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#several improvements

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Valentin Heimhuber 7 years ago
parent 6baeb9c237
commit c5f2f4f743
1 changed files with 232 additions and 37 deletions
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Analysis/Code/ggplot_time_series_with_trends.R
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@ -19,18 +19,40 @@ setwd("C:/Users/z5025317/OneDrive - UNSW/WRL_Postdoc_Manual_Backup/WRL_Postdoc/P
#Set inputs #Set inputs
###################### ######################
Case.Study <- "CASESTUDY2" Case.Study <- "CASESTUDY2"
Estuary <- "HUNTER" Estuary <- "RICHMOND"
Climvar <- 'tasmean' Riv.Gauge.loc <- "OAKLANDROAD" #GRETA
ggplotGAM.k <- 14 Est.Gauge.loc <- "CORAKI" #"RAYMONDTERRACE" # "HEXHAMBRIDGE"
logtransformFlow <- TRUE
ggplotGAM.k <- 15
rivTempGAM.k <- 20
Version <- 'V2'
###################### ######################
######################
Output.Directory <- paste('./Output/', Case.Study, '/', Estuary,'/Recent_Trends/Riv_', Riv.Gauge.loc,'_Est_',Est.Gauge.loc,'_GAMk', ggplotGAM.k, '/', sep="")
if (file.exists(Output.Directory)){
print('output folder already existed and was not created again')
} else {
dir.create(file.path(Output.Directory))
print('output folder did not exist and was created')
}
######################
###################### ######################
#Set input file paths #Set input file paths
###################### ######################
AirT_CSV_Path <- "./Data/SILO/CASESTUDY2/HUNTER/SILO_climdata_HUNTER_Catchment_-32.162479_150.5335812.csv"
RivT_CSV_Path <- "./Data/River_Gauge_Data/HUNTER_210064_20180615/210064_Temp.csv" pattern = paste('SILO_climdata_', Estuary,'*', sep="")
SST_CSV_Path <- './Data/NARCLIM_Site_CSVs/CASESTUDY2/HUNTER_32.751_151.690/sstmean_NNRP_HUNTER_33.034_152.156_NARCliM_summary.csv' AirT_CSV_Path <- list.files(paste("./Data/SILO/",Case.Study, '/',sep=""), pattern, full.names=T, recursive=T)
pattern = paste(Estuary,'@', Riv.Gauge.loc, '.*.ALL.csv', sep="")
RivT_CSV_Path <- list.files("./Data/River_Gauge_Data/", pattern, full.names=T)
pattern = paste(Estuary,'@', Est.Gauge.loc, '.*.ALL.csv', sep="")
EstT_CSV_Path <- list.files("./Data/River_Gauge_Data/", pattern, full.names=T)
pattern = paste('sstmean_NNRP_', Estuary,'*', sep="")
SST_CSV_Path <- list.files(paste("./Data/NARCLIM_Site_CSVs/",Case.Study, '/', sep=""), pattern, full.names=T, recursive=T)
###################### ######################
@ -62,9 +84,21 @@ AirT.full.lintrend <- summary(linear.trend.model_EC_all )$coefficients[2,1] * 35
############River temp ############River temp
#Load a daily (no gaps) time series as a time serie baseline for other time series used here #Load a daily (no gaps) time series as a time serie baseline for other time series used here
#Here we use the raw DPI CSV format that comes with a bunch of metadata
RivT.df <- data.frame(read.csv(RivT_CSV_Path)) RivT.df <- data.frame(read.csv(RivT_CSV_Path))
RivT.full.TS <- zoo(RivT.df$Temp, order.by= as.Date(RivT.df[,"Date"], format = "%d/%m/%Y")) #=daily time series of rainfall for creation of clean, daily TS of ET and Q char.df <- data.frame(lapply(RivT.df[2,], as.character), stringsAsFactors=FALSE)
