Stage vs CFS at USGS Naomi Gage Station

setwd('C:\\Users\\Jack\\Documents\\AB\\PVA MS Sturgeon 2019')
rawDat <- read.table('USGS Naomi stage cfs.txt', header = TRUE, sep = "\t")
dat <- rawDat
names(dat) <- c("agency", "site", "date", "stage", "stageStatus", "cfs", "cfsStatus")
head(dat)

Make a new data set that only uses the data that are ready for publication, ignoring provisional data

dat2 <- dat[dat$stageStatus == "A" & dat$cfsStatus == "A",]

plot(dat2$cfs, dat2$stage, log = "xy")

fit1 <- lm(log(stage) ~ log(cfs), data = dat2, na.action = na.exclude)
fit1

Call:
lm(formula = log(stage) ~ log(cfs), data = dat2, na.action = na.exclude)

Coefficients:
(Intercept)     log(cfs)  
    -1.9449       0.4525  

summary(fit1)

Call:
lm(formula = log(stage) ~ log(cfs), data = dat2, na.action = na.exclude)

Residuals:
     Min       1Q   Median       3Q      Max 
-3.09717  0.03726  0.07940  0.12018  0.76888 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) -1.94488    0.18622  -10.44   <2e-16 ***
log(cfs)     0.45245    0.02882   15.70   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4186 on 783 degrees of freedom
Multiple R-squared:  0.2395,    Adjusted R-squared:  0.2385 
F-statistic: 246.5 on 1 and 783 DF,  p-value: < 2.2e-16

plot(dat2$cfs, residuals(fit1))