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I’ve heard quite a bit about the current problems with the Mississippi River and wanted to see for myself (with data) just how bad it is.
St Louis seems to be quite indicative of the severity of the situation, so I pulled the USGS “stream” records for it and also the historic low water level records for it and put them both into R for some analysis & graphing:
click for larger version
click for larger version
They are both in PDF format as well [1] [2]
As you can see, there have only been four other (recorded) times when the river was this low and it has just come off of multi-year severely high points with a fairly rapid trend downwards. I’m sure the residents along the Mississippi do not need this data to tell them just how bad things are, but it has helped me understand just how bad the situation is.
For those interested, the R code uses ggplot2 for time-series charting along with a custom theme and various annotation aids that might be useful to others learning their way around the grammar of graphics in R (so the code is below).
#
# stream.R - graph the recent history of the Mississippi River at St Louis
#
library(ggplot2)
require(scales)
library(ggthemes)
# read in st louis, mo USGS stream data
df.raw = read.csv("~/Desktop/stream.txt")
# need date/time as an R Date for ggplot2 time series plot
df = data.frame(as.POSIXct(df.raw$datetime,format = "%Y-%m-%d %H:%M"),df.raw$gauge)
df = df[!is.na(df.raw$gauge),]
# pretty up the column names
colnames(df) = c("datetime","gauge")
# we uses these a few times
maxdate = max(df$datetime)
mindate = min(df$datetime)
mingauge = min(df$gauge)
# do the plot
st1 = ggplot(df, aes(datetime, gauge)) +
theme_economist() + # pretty theme
# background bands for various water level stages
geom_rect(data=df,aes(xmin=mindate, xmax=maxdate, ymin=28, ymax=30), alpha=1, fill="khaki1") +
geom_rect(data=df,aes(xmin=mindate, xmax=maxdate, ymin=30, ymax=35), alpha=1, fill="gold1") +
geom_rect(data=df,aes(xmin=mindate, xmax=maxdate, ymin=35, ymax=40), alpha=1, fill="firebrick") +
geom_rect(data=df,aes(xmin=mindate, xmax=maxdate, ymin=mingauge, ymax=0), alpha=1, fill="white") +
# labels for the bands
geom_text(data=data.frame(x=maxdate,y=29), aes(x=x,y=y,label="Action Stage "), size=3, hjust=1) +
geom_text(data=data.frame(x=maxdate,y=32), aes(x=x,y=y,label="Flood Stage "), size=3, hjust=1) +
geom_text(data=data.frame(x=maxdate,y=37), aes(x=x,y=y,label="Moderate Flood Stage "), size=3, hjust=1, colour="white") +
geom_text(data=data.frame(x=mindate,y=mingauge/2), aes(x=x,y=y,label=" Below gauge"), size=3, hjust=0, colour="black") +
# the raw stream data
geom_line(size=0.15) +
# change the x label to just years
scale_x_datetime(breaks=date_breaks("years"), labels=date_format("%Y")) +
# labels
labs(title="Mississipi River Depth at St Louis, MO", x="", y="Gauge Height (in.)") +
# add a smoothed trend line
geom_smooth() +
# remove the legend
theme(legend.position = "none")
# make a PDF
ggsave("~/Desktop/mississippi.pdf",st1,w=8,h=5,dpi=150) |
#
# low.R - graph the historic low records for the Mississippi River at St Louis
#
library(ggplot2)
require(scales)
library(ggthemes)
# read in historic low records
df.raw = read.csv("~/Desktop/low.csv")
# need date/time as an R Date for ggplot2 time series plot
df = data.frame(as.POSIXct(df.raw$date,format = "%m/%d/%Y"),df.raw$gauge)
colnames(df) = c("date","gauge")
# pretty up the column names
maxdate = max(df$date)
mindate = min(df$date)
# do the plot
low1 = ggplot(data=df,aes(date,gauge)) +
geom_rect(data=df,aes(xmin=mindate, xmax=maxdate, ymin=-4.55, ymax=-4.55), alpha=1, color="firebrick",fill="firebrick") +
geom_text(data=data.frame(x=mindate,y=-4.75), aes(x=x,y=y,label="January 2013 :: -4.55in"), size=3, hjust=0, colour="firebrick") +
geom_line(size=0.15) +
labs(title="Historic Low Water Depths at St Louis, MO", x="", y="Gauge Height (in.)") +
theme_economist()
ggsave("~/Desktop/low.pdf",low1,w=8,h=5,dpi=150) |
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