RivT.TS <- window(RivT.full.TS, start=as.Date("1995-01-01"), end=as.Date("2018-01-01")) #dat <- data.frame(lapply(RivT.df[(4:nrow(RivT.df)),(2:ncol(RivT.df))], as.numeric), stringsAsFactors=FALSE)
#dat <- RivT.df.num[!is.na(as.numeric(as.character(RivT.df.num))),]
dat <- RivT.df[(4:nrow(RivT.df)),]
colnames(dat) <- lapply(RivT.df[2,], as.character)
dat$Date <- gsub(x=dat$Date,pattern="00:00:00",replacement="",fixed=T)
colnames(dat) <- gsub(x=colnames(dat),pattern="Water Temp(C)",replacement="Temp",fixed=T)
RivT.df <- dat
rm(dat,char.df)
RivT.full.TS <- zoo(as.numeric(as.character(RivT.df$Temp)), order.by= as.Date(RivT.df[,"Date"], format = "%d/%m/%Y")) #=daily time series of rainfall for creation of clean, daily TS of ET and Q
RivT.full.TS <- window(RivT.full.TS, start=as.Date("1995-07-01"), end=as.Date("2018-01-01"))
RivT.full.TS <- na.approx(RivT.full.TS)
RivT.TS <- RivT.full.TS
RivT.full.df <- data.frame(RivT.TS) ### This is only done because RivT.full.df <- data.frame(RivT.TS) ### This is only done because
RivT.df <- data.frame(RivT.TS) RivT.df <- data.frame(RivT.TS)
colnames(RivT.df) <- 'rivTmean' colnames(RivT.df) <- 'rivTmean'
@ -80,6 +114,37 @@ RivT.full.pvalNCV_ECall <- summary(linear.trend.model_EC_all )$coefficients[2,4]
RivT.full.lintrend <- summary(linear.trend.model_EC_all )$coefficients[2,1] * 356 RivT.full.lintrend <- summary(linear.trend.model_EC_all )$coefficients[2,1] * 356
############River temp ############River temp
############River flow
#Load a daily (no gaps) time series as a time serie baseline for other time series used here
#Here we use the raw DPI CSV format that comes with a bunch of metadata
RivQ.df <- data.frame(read.csv(RivT_CSV_Path))
char.df <- data.frame(lapply(RivQ.df[2,], as.character), stringsAsFactors=FALSE)
dat <- RivQ.df[(4:nrow(RivQ.df)),]
colnames(dat) <- lapply(RivQ.df[2,], as.character)
dat$Date <- gsub(x=dat$Date,pattern="00:00:00",replacement="",fixed=T)
colnames(dat) <- gsub(x=colnames(dat), pattern="Discharge (ML/d)",replacement="Flow",fixed=T)
RivQ.df <- dat
rm(dat,char.df)
#RivQ.full.TS <- zoo(log10((as.numeric(as.character(RivQ.df$Flow))) +1) , order.by= as.Date(RivQ.df[,"Date"], format = "%d/%m/%Y")) #=daily time series of rainfall for creation of clean, daily TS of ET and Q
RivQ.full.TS <- zoo(as.numeric(as.character(RivQ.df$Flow)), order.by= as.Date(RivQ.df[,"Date"], format = "%d/%m/%Y")) #=daily time series of rainfall for creation of clean, daily TS of ET and Q
RivQ.TS <- window(RivQ.full.TS, start=as.Date("1990-01-01"), end=as.Date("2018-01-01"))
RivQ.full.df <- data.frame(RivQ.full.TS) ### This is only done because
RivQ.df <- data.frame(RivQ.TS)
colnames(RivQ.df) <- 'RivQmean'
colnames(RivQ.full.df) <- 'RivQmean'
############trends
RivQ.df$Julday1 <- seq(1,length(RivQ.df[,1]),1)
linear.trend.model_EC_all <- lm(RivQmean ~ Julday1, RivQ.df)
RivQ.pvalNCV_ECall <- summary(linear.trend.model_EC_all )$coefficients[2,4]
RivQ.lintrend <- summary(linear.trend.model_EC_all )$coefficients[2,1] * 356
RivQ.full.df$Julday1 <- seq(1,length(RivQ.full.df[,1]),1)
linear.trend.model_EC_all <- lm(RivQmean ~ Julday1, RivQ.full.df)
