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Impact_evaluation_PCW_121217.Rmd
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Impact_evaluation_PCW_121217.Rmd
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---
title: "Preliminary results of the impact evaluation paper"
author: "Mani Rouhi Rad"
date: '`r format(Sys.Date(), "%B %d, %Y")`'
#output: pdf_document
#output: md_document
output:
html_document:
css: custom.css
# keep_md: true
#fontsize: 12pt
---
This is an [R Markdown](http://rmarkdown.rstudio.com) Notebook. When you execute code within the notebook, the results appear beneath the code.
Try executing this chunk by clicking the *Run* button within the chunk or by placing your cursor inside it and pressing *Ctrl+Shift+Enter*.
```{r}
plot(cars)
```
Add a new chunk by clicking the *Insert Chunk* button on the toolbar or by pressing *Ctrl+Alt+I*.
When you save the notebook, an HTML file containing the code and output will be saved alongside it (click the *Preview* button or press *Ctrl+Shift+K* to preview the HTML file).
The preview shows you a rendered HTML copy of the contents of the editor. Consequently, unlike *Knit*, *Preview* does not run any R code chunks. Instead, the output of the chunk when it was last run in the editor is displayed.
```{r, include=FALSE, warning=FALSE}
library(rgeos)
library(rgdal)
library(plyr)
library(reshape2)
library(dplyr)
library(data.table)
library(ggplot2)
library(scales)
library(R.matlab)
library(sp)
library(sf)
library(maptools)
library(broom)
library(quantreg)
library(foreign)
library(raster)
library(lmtest)
library(RColorBrewer)
library(readstata13)
library(parallel)
require(stargazer)
library(AER)
library(texreg)
```
```{r setup, include=FALSE}
# knitr::opts_knit$set(root.dir = 'C:/Users/mr2284/Dropbox/Panama S2/Impact Evaluation')
knitr::opts_knit$set(root.dir = '/Users/Mani/Dropbox/Panama S2/Impact Evaluation')
# knitr::opts_chunk$set(fig.width=12, fig.height=8, fig.path='./Figures and Tables', echo=FALSE, warning=FALSE, message=FALSE, cache=TRUE)
```
```{r, include=FALSE, warning=FALSE}
simpleCap <- function(x) { # 1) Function defined to make all caps to propper
paste(substring(x, 1,1), tolower(substring(x, 2)), # 2)
sep="") } # 3)
FN_area_sp = function(input_sp, scenario){ # 1) function defined to find the area
foo = st_as_sf(input_sp)
a = as.data.table(input_sp@data)
b = as.data.table(st_area(foo))
b[, paste(scenario, "ha", sep="_"):=as.numeric(x*0.0001)]
b=b[, 2]
output_data=data.table(a, b)
return(output_data)
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
######## Input data ######
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# I. River discharge
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
river_discharge=data.table(read.csv("./Data/Map Area_update.csv"))
river_discharge=melt(river_discharge, id=c("River", "Year", "Day"), variable.name = "month", value.name = "discharge_m3_s")
river_discharge=river_discharge[complete.cases(Day)]
river_discharge[, date_read := as.Date(as.character(paste(Year, month, Day, sep = "")), "%Y%b%d")]
river_discharge=river_discharge[,.(River, year=Year, month, day=Day, date_read, discharge_m3_s)]
