title = "Stanislaus River",
x = element_blank(),
y = "Total River Outflow (mcm/year)") + #name of x axis
theme(legend.position = "none",
#legend.direction = "horizontal",
#legend.box.margin = margin(t = -19),
plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
strip.placement = "outside",
strip.background = element_blank(),
panel.spacing.y = unit(0, "lines"))+
png("Stn_outflow_GCMs2.png", units ="in", width=8, height=5, res = 300)
```
```{r}
Livneh_Outflow_USJ <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/upper_san_joaquin/historical/Livneh/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,4)]
Livneh_Outflow_USJ <-Livneh_Outflow_USJ %>%
# mutate(Livneh = rowSums(Livneh_Outflow_Stn[c(2:11)])) %>%
filter(between(node, as.Date("1980-10-01"), as.Date("2010-09-30")))
colnames(Livneh_Outflow_USJ) <- c("node", "Livneh (Historical)")
Livneh_Outflow_USJ
CanES_Outflow_USJ <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/upper_san_joaquin/gcms/CanESM2_rcp45/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,4)]
#CanES_Outflow_Stn <- CanES_Outflow_Stn %>%
# mutate(CanESM2 = rowSums(CanES_Outflow_Stn[c(2:11)]))
colnames(CanES_Outflow_USJ) <- c("node", "CanESM2")
CanES_Outflow_USJ
CNRM_Outflow_USJ <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/upper_san_joaquin/gcms/CNRM-CM5_rcp45/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,4)]
#CNRM_Outflow_Stn <- CNRM_Outflow_Stn %>%
# mutate(`CNRM-CM5` = rowSums(CNRM_Outflow_Stn[c(2:11)]))
colnames(CNRM_Outflow_USJ) <- c("node", "CNRM-CM5")
CNRM_Outflow_USJ
HadGEM_Outflow_USJ <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/upper_san_joaquin/gcms/HadGEM2-ES_rcp45/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,4)]
#HadGEM_Outflow_Stn <- HadGEM_Outflow_Stn %>%
# mutate(`HadGEM2-ES` = rowSums(HadGEM_Outflow_Stn[c(2:11)]))
colnames(HadGEM_Outflow_USJ) <- c("node", "HadGEM2-ES")
HadGEM_Outflow_USJ
MIROC_Outflow_USJ <- read_csv("C:/Users/gusta/Box/VICE Lab/RESEARCH/PROJECTS/CERC-WET/Task7_San_Joaquin_Model/Pywr models/results/Binary IFRs x Prices/upper_san_joaquin/gcms/MIROC5_rcp45/Output_Flow_mcm.csv", col_types = cols(node = col_date(), .default = col_double()))[-c(1:3), c(1,4)]
#MIROC_Outflow_Stn <- MIROC_Outflow_Stn %>%
# mutate(MIROC5 = rowSums(MIROC_Outflow_Stn[c(2:11)]))
colnames(MIROC_Outflow_USJ) <- c("node", "MIROC5")
MIROC_Outflow_USJ
```
```{r}
Livneh_USJ_Outflow <- Livneh_Outflow_USJ
Livneh_USJ_Outflow <- melt(Livneh_USJ_Outflow, id = "node")
Livneh_USJ_Outflow
Outflow_USJ <- cbind(CanES_Outflow_USJ, CNRM_Outflow_USJ[-1],
HadGEM_Outflow_USJ[-1], MIROC_Outflow_USJ[-1])
Outflow_USJ
Outflow_USJ2 <- melt(Outflow_USJ, id = "node")
Outflow_USJ2
```
```{r}
Outflow_USJ2 <- rbind(Outflow_USJ2, Livneh_USJ_Outflow) %>%
mutate(Month = as.factor(format(as.Date(node, format = "%B"), "%b")),
Year = water_year(node, origin = "usgs"),
Scenario = as.factor("RCP 4.5")) %>%
group_by(Year, Month, variable) %>%
dplyr::summarize(MonthlyTotal = sum(value))
Outflow_USJ2
Outflow_USJ2$variable <- factor(Outflow_USJ2$variable, levels = c("Livneh (Historical)", "HadGEM2-ES", "CanESM2", "MIROC5", "CNRM-CM5"))
Outflow_USJ2
Outflow_USJ3 <- Outflow_USJ2 %>%
group_by(Year, variable) %>%
dplyr::summarize(AnnualTotal = sum(MonthlyTotal))
Outflow_USJ3
```
```{r}
ggplot(Outflow_USJ2) +
theme_bw(base_size=12, base_family='Times New Roman') + #change font to Times New Roman, 12pt, Bold
geom_boxplot(aes( x = Month, y = MonthlyTotal, fill = variable), outlier.alpha = 0.3) + #plot monthly observed data in greenish blue
#geom_line(aes(x = node, y = value)) +