RivQ.full.pvalNCV_ECall <- summary(linear.trend.model_EC_all )$coefficients[2,4]
RivQ.full.lintrend <- summary(linear.trend.model_EC_all )$coefficients[2,1] * 356
############River Flow
############ SST ############ SST
#Load a daily (no gaps) time series as a time serie baseline for other time series used here #Load a daily (no gaps) time series as a time serie baseline for other time series used here
SST.df <- data.frame(read.csv(SST_CSV_Path)) SST.df <- data.frame(read.csv(SST_CSV_Path))
@ -102,6 +167,42 @@ SST.lintrend <- summary(linear.trend.model_EC_all2)$coefficients[2,1] * 356
############ SST ############ SST
############Estuary temp
#Load a daily (no gaps) time series as a time serie baseline for other time series used here
#Here we use the raw DPI CSV format that comes with a bunch of metadata
EstT.df <- data.frame(read.csv(EstT_CSV_Path))
char.df <- data.frame(lapply(EstT.df[2,], as.character), stringsAsFactors=FALSE)
#dat <- data.frame(lapply(EstT.df[(4:nrow(EstT.df)),(2:ncol(EstT.df))], as.numeric), stringsAsFactors=FALSE)
#dat <- EstT.df.num[!is.na(as.numeric(as.character(EstT.df.num))),]
dat <- EstT.df[(4:nrow(EstT.df)),]
colnames(dat) <- lapply(EstT.df[2,], as.character)
dat$Date <- gsub(x=dat$Date,pattern="00:00:00",replacement="",fixed=T)
colnames(dat) <- gsub(x=colnames(dat),pattern="Water Temp(C)",replacement="Temp",fixed=T)
EstT.df <- dat
rm(dat,char.df)
#replace negative values with NA
EstT.df$Temp <- replace(EstT.df$Temp, which(as.numeric(as.character(EstT.df$Temp)) < 11), NA)
EstT.full.TS <- zoo(as.numeric(as.character(EstT.df$Temp)), order.by= as.Date(EstT.df[,"Date"], format = "%d/%m/%Y")) #=daily time series of rainfall for creation of clean, daily TS of ET and Q
plot(EstT.full.TS)
EstT.TS <- window(EstT.full.TS, start=as.Date("2013-06-01"), end=as.Date("2018-01-01"))
EstT.full.TS <- EstT.TS
EstT.full.df <- data.frame(EstT.TS) ### This is only done because of poor data at beginning
EstT.df <- data.frame(EstT.TS)
colnames(EstT.df) <- 'EstTmean'
colnames(EstT.full.df) <- 'EstTmean'
############
EstT.df$Julday1 <- seq(1,length(EstT.df[,1]),1)
linear.trend.model_EC_all <- lm(EstTmean ~ Julday1, EstT.df)
EstT.pvalNCV_ECall <- summary(linear.trend.model_EC_all )$coefficients[2,4]
EstT.lintrend <- summary(linear.trend.model_EC_all )$coefficients[2,1] * 356
EstT.full.df$Julday1 <- seq(1,length(EstT.full.df[,1]),1)
linear.trend.model_EC_all <- lm(EstTmean ~ Julday1, EstT.full.df)
EstT.full.pvalNCV_ECall <- summary(linear.trend.model_EC_all )$coefficients[2,4]
EstT.full.lintrend <- summary(linear.trend.model_EC_all )$coefficients[2,1] * 356
############Est temp
###################### ######################
#Plot #Plot
@ -110,57 +211,91 @@ SST.lintrend <- summary(linear.trend.model_EC_all2)$coefficients[2,1] * 356
##################################### Full Time Period ##################################### Full Time Period
#Air temp Full period #Air temp Full period
p1air <- ggplot(AirT.full.df, aes(y=tasmean, x=index(AirT.full.TS))) + geom_line(alpha=0.5) + p1air <- ggplot(AirT.full.df, aes(y=tasmean, x=index(AirT.full.TS))) + geom_line(alpha=0.5) +