river_discharge[, discharge_m3_s:=as.numeric(discharge_m3_s)]
# windows
river_discharge[, River:=gsub("Gat?n", "Gatun", River)]
river_discharge[, River:=gsub("Ca?o Quebrado", "Cano Quebrado", River)]
river_discharge[, River:=gsub("Boquer?n", "Boqueron", River)]
river_discharge[, River:=gsub("Cir? Grande", "Ciri grande", River)]
river_discharge[, River:=gsub("Indio BdU", "Indio", River)]
river_discharge[, River:=gsub("Pequen?", "Pequeni", River)]
river_discharge[, unique(River)]
# mac
river_discharge[, River:=gsub("Gat\xfan", "Gatun", River)]
river_discharge[, River:=gsub("Ca\xf1o Quebrado", "Cano Quebrado", River)]
river_discharge[, River:=gsub("Boquer\xf3n", "Boqueron", River)]
river_discharge[, River:=gsub("Cir\xed Grande", "Ciri grande", River)]
river_discharge[, River:=gsub("Indio BdU", "Indio", River)]
river_discharge[, River:=gsub("Pequen\xed", "Pequeni", River)]
river_discharge[, unique(River)]
river_discharge[ , month:=month(date_read)]
# Since I am a visual person:
ggplot(data = river_discharge[(River=="Cano Quebrado" | River=="Trinidad")], aes(x=date_read, y=discharge_m3_s, group=River, colour=River))+
geom_line(size=1.1)+
coord_cartesian(ylim=c(0, 400)) +
scale_x_date(labels = date_format("%m-%Y")) +
scale_y_discrete(breaks=seq(0, 400, 100)) # Ticks from 0-10, every .25
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# II. River - watershed connection
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
river_names = readOGR(dsn="./Data/Rivers",layer="Rivers_PCWCopy")
river_names=data.table(river_names@data)
river_names=river_names[,.(NOMBRE, SUBCUENC_2)]
river_names[, River:=simpleCap(NOMBRE)]
spanish_cano=river_names[, unique(River)][3]
river_names[, River:=gsub(spanish_cano, "Cano Quebrado", River)]
river_names[, unique(River)]
setkey(river_names, River)
setkey(river_discharge, River)
river_discharge=river_names[river_discharge]
river_discharge=river_discharge[complete.cases(NOMBRE)]
river_discharge=river_discharge[,.(River, SUBCUENC_2, year, month, day, date_read, discharge_m3_s)]
weird_char = unique(river_discharge$SUBCUENC_2)[1]
weird_char = substr(weird_char, 1, 4) # win
weird_char = substr(weird_char, 1, 3) # mac
river_discharge[, SUBCUENC_2 := gsub(weird_char, "Rio", SUBCUENC_2)]
river_discharge[, SUBCUENC_2 := gsub("Boquerón", "Boqueron", SUBCUENC_2)]
river_discharge[, SUBCUENC_2 := gsub("Caño", "Cano", SUBCUENC_2)]
weird_char_ciri=unique(river_discharge$SUBCUENC_2)[4]
weird_char_ciri=substr(weird_char_ciri, 5, 8)
weird_char_pequeni=unique(river_discharge$SUBCUENC_2)[7]
weird_char_pequeni=substr(weird_char_pequeni, 5, 13)
river_discharge[, SUBCUENC_2 := gsub(weird_char_ciri, "Ciri", SUBCUENC_2)] # win
river_discharge[, SUBCUENC_2 := gsub(weird_char_pequeni, "Pequeni", SUBCUENC_2)] # win
river_discharge[, SUBCUENC_2 := gsub("Gatún", "Gatun", SUBCUENC_2)]
river_discharge[, unique(SUBCUENC_2)]
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# II. Hectares in each region-year
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
PIEA = readOGR(dsn="./Data/PIEA", layer="PIEA_polygons")
watershed_original = readOGR(dsn="./Data/Watersheds", layer="Watersheds_PCW")
