In this exercise, we will calculate the runoff ratio for the Big Sandy River watershed. The runoff ratio will be used in the next module to build the gridded runoff model in GIS at the annual and monthly timescales.
Recall from Module 1 that the runoff ratio is calculated as the ratio of long-term mean streamflow to long-term mean precipitation, Q/P. Here we will call the long-term mean streamflow from Module 7 and long-term mean precipitation from Module 8.
MAF1<-read.csv("Qmm_mean_annual.csv",header=TRUE)
MAF1## X x
## 1 1 727.2195BigSandy_precip_yr<-read.csv("BigSandy_annual_average_P.csv",header=TRUE)
BigSandy_precip_yr## X V1
## 1 1 1257.708QP_annual <- MAF1/BigSandy_precip_yr
QP_annual## X x
## 1 1 0.5782102# The calculated runoff ratio for the Big Sandy watershed is 0.5782102. This is, rounding up, interpreted as "58% of annual precipitation become streamflow". Qmonth_mean<-read.csv("Q_mean_monthly.csv",header=TRUE)
Qmonth_mean## X x
## 1 Jan 85.16767
## 2 Feb 94.29354
## 3 Mar 116.33775
## 4 Apr 90.55266
## 5 May 73.95480
## 6 Jun 41.32014
## 7 Jul 28.71438
## 8 Aug 18.89000
## 9 Sep 16.20491
## 10 Oct 21.72974
## 11 Nov 57.07394
## 12 Dec 82.97996BigSandy_precip_mo<-read.csv("Bigsandy_monthly_precip_average.csv",header=TRUE)
BigSandy_precip_mo## X V1
## 1 1 98.27677
## 2 2 87.25774
## 3 3 104.18484
## 4 4 107.66742
## 5 5 126.81645
## 6 6 121.10484
## 7 7 136.38097
## 8 8 99.04871
## 9 9 96.23645
## 10 10 82.96548
## 11 11 100.59968
## 12 12 97.16839QP_monthly <- Qmonth_mean [,2] /BigSandy_precip_mo[,2]
QP_monthly## [1] 0.8666103 1.0806324 1.1166476 0.8410405 0.5831641 0.3411931 0.2105453
## [8] 0.1907143 0.1683864 0.2619130 0.5673372 0.8539810# The calculated runoff ratio for the Big Sandy watershedshed for January - December.