ggtitle(paste(Estuary, " - Linear and smooth trend in catchment airT (SILO) lin trend was ", ggtitle(paste(Estuary," Catchment Centroid - Linear and smooth trend in catchment airT (SILO) lin trend was ",
round(AirT.full.lintrend,3), ' C°/year with p=', round(AirT.full.pvalNCV_ECall,10), sep=" ")) + round(AirT.full.lintrend,3), ' C°/year with p=', round(AirT.full.pvalNCV_ECall,10), sep=" ")) +
theme(plot.title=element_text(face="bold", size=9)) + theme(plot.title=element_text(face="bold", size=9)) +
geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) + geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) +
stat_smooth(method=gam, formula=y~s(x, k=ggplotGAM.k), se=T, size=0.5) + stat_smooth(method=gam, formula=y~s(x, k=ggplotGAM.k), se=T, size=0.5) +
ylab("Air Temperature [C°]") + xlab("Time") ylab("Air Temperature [C°]") + xlab("Time")
#Riv temp Full period
p1riv <- ggplot(RivT.full.df, aes(y=rivTmean, x=index(RivT.TS))) + geom_line(alpha=0.5) + p1riv <- ggplot(RivT.full.df, aes(y=rivTmean, x=index(RivT.TS))) + geom_line(alpha=0.5) +
ggtitle(paste(Estuary, " - Linear and smooth trend in river temperature (GAUGE) lin trend was ", ggtitle(paste(Estuary,'@', Riv.Gauge.loc, " - Linear and smooth trend in river temperature (GAUGE) lin trend was ",
round(RivT.full.lintrend,3), ' C°/year with p=', round(RivT.full.pvalNCV_ECall,10), sep=" ")) + round(RivT.full.lintrend,3), ' C°/year with p=', round(RivT.full.pvalNCV_ECall,10), sep=" ")) +
theme(plot.title=element_text(face="bold", size=9)) + theme(plot.title=element_text(face="bold", size=9)) +
geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) + geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) +
stat_smooth(method=gam, formula=y~s(x, k=ggplotGAM.k), se=T, size=0.5) + stat_smooth(method=gam, formula=y~s(x, k=ggplotGAM.k), se=T, size=0.5) +
ylab("River Temperature [C°]") + xlab("Time") ylab("River Temperature [C°]") + xlab("Time")
if(logtransformFlow ==TRUE){
p1rivQ <- ggplot(RivQ.full.df, aes(y=log10(RivQmean+2), x=index(RivQ.full.TS))) + geom_line(alpha=0.5) +
ggtitle(paste(Estuary,'@', Riv.Gauge.loc, " - Linear and smooth trend in river flow (GAUGE) lin trend was ",
round(RivQ.full.lintrend,3), ' ML/day /year with p=', round(RivQ.full.pvalNCV_ECall,10), sep=" ")) +
theme(plot.title=element_text(face="bold", size=9)) +
geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) +
stat_smooth(method=gam, formula=y~s(x, k=ggplotGAM.k), se=T, size=0.5) +
ylab(expression(paste("log10(River Flow [ML/day] + 2)", sep=""))) + xlab("Time")
} else {
p1rivQ <- ggplot(RivQ.full.df, aes(y=RivQmean, x=index(RivQ.full.TS))) + geom_line(alpha=0.5) +
ggtitle(paste(Estuary,'@', Riv.Gauge.loc, " - Linear and smooth trend in river flow (GAUGE) lin trend was ",
round(RivQ.full.lintrend,3), ' ML/day with p=', round(RivQ.full.pvalNCV_ECall,10), sep=" ")) +
theme(plot.title=element_text(face="bold", size=9)) +
geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) +
stat_smooth(method=gam, formula=y~s(x, k=ggplotGAM.k), se=T, size=0.5) +
ylab(expression(paste("River Flow [ML/day]", sep=""))) + xlab("Time")
}
#Sea temp Full period #Sea temp Full period
p1sst <- ggplot(SST.full.df, aes(y=SSTmean, x=index(SST.full.TS))) + geom_line(alpha=0.5) + p1sst <- ggplot(SST.full.df, aes(y=SSTmean, x=index(SST.full.TS))) + geom_line(alpha=0.5) +