watershed_original = gBuffer(watershed_original, byid = TRUE, width = 0)
watershed_PIEA_final = raster::intersect(PIEA, watershed_original)
# writeOGR(watershed_PIEA_final,
# dsn="./Data/PIEA", layer="PIEA_by_watershed", driver="ESRI Shapefile")
watershed_PIEA_final=FN_area_sp(watershed_PIEA_final, "area_PIEA_watershed")
watershed_PIEA_final=watershed_PIEA_final[,.(Uso, SUBCUENC_2, area_PIEA_watershed_ha, area_watershed_ha=area_Water)]
watershed_PIEA_final[, Uso:=gsub(": Programa PIEA", "", Uso)]
watershed_PIEA_final_by_land_use = watershed_PIEA_final[, sum(area_PIEA_watershed_ha), by="Uso"]
watershed_PIEA_final_by_watershed= watershed_PIEA_final[, .(sum(area_PIEA_watershed_ha), sum(area_watershed_ha)), by="SUBCUENC_2"]
watershed_PIEA_final_by_watershed[, percent_area:=V1/V2*100]
setkey(watershed_PIEA_final_by_watershed, percent_area)
watershed_PIEA_final[, SUBCUENC_2 := gsub(weird_char, "Rio", SUBCUENC_2)]
watershed_PIEA_final[, SUBCUENC_2 := gsub("Boquerón", "Boqueron", SUBCUENC_2)]
watershed_PIEA_final[, SUBCUENC_2 := gsub("Caño", "Cano", SUBCUENC_2)]
watershed_PIEA_final[, SUBCUENC_2 := gsub(weird_char_ciri, "Ciri", SUBCUENC_2)]
watershed_PIEA_final[, SUBCUENC_2 := gsub(weird_char_pequeni, "Pequeni", SUBCUENC_2)] # mac
watershed_PIEA_final[, SUBCUENC_2 := gsub("Gatún", "Gatun", SUBCUENC_2)]
watershed_PIEA_final[, unique(SUBCUENC_2)]
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# III. Rainfall (Other climatic variables?)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
rainfall_PIEA=read.dta13("./Data/Rainfall/acp_15Minstorms_Steve_v18112016.dta")
rainfall_PIEA=data.table(rainfall_PIEA)
rainfall_PIEA[,month:=substr(date, 4, 5)]
rainfall_PIEA[,day :=substr(date, 1, 2)]
rainfall_PIEA[,total_rain_day:=sum(Totalrain), by=c("site", "Year", "month", "day")]
rainfall_PIEA=unique(rainfall_PIEA, by=c("site", "Year", "month", "day"))
rainfall_PIEA[,month:=as.numeric(month)]
rainfall_PIEA[,day :=as.numeric(day)]
rainfall_stations = readOGR(dsn="./Data/Rainfall/stations", layer="stations")
# foo1 = watershed_original[!is.na(over(rainfall_stations, as(watershed_original,"SpatialPolygons"))),]
bar_1=over(rainfall_stations, as(watershed_original,"SpatialPolygons"))
bar_1=data.table(bar_1)
setnames(bar_1, "bar_1", "over_id")
bar_2=data.table(bar_1, rainfall_stations@data)
bar_2=bar_2[complete.cases(over_id)]
bar_3=data.table(watershed_original@data)
setkey(bar_2, over_id)
setkey(bar_3, OBJECTID_1)
bar= bar_2[bar_3]
bar=bar[complete.cases(CODENAME)]
setkey(bar, CODENAME)
rainfall_stations=bar[,.(OBJECTID, over_id, CODENAME, SUBCUENC_2)]
rainfall_stations[, CODENAME:=gsub(" ", "", CODENAME, fixed = TRUE)]
setkey(rainfall_stations, CODENAME)
setkey(rainfall_PIEA, site)
rainfall_PIEA=rainfall_stations[rainfall_PIEA]
rainfall_PIEA=rainfall_PIEA[complete.cases(CODENAME) & complete.cases(SUBCUENC_2)]
rainfall_PIEA=rainfall_PIEA[,.(Station= CODENAME, SUBCUENC_2, date, Year, month, day, total_rain_day)]
rainfall_PIEA[, date_read:=as.Date(date, "dd/mm/yyyy")]
rainfall_PIEA[, date_read:=as.Date(date, "%d/%m/%Y")]
ggplot(data = rainfall_PIEA[Station=="CANONES"], aes(x=date, y=total_rain_day))+
