Normal Lake Stage Envelope Score

norm_env(stg.data)

Arguments

stg.data

see details

Value

Returns a data.frame of original data and normal stage elevation score.

Details

The input stg.data is a data.frame with columns:

  • Date (as a POSIXct or Date variable)

  • Data.Value as stage elevation data in feet (NGVD29)

Examples

# Example dataset (not real data) dat=data.frame(Date=seq(as.Date("2016-01-01"), as.Date("2016-03-02"),"1 days"),Data.Value=runif(62,12,18)) norm_env(dat)
#> Date Data.Value penalty #> 1 2016-01-01 12.48450 -2.5154992 #> 2 2016-01-02 17.00600 4.0119964 #> 3 2016-01-03 15.60457 0.6045653 #> 4 2016-01-04 12.94325 -2.0567494 #> 5 2016-01-05 12.04440 -2.9556034 #> 6 2016-01-06 14.79836 0.0000000 #> 7 2016-01-07 14.98666 0.0000000 #> 8 2016-01-08 13.73860 -1.2613965 #> 9 2016-01-09 16.39729 2.7945838 #> 10 2016-01-10 16.63513 3.2702581 #> 11 2016-01-11 17.24760 4.4952079 #> 12 2016-01-12 13.04964 -1.9503562 #> 13 2016-01-13 12.20545 -2.7945520 #> 14 2016-01-14 13.92231 -1.0776856 #> 15 2016-01-15 14.41397 -0.5860306 #> 16 2016-01-16 13.17402 -1.8098810 #> 17 2016-01-17 14.42123 -0.5465713 #> 18 2016-01-18 12.38197 -2.5697313 #> 19 2016-01-19 14.33221 -0.6033921 #> 20 2016-01-20 17.85329 5.7065740 #> 21 2016-01-21 13.73935 -1.1640462 #> 22 2016-01-22 16.07028 2.1405651 #> 23 2016-01-23 16.41192 2.8238352 #> 24 2016-01-24 13.17574 -1.6793596 #> 25 2016-01-25 17.88324 5.7664761 #> 26 2016-01-26 16.44913 2.8982583 #> 27 2016-01-27 12.30868 -2.4981223 #> 28 2016-01-28 15.18127 0.0000000 #> 29 2016-01-29 16.17494 2.3498865 #> 30 2016-01-30 16.13134 2.2626720 #> 31 2016-01-31 12.18738 -2.5550180 #> 32 2016-02-01 13.35338 -1.3729248 #> 33 2016-02-02 13.80498 -0.9052152 #> 34 2016-02-03 15.81879 1.4076289 #> 35 2016-02-04 14.87415 0.0000000 #> 36 2016-02-05 14.59303 0.0000000 #> 37 2016-02-06 16.23860 2.4772061 #> 38 2016-02-07 17.69146 5.3829189 #> 39 2016-02-08 13.08203 -1.5315674 #> 40 2016-02-09 13.30140 -1.2961007 #> 41 2016-02-10 16.08098 2.1619550 #> 42 2016-02-11 14.99307 0.0000000 #> 43 2016-02-12 15.85008 1.6674270 #> 44 2016-02-13 15.96171 1.9179826 #> 45 2016-02-14 12.57614 -1.9408551 #> 46 2016-02-15 16.59360 3.1872020 #> 47 2016-02-16 16.61805 3.2717977 #> 48 2016-02-17 17.94427 5.9599477 #> 49 2016-02-18 17.82313 5.7533508 #> 50 2016-02-19 14.33510 0.0000000 #> 51 2016-02-20 14.76712 0.0000000 #> 52 2016-02-21 13.89145 -0.5014495 #> 53 2016-02-22 13.04806 -1.3269946 #> 54 2016-02-23 15.18944 0.8322412 #> 55 2016-02-24 14.96182 0.6224721 #> 56 2016-02-25 16.67585 3.7087035 #> 57 2016-02-26 13.22507 -1.0785799 #> 58 2016-02-27 16.28038 2.9891673 #> 59 2016-02-28 12.39130 -1.8766533 #> 60 2016-02-29 14.12524 0.0000000 #> 61 2016-03-01 16.95120 4.4021931 #> 62 2016-03-02 13.64291 -0.5893405