knitr::opts_chunk$set(echo = TRUE, message = FALSE) knitr::opts_knit$set(root.dir = rprojroot::find_rstudio_root_file()) library(tidyverse) library(readxl) library(cvpiaHabitat)
lengths_table <- read_excel('data-raw/floodplain/CVPIA_FloodplainAreas.xlsx', sheet = 'MetaData', col_types = c('text', 'text', 'text', 'text', rep('numeric', 17), 'text', 'numeric', 'text'), na = 'na') pools_perc <- read_csv('data-raw/instream/pools/pools.csv', col_types = 'cnc') %>% select(-FW_QAQC) mean_pools_perc <- filter(pools_perc, watershed != 'Feather River') %>% pull(percent_pools) %>% mean(na.rm = TRUE) pools_perc wss <- cvpiaData::watershed_ordering$watershed pools <- lengths_table %>% filter(watershed %in% wss) %>% mutate(SR_prop_length = SR_rearing_length_mi/FR_rearing_length_mi, ST_prop_length = ST_rearing_length_mi/FR_rearing_length_mi, FR_channel_area = FR_channel_area_of_length_modeled_acres, SR_channel_area = FR_channel_area * SR_prop_length, ST_channel_area = FR_channel_area * ST_prop_length) %>% select(watershed, FR_channel_area, SR_channel_area, ST_channel_area) %>% left_join(pools_perc) %>% mutate(percent_pools = replace(percent_pools, is.na(percent_pools), mean_pools_perc), SR_pools_sq_meters = SR_channel_area * percent_pools/100 * 4046.86, ST_pools_sq_meters = ST_channel_area * percent_pools/100 * 4046.86) %>% select(watershed, SR_pools_sq_meters, ST_pools_sq_meters) %>% left_join(cvpiaData::watershed_ordering) %>% arrange(order) %>% select(-order) # put combinded values of upper sac + upper mid sac in upper sac # upper sac + upper mid sac 6174 acres, from mark gard pools_upper_sac <- 6174 * 7.2/100 * 4046.86 pools[pools$watershed == 'Upper Sacramento River', c('SR_pools_sq_meters', 'ST_pools_sq_meters')] <- c(pools_upper_sac, pools_upper_sac) # use_data(pools, overwrite = TRUE) pools
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