geom_line(size=1.1)+
# coord_cartesian(ylim=c(0, 400)) +
scale_x_date(labels = date_format("%m-%Y")) #+
# scale_y_discrete(breaks=seq(0, 400, 100)) # Ticks from 0-10, every .25
rainfall_PIEA[, unique(Station)]
# rainfall_PIEA[, unique(SUBCUENC_2)]
# watershed_PIEA_final[, unique(SUBCUENC_2)]
# river_discharge[, unique(SUBCUENC_2)]
# str(river_discharge)
# str(rainfall_PIEA)
rainfall_PIEA[, SUBCUENC_2 := gsub(weird_char, "Rio", SUBCUENC_2)]
rainfall_PIEA[, SUBCUENC_2 := gsub("Boquerón", "Boqueron", SUBCUENC_2)]
rainfall_PIEA[, SUBCUENC_2 := gsub("Caño", "Cano", SUBCUENC_2)]
rainfall_PIEA[, SUBCUENC_2 := gsub(weird_char_ciri, "Ciri", SUBCUENC_2)] # win
rainfall_PIEA[, SUBCUENC_2 := gsub(weird_char_pequeni, "Pequeni", SUBCUENC_2)] # win
rainfall_PIEA[, SUBCUENC_2 := gsub("Gatún", "Gatun", SUBCUENC_2)]
rainfall_PIEA[, unique(SUBCUENC_2)]
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# IV. Seasons
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
seasons=read.csv("./Data/seasons.csv")
seasons=data.table(seasons)
seasons[, Dry_season_start_date := as.Date(Dry_season_start, "%d-%b-%y")]
seasons[, Dry_season_end_date := as.Date(Dry_season_end, "%d-%b-%y")]
seasons=seasons[,.(YEAR, Dry_season_start_date, Dry_season_end_date)]
seasons[, Dry_season_length := Dry_season_end_date - Dry_season_start_date]
setkey(seasons, YEAR)
setkey(river_discharge, year)
river_discharge=river_discharge[seasons]
river_discharge=river_discharge[complete.cases(River)]
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# V. Merge
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
setkey(rainfall_PIEA, SUBCUENC_2, Year, month, day)
setkey(river_discharge, SUBCUENC_2, year, month, day)
unique(rainfall_PIEA, by="SUBCUENC_2")
unique(river_discharge, by="SUBCUENC_2")
# setkey(watershed_PIEA_final, SUBCUENC_2, year, month, day)
# setkey(watershed_PIEA_final, SUBCUENC_2, Uso)
# data_reg = river_discharge[rainfall_PIEA, allow.cartesian=T, all.x=T]
# data_reg = rainfall_PIEA[river_discharge, allow.cartesian=T]
# data_reg = data_reg[complete.cases(date_read)]
# data_reg = data_reg[complete.cases(total_rain_day) & complete.cases(discharge_m3_s)]
data_reg = merge(river_discharge, rainfall_PIEA, by.x=c("SUBCUENC_2", "date_read"), by.y=c("SUBCUENC_2", "date_read") , all.x=T)
data_reg = data_reg[year > 2004]
data_reg = data_reg[,.(SUBCUENC_2, River, year, month=month.x, date_read, Dry_season_start_date, Dry_season_end_date, discharge_m3_s, Station, total_rain_day)]
data_reg[, day_of_dry_season := date_read - Dry_season_start_date]
data_reg[, day_of_wet_season := date_read - (Dry_season_end_date+1)]
data_reg[, day_of_season := ifelse(date_read < Dry_season_end_date+1, day_of_dry_season, day_of_wet_season)]
data_reg[, dry_dummy := ifelse(date_read < Dry_season_end_date+1, 1, 0)]
data_reg[, total_rain_day := ifelse(is.na(total_rain_day), 0, total_rain_day)]
data_reg=data_reg[year<2016]
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# VI. land use data
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
land_use=read.csv("./Data/Land Covers/land_use_by_catchment_by_year.csv")