# scale_y_continuous(limits = c(0, NA),
# expand = c(0, NA),
# labels = comma) +
scale_x_discrete(limits=c("Oct","Nov","Dec", "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep"))+
scale_fill_manual(values = c("#5A5A5A", "#E69F00", "#F0E442", "#009E73", "#56B4E9")) +
scale_y_log10(breaks=c(0, 0.1,1,10,100,1000), labels=comma)+
labs(fill = "RCP 4.5",
title = "Upper San Joaquin River",
x = element_blank(),
y = "Total River Outflow (mcm/month)") + #name of x axis
theme(legend.position = "bottom",
legend.direction = "horizontal",
legend.box.margin = margin(t = -17),
plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
strip.placement = "outside",
strip.background = element_blank(),
panel.spacing.y = unit(0, "lines"))+
png("USJ_outflow_GCMs_logscale.png", units ="in", width=8, height=5, res = 300)
```
```{r}
ggplot(Outflow_USJ2) +
theme_bw(base_size=12, base_family='Times New Roman') + #change font to Times New Roman, 12pt, Bold
geom_boxplot(aes( x = Month, y = MonthlyTotal, fill = variable), outlier.alpha = 0.3) + #plot monthly observed data in greenish blue
#geom_line(aes(x = node, y = value)) +
scale_y_continuous(limits = c(0, NA),
expand = c(0, NA),
labels = comma) +
scale_x_discrete(limits=c("Oct","Nov","Dec", "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep"))+
scale_fill_manual(values = c("#5A5A5A", "#E69F00", "#F0E442", "#009E73", "#56B4E9")) +
# scale_y_log10(breaks=c(-10000000,-1000000,-100000,-10000, -1000, -100, -10, 0.1,1,10,100,1000), labels=c(-10000000,-1000000,-100000,-10000, -1000, -100, -10, 0.1,1,10,100,1000))+
labs(fill = "RCP 4.5",
title = "Upper San Joaquin River",
x = element_blank(),
y = "Total River Outflow (mcm/month)") + #name of x axis
theme(legend.position = "bottom",
legend.direction = "horizontal",
legend.box.margin = margin(t = -17),
plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
strip.placement = "outside",
strip.background = element_blank(),
panel.spacing.y = unit(0, "lines"))+
png("USJ_outflow_GCMs.png", units ="in", width=8, height=5, res = 300)
```
```{r}
#annual aggreagate
ggplot(Outflow_USJ3) +
theme_bw(base_size=12, base_family='Times New Roman') + #change font to Times New Roman, 12pt, Bold
geom_violin(draw_quantiles = c(.25, .5, .75), aes( x = variable, y = AnnualTotal, fill = variable)) + #plot monthly observed data in greenish blue
#geom_line(aes(x = node, y = value)) +
scale_y_continuous(limits = c(0, NA),
expand = c(0, NA),
labels = comma) +
# scale_y_log10(breaks=c(-10000000,-1000000,-100000,-10000, -1000, -100, -10, 0.1,1,10,100,1000), labels=c(-10000000,-1000000,-100000,-10000, -1000, -100, -10, 0.1,1,10,100,1000))+
scale_x_discrete(limits=c("Livneh (Historical)", "HadGEM2-ES", "CanESM2", "MIROC5", "CNRM-CM5"))+
scale_fill_manual(values = c("#5A5A5A", "#E69F00", "#F0E442", "#009E73", "#56B4E9")) +
labs(subtitle = "RCP 4.5 Scenario",
title = "Upper San Joaquin River",
x = element_blank(),
y = "Total River Outflow (mcm/year)") + #name of x axis
theme(legend.position = "none",
#legend.direction = "horizontal",
#legend.box.margin = margin(t = -19),
plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
strip.placement = "outside",
strip.background = element_blank(),
panel.spacing.y = unit(0, "lines"))+
png("USJ_outflow_GCMs2.png", units ="in", width=8, height=5, res = 300)
```
```{r}
#Facet wraps of all basins
Outflow_Mer2$Basin <- "Merced River"
Outflow_Mer3$Basin <- "Merced River"
Outflow_Tuo2$Basin <- "Tuolumne River"
Outflow_Tuo3$Basin <- "Tuolumne River"
Outflow_Stn2$Basin <- "Stanislaus River"
Outflow_Stn3$Basin <- "Stanislaus River"
Outflow_USJ2$Basin <- "Upper San Joaquin River"