ggtitle(paste(Estuary, " - Linear and smooth trend in sea surface temperature (NNRP) lin trend was ", ggtitle(paste(Estuary, "NNRP (NARCLIM reanalysis) - Linear and smooth trend in sea surface temperature (NNRP) lin trend was ",
round(SST.full.lintrend,3), ' C°/year with p=', round(SST.full.pvalNCV_ECall,10), sep=" ")) + round(SST.full.lintrend,3), ' C°/year with p=', round(SST.full.pvalNCV_ECall,10), sep=" ")) +
theme(plot.title=element_text(face="bold", size=9)) + theme(plot.title=element_text(face="bold", size=9)) +
geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) + geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) +
stat_smooth(method=gam, formula=y~s(x, k=ggplotGAM.k), se=T, size=0.5) + stat_smooth(method=gam, formula=y~s(x, k=ggplotGAM.k), se=T, size=0.5) +
ylab("Sea Surface Temperature [C°]") + xlab("Time") ylab("Sea Surface Temperature [C°]") + xlab("Time")
p1Est <- ggplot(EstT.full.df, aes(y=EstTmean, x=index(EstT.TS))) + geom_line(alpha=0.5) +
ggtitle(paste(Estuary,'@', Est.Gauge.loc, " - Linear and smooth trend in Estuary temperature (GAUGE) lin trend was ",
round(EstT.full.lintrend,3), ' C°/year with p=', round(EstT.full.pvalNCV_ECall,10), sep=" ")) +
theme(plot.title=element_text(face="bold", size=9)) +
geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) +
stat_smooth(method=gam, formula=y~s(x, k=ggplotGAM.k), se=T, size=0.5) +
ylab("Estuary Temperature [C°]") + xlab("Time")
#export to png #export to png
png.name <- paste('./Output/', Case.Study, '/', Estuary, '/Trends_tasmean_full_period_', Sys.Date(),".png", sep="") png.name <- paste(Output.Directory, Estuary, '@', Riv.Gauge.loc, '_Trends_tasmean_full_period_', Sys.Date(),".png", sep="")
png(file = png.name, width = 10.5, height = 7, units='in', res=500) png(file = png.name, width = 10.5, height = 7, units='in', res=500)
grid.arrange(p1air,ncol=1) grid.arrange(p1air,ncol=1)
dev.off() dev.off()
png.name <- paste('./Output/', Case.Study, '/', Estuary, '/Trends_rivTmean_full_period_', Sys.Date(),".png", sep="") png.name <- paste(Output.Directory, Estuary, '@', Riv.Gauge.loc, '_Trends_rivTmean_full_period_', Sys.Date(),".png", sep="")
png(file = png.name, width = 10.5, height = 7, units='in', res=500) png(file = png.name, width = 10.5, height = 7, units='in', res=500)
grid.arrange(p1riv,ncol=1) grid.arrange(p1riv,ncol=1)
dev.off() dev.off()
png.name <- paste('./Output/', Case.Study, '/', Estuary, '/Trends_SSTmean_full_period_', Sys.Date(),".png", sep="") png.name <- paste(Output.Directory, Estuary, '@', Riv.Gauge.loc, '_Trends_RivQmean_full_period_', Sys.Date(),".png", sep="")
png(file = png.name, width = 10.5, height = 7, units='in', res=500)
grid.arrange(p1rivQ,ncol=1)
dev.off()
png.name <- paste(Output.Directory, Estuary, '@', Riv.Gauge.loc, '_Trends_SSTmean_full_period_', Sys.Date(),".png", sep="")
png(file = png.name, width = 10.5, height = 7, units='in', res=500) png(file = png.name, width = 10.5, height = 7, units='in', res=500)
grid.arrange(p1sst,ncol=1) grid.arrange(p1sst,ncol=1)
dev.off() dev.off()
png.name <- paste(Output.Directory, Estuary, '@', Est.Gauge.loc, '_Trends_estTmean_full_period_', Sys.Date(),".png", sep="")