land_use=data.table(land_use)
# mac
land_use[, River:=gsub("Gat\xfan", "Gatun", River)]
land_use[, River:=gsub("Ca\xf1o Quebrado", "Cano Quebrado", River)]
land_use[, River:=gsub("Boquer\xf3n", "Boqueron", River)]
land_use[, River:=gsub("Cir\xed Grande", "Ciri grande", River)]
land_use[, River:=gsub("Indio BdU", "Indio", River)]
land_use[, River:=gsub("Pequen\xed", "Pequeni", River)]
land_use[, unique(River)]
land_use[,foo:=NULL]
land_use=land_use[River=="Trinidad" | River== "Ciri grande" | River=="Cano Quebrado"]
land_use=land_use[,foo:=ifelse(X2003==0 & X2008==0 & X2012==0, 1, 0)]
land_use=land_use[foo==0]
land_use=land_use[land.use!="Water"]
forest=land_use[land.use=="Mature Forests" | land.use=="Secondary Forests" | land.use=="Forest Plantations"]
cols=colnames(forest)[3:5]
forest[, (cols):=lapply(.SD, sum), by="River", .SDcols=cols]
forest=unique(forest, by="River")
forest[, forest_2012_2008:=X2012 - X2008]
forest=forest[,.(River, forest_2012_2008)]
pasture=land_use[land.use=="Pastures"]
pasture[, pasture_2012_2008:=X2012 - X2008]
pasture=pasture[,.(River, pasture_2012_2008)]
convertible=land_use[land.use=="Pastures" | land.use=="Crops" | land.use=="Scrub"]
cols=colnames(convertible)[3:5]
convertible[, (cols):=lapply(.SD, sum), by="River", .SDcols=cols]
convertible=unique(convertible, by="River")
convertible[, convertible_2012_2008:=X2012 - X2008]
convertible=convertible[,.(River, convertible_2012_2008)]
setkey(forest, River)
setkey(pasture, River)
setkey(convertible, River)
land_use_2008_2012=forest[pasture]
land_use_2008_2012=land_use_2008_2012[convertible]
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ####
######## Data Analysis ###########
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
trin = watershed_PIEA_final_by_watershed[,SUBCUENC_2][25]
ciri = watershed_PIEA_final_by_watershed[,SUBCUENC_2][31]
watershed_PIEA_west = watershed_PIEA_final_by_watershed[SUBCUENC_2==trin | SUBCUENC_2==ciri]
watershed_PIEA_west = watershed_PIEA_west[ SUBCUENC_2==trin, SUBCUENC_2:="Trinidad"]
watershed_PIEA_west = watershed_PIEA_west[ SUBCUENC_2==ciri, SUBCUENC_2:="Ciri grande"]
river_discharge_west= river_discharge[River=="Trinidad" | River=="Ciri grande"]
river_discharge_west=river_discharge_west[date_read < Dry_season_end_date]
river_discharge_west[, tot_discharge := discharge_m3_s*24*3600/1000000]
river_discharge_west[, tot_discharge := sum(tot_discharge), by=c("River", "year")]
river_discharge_west=unique(river_discharge_west, by=c("River", "year"))
river_discharge_west[, tot_discharge:=mean(tot_discharge), by="River"]
river_discharge_west=unique(river_discharge_west, by="River")
river_discharge_west=river_discharge_west[,.(River, tot_discharge)]
setkey(watershed_PIEA_west, SUBCUENC_2)
setkey(river_discharge_west, River)
watershed_PIEA_west=watershed_PIEA_west[river_discharge_west]
watershed_PIEA_west[, discharge_per_ha := tot_discharge/V2*10^6]
watershed_PIEA_west[, extra_discharge := discharge_per_ha * V1 * .2]
watershed_PIEA_west[, percent_extra_discharge := extra_discharge/(tot_discharge * 10^6)*100]
# watershed_PIEA_final_by_watershed[, water_increase_treatment_ESE_15:=V1*.15]
```