Outflow_USJ3$Basin <- "Upper San Joaquin River"
all_Outflow_monthly <- rbind(Outflow_Mer2, Outflow_Tuo2, Outflow_Stn2 ,Outflow_USJ2)
all_Outflow_monthly$Basin <- factor(all_Outflow_monthly$Basin, levels = c("Stanislaus River", "Tuolumne River", "Merced River", "Upper San Joaquin River"))
all_Outflow_monthly
all_Outflow_annual <- rbind(Outflow_Mer3, Outflow_Tuo3, Outflow_Stn3 ,Outflow_USJ3)
all_Outflow_annual$Basin <- factor(all_Outflow_annual$Basin, levels = c("Stanislaus River", "Tuolumne River", "Merced River", "Upper San Joaquin River"))
all_Outflow_annual
```
```{r}
all_Outflow_monthly$Month <- factor(all_Outflow_monthly$Month, levels = c("Oct", "Nov", "Dec", "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep"))
all_Outflow_monthly
All_Montlhy_Stats_Outflow <- aggregate(MonthlyTotal ~ Month+variable+Basin, all_Outflow_monthly, summary)
write.csv(All_Montlhy_Stats_Outflow, "All_Monthly_Stats_Outflow_mcm_rcp45_2045prices.csv")
All_Annual_Stats_Outflow <- aggregate(AnnualTotal ~ variable+Basin, all_Outflow_annual, summary)
write.csv(All_Annual_Stats_Outflow, "All_Annual_Stats_Outflow_mcm_rcp45_2045prices.csv")
all_Outflow_annual
```
```{r}
ggplot(all_Outflow_monthly) +
theme_bw(base_size=12, base_family='Times New Roman') + #change font to Times New Roman, 12pt, Bold
geom_boxplot(aes( x = Month, y = MonthlyTotal, fill = variable), outlier.alpha = 0.3) + #plot monthly observed data in greenish blue
#geom_line(aes(x = node, y = value)) +
# scale_y_log10(breaks=c(0,1,10,100,1000), labels=scales::comma)+
scale_y_continuous(limits = c(0, NA),
expand = c(0, NA),
labels = scales::comma) +
scale_x_discrete(limits=c("Oct","Nov","Dec", "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep"))+
scale_fill_manual(values = c("#5A5A5A", "#E69F00", "#F0E442", "#009E73", "#56B4E9")) +
labs(fill = "RCP 4.5",
#title = "Upper San Joaquin River",
x = element_blank(),
y = "Total River Outflow (mcm/month)") + #name of x axis
theme(legend.position = "bottom",
legend.direction = "horizontal",
legend.box.margin = margin(t = -17),
plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
strip.placement = "outside",
strip.background = element_blank(),
panel.spacing.y = unit(0, "lines"))+
facet_wrap(~Basin, scales = "free_y")+
png("AllBasins_outflow_GCMs_RCP8.5.png", units ="in", width=8, height=5, res = 300)
```
```{r}
#annual aggreagate
ggplot(all_Outflow_annual) +
theme_bw(base_size=12, base_family='Times New Roman') + #change font to Times New Roman, 12pt, Bold
geom_violin(draw_quantiles = c(.25, .5, .75), aes( x = variable, y = AnnualTotal, fill = variable)) + #plot monthly observed data in greenish blue
#geom_line(aes(x = node, y = value)) +
scale_y_continuous(limits = c(0, NA),
expand = c(0, NA),
labels = scales::comma) +
scale_x_discrete(limits=c("Livneh (Historical)", "HadGEM2-ES", "CanESM2", "MIROC5", "CNRM-CM5"))+
scale_fill_manual(values = c("#5A5A5A", "#E69F00", "#F0E442", "#009E73", "#56B4E9")) +
labs(fill = "RCP 4.5",
#title = "Upper San Joaquin River",
x = element_blank(),
y = "Total River Outflow (mcm/year)") + #name of x axis
theme(legend.position = "bottom",
legend.direction = "horizontal",
legend.box.margin = margin(t = -17),
axis.ticks.x=element_blank(),
axis.text.x=element_blank(),
plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
strip.placement = "outside",
strip.background = element_blank(),
legend.text = element_text(size = 9),
legend.key.size = unit(0.75,"line"),
panel.spacing.y = unit(0, "lines"))+
facet_wrap(~Basin, scales = "free_y")+
png("AllBasins_outflow_GCMs2_RCP8.5.png", units ="in", width=8, height=5, res = 300)
```