png(file = png.name, width = 10.5, height = 7, units='in', res=500)
grid.arrange(p1Est,ncol=1)
dev.off()
##################################### Full Time Period ##################################### Full Time Period
######################### 1990-present ######################### 1990-present
combined.TS <- window(merge(AirT.full.TS, window(RivT.full.TS, start=as.Date("1995-01-01"), end=end(RivT.full.TS)), SST.full.TS, all=T), start=as.Date("1990-01-01"), end=end(AirT.full.TS)) combined.TS <- window(merge(AirT.full.TS, window(RivT.full.TS, start=as.Date("1995-01-01"), end=end(RivT.full.TS)), SST.full.TS,EstT.full.TS,RivQ.full.TS, all=T), start=as.Date("1990-01-01"), end=end(AirT.full.TS))
combined.df <- data.frame(combined.TS) combined.df <- data.frame(combined.TS)
colnames(combined.df) <- c('tasmean','rivTmean', 'SSTmean') colnames(combined.df) <- c('tasmean','rivTmean', 'SSTmean', 'EstTmean', 'rivQmean')
#Air temp #Air temp
p1air <- ggplot(combined.df, aes(y=tasmean, x=index(combined.TS))) + geom_line(alpha=0.5) + p2air <- ggplot(combined.df, aes(y=tasmean, x=index(combined.TS))) + geom_line(alpha=0.5) +
ggtitle(paste(Estuary, " - Linear and smooth trend in catchment airT (SILO) lin trend was ", ggtitle(paste(Estuary," Catchment centroid - Linear and smooth trend in catchment airT (SILO) lin trend was ",
round(AirT.lintrend,3), ' C°/year with p=', round(AirT.pvalNCV_ECall,10), sep=" ")) + round(AirT.lintrend,3), ' C°/year with p=', round(AirT.pvalNCV_ECall,10), sep=" ")) +
theme(plot.title=element_text(face="bold", size=9)) + theme(plot.title=element_text(face="bold", size=9)) +
geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) + geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) +
@ -168,49 +303,109 @@ p1air <- ggplot(combined.df, aes(y=tasmean, x=index(combined.TS))) + geom_line(a
ylab("Air Temperature [C°]") + xlab("Time") ylab("Air Temperature [C°]") + xlab("Time")
#Riv temp #Riv temp
p1riv <- ggplot(combined.df, aes(y=rivTmean, x=index(combined.TS))) + geom_line(alpha=0.5) + p2riv <- ggplot(combined.df, aes(y=rivTmean, x=index(combined.TS))) + geom_line(alpha=0.5) +
ggtitle(paste(Estuary, " - Linear and smooth trend in river temperature (GAUGE) lin trend was ", ggtitle(paste(Estuary,'@', Riv.Gauge.loc, " - Linear and smooth trend in river temperature (GAUGE) lin trend was ",
round(RivT.lintrend,3), ' C°/year with p=', round(RivT.pvalNCV_ECall,10), sep=" ")) + round(RivT.lintrend,3), ' C°/year with p=', round(RivT.pvalNCV_ECall,10), sep=" ")) +
theme(plot.title=element_text(face="bold", size=9)) + theme(plot.title=element_text(face="bold", size=9)) +
geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) + geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) +
stat_smooth(method=gam, formula=y~s(x, k=ggplotGAM.k), se=T, size=0.5) + stat_smooth(method=gam, formula=y~s(x, k=ggplotGAM.k), se=T, size=0.5) +
ylab("River Temperature [C°]") + xlab("Time") ylab("River Temperature [C°]") + xlab("Time")
#Riv flow
if(logtransformFlow ==TRUE){
p2rivQ <- ggplot(combined.df, aes(y=log10(rivQmean+2), x=index(combined.TS))) + geom_line(alpha=0.5) +
ggtitle(paste(Estuary,'@', Riv.Gauge.loc, " - Linear and smooth trend in river flow (GAUGE) lin trend was ",
round(RivQ.full.lintrend,3), ' ML/day /year with p=', round(RivQ.full.pvalNCV_ECall,10), sep=" ")) +
theme(plot.title=element_text(face="bold", size=9)) +
geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) +
stat_smooth(method=gam, formula=y~s(x, k=ggplotGAM.k), se=T, size=0.5) +
ylab(expression(paste("log10(River Flow [ML/day] + 2)", sep=""))) + xlab("Time")
} else {
p2rivQ <- ggplot(combined.df, aes(y=rivQmean, x=index(combined.TS))) + geom_line(alpha=0.5) +
ggtitle(paste(Estuary,'@', Riv.Gauge.loc, " - Linear and smooth trend in river flow (GAUGE) lin trend was ",
round(RivT.lintrend,3), ' C°/year with p=', round(RivT.pvalNCV_ECall,10), sep=" ")) +
theme(plot.title=element_text(face="bold", size=9)) +
geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) +
stat_smooth(method=gam, formula=y~s(x, k=ggplotGAM.k), se=T, size=0.5) +
ylab(expression(paste("River Flow [ML/day]", sep=""))) + xlab("Time")
}
#Sea temp #Sea temp
p1sst <- ggplot(combined.df, aes(y=SSTmean, x=index(combined.TS))) + geom_line(alpha=0.5) + p2sst <- ggplot(combined.df, aes(y=SSTmean, x=index(combined.TS))) + geom_line(alpha=0.5) +
ggtitle(paste(Estuary, " - Linear and smooth trend in sea surface temperature (NNRP) lin trend was ", ggtitle(paste(Estuary,"NNRP(NARCLIM reanalysis) - Linear and smooth trend in sea surface temperature (NNRP) lin trend was ",
round(SST.lintrend,3), ' C°/year with p=', round(SST.pvalNCV_ECall,10), sep=" ")) + round(SST.lintrend,3), ' C°/year with p=', round(SST.pvalNCV_ECall,10), sep=" ")) +
theme(plot.title=element_text(face="bold", size=9)) + theme(plot.title=element_text(face="bold", size=9)) +
geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) + geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) +
stat_smooth(method=gam, formula=y~s(x, k=ggplotGAM.k), se=T, size=0.5) + stat_smooth(method=gam, formula=y~s(x, k=ggplotGAM.k), se=T, size=0.5) +
ylab("Sea Surface Temperature [C°]") + xlab("Time") ylab("Sea Surface Temperature [C°]") + xlab("Time")
#sst temp
p2Est <- ggplot(combined.df, aes(y=EstTmean, x=index(combined.TS))) + geom_line(alpha=0.5) +
ggtitle(paste(Estuary,'@', Est.Gauge.loc, " - Linear and smooth trend in Estuary temperature (GAUGE) lin trend was ",
round(EstT.lintrend,3), ' C°/year with p=', round(EstT.pvalNCV_ECall,10), sep=" ")) +
theme(plot.title=element_text(face="bold", size=9)) +
geom_smooth(method='lm',fill="green", formula=y~x, colour="darkgreen", size = 0.5) +
#stat_smooth(method=gam, formula=y~s(x, k=ggplotGAM.k), se=T, size=0.5) +
ylab("Estuary Temperature [C°]") + xlab("Time")
#export to png #export to png
png.name <- paste('./Output/', Case.Study, '/', Estuary, '/Trends_tasmean_1990-present_', Sys.Date(),".png", sep="") png.name <- paste(Output.Directory, Estuary, '@', Riv.Gauge.loc, '_Trends_tasmean_1990-present_', Sys.Date(),".png", sep="")
png(file = png.name, width = 10.5, height = 7, units='in', res=500) png(file = png.name, width = 10.5, height = 7, units='in', res=500)
grid.arrange(p1air,ncol=1) grid.arrange(p2air,ncol=1)
dev.off() dev.off()
png.name <- paste('./Output/', Case.Study, '/', Estuary, '/Trends_rivTmean_1990-present_', Sys.Date(),".png", sep="") png.name <- paste(Output.Directory, Estuary, '@', Riv.Gauge.loc, '_Trends_rivTmean_1990-present_', Sys.Date(),".png", sep="")
png(file = png.name, width = 10.5, height = 7, units='in', res=500) png(file = png.name, width = 10.5, height = 7, units='in', res=500)
grid.arrange(p1riv,ncol=1) grid.arrange(p2riv,ncol=1)
dev.off() dev.off()
png.name <- paste('./Output/', Case.Study, '/', Estuary, '/Trends_SSTmean_1990-present_', Sys.Date(),".png", sep="") png.name <- paste(Output.Directory, Estuary, '@', Riv.Gauge.loc, '_Trends_rivQmean_1990-present_', Sys.Date(),".png", sep="")
png(file = png.name, width = 10.5, height = 7, units='in', res=500) png(file = png.name, width = 10.5, height = 7, units='in', res=500)
grid.arrange(p1sst,ncol=1) grid.arrange(p2rivQ,ncol=1)
dev.off()
png.name <- paste(Output.Directory, Estuary, '@', Riv.Gauge.loc, '_Trends_SSTmean_1990-present_', Sys.Date(),".png", sep="")
png(file = png.name, width = 10.5, height = 7, units='in', res=500)
grid.arrange(p2sst,ncol=1)
dev.off() dev.off()
#export an overview plot as png #export an overview plot as png
gA <- ggplotGrob(p1air) gA <- ggplotGrob(p2air)
gB <- ggplotGrob(p1riv) gB <- ggplotGrob(p2riv)
gC <- ggplotGrob(p1sst) gC <- ggplotGrob(p2sst)
gA$widths <- gB$widths gD <- ggplotGrob(p2Est)
gC$widths <- gB$widths gE <- ggplotGrob(p2rivQ)
png.name <- paste('./Output/', Case.Study, '/', Estuary, '/Trends_Summary_1990-present_', Sys.Date(),".png", sep="") gA$widths <- gE$widths
gC$widths <- gE$widths
gD$widths <- gE$widths
gB$widths <- gE$widths
png.name <- paste(Output.Directory, Estuary, '@', Riv.Gauge.loc, '_Trends_SST_RivT_AirT_1990-present_', Sys.Date(),".png", sep="")
png(file = png.name, width = 10.5, height = 7, units='in', res=500) png(file = png.name, width = 10.5, height = 7, units='in', res=500)
grid.arrange(gA,gB ,gC,ncol=1) grid.arrange(gA,gB ,gC,ncol=1)
dev.off() dev.off()
png.name <- paste(Output.Directory, Estuary, '@', Riv.Gauge.loc, '_Trends_SST_RivT_EstT_1990-present_', Sys.Date(),".png", sep="")
png(file = png.name, width = 10.5, height = 7, units='in', res=500)
grid.arrange(gB,gD,gC,ncol=1)
dev.off()
png.name <- paste(Output.Directory, Estuary, '@', Riv.Gauge.loc, '_Trends_RivQ_RivT_EstT_1990-present_', Sys.Date(),".png", sep="")
png(file = png.name, width = 10.5, height = 7, units='in', res=500)
grid.arrange(gE,gB,gD,ncol=1)
dev.off()
png.name <- paste(Output.Directory, Estuary, '@', Riv.Gauge.loc, '_Trends_AirT_RivT_RivQ_1990-present_', Sys.Date(),".png", sep="")
png(file = png.name, width = 10.5, height = 7, units='in', res=500)
grid.arrange(gA,gB,gE,ncol=1)
dev.off()
png.name <- paste(Output.Directory, Estuary, '@', Riv.Gauge.loc, '_Trends_AirT_RivT_1990-present_', Sys.Date(),".png", sep="")
png(file = png.name, width = 10.5, height = 7, units='in', res=500)
grid.arrange(gA,gB,ncol=1)
dev.off()
png.name <- paste(Output.Directory, Estuary, '@', Riv.Gauge.loc, '_Trends_RivT_RivQ_1990-present_', Sys.Date(),".png", sep="")
png(file = png.name, width = 10.5, height = 7, units='in', res=500)
grid.arrange(gB,gE,ncol=1)
dev.off()

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