R/inventory.R
In nationalparkservice/mojn-ds-rpackage: Desert Springs Protocol R Package
Defines functions
FlowCatElevPlot
FullFlowCategoriesHeatMap
FullFlowCategoriesPlot
SpCondElevPlot
TempElevPlot
FullFlowCategoriesThreeYearHeatMap
FullFlowCategoriesAnnualHeatMap
FullFlowCategoriesThreeYearPlot
FullFlowCategoriesAnnualPlot
FullFlowCategoriesDiscontinuous
FullSpringDischarge
FullSpringDischarge <- function(park, site, field.season) {
name <- "C:/Users/jbailard/Documents/R/desertsprings/inventorydata/qSumB_SpringInventoryEvents_20220216.csv"
name2 <- "C:/Users/jbailard/Documents/R/desertsprings/inventorydata/DSVisitRawData.csv"
mon <- SpringDischarge(park = park, site = site, field.season = field.season)
inv <- readr::read_csv(name, show_col_types = FALSE)
sites <- ReadAndFilterData(park = park, site = site, field.season = field.season, data.name = "Site")
visit <- ReadAndFilterData(park = park, site = site, field.season = field.season, data.name = "Visit")
wy22 <- readr::read_csv(name2, show_col_types = FALSE)
coords <- sites %>%
dplyr::select(SiteCode, Lat_WGS84, Lon_WGS84, X_UTM_NAD83_11N, Y_UTM_NAD83_11N)
type <- visit %>%
dplyr::select(SiteCode, VisitDate, SpringType)
inv.app <- sites %>%
dplyr::select(SiteCode, SampleFrame)
inv.tidy <- inv %>%
dplyr::mutate(VolDischarge_L_per_s = Discharge_liters_per_minute / 60) %>%
dplyr::mutate(SpringType = SpringHabitat_Label) %>%
dplyr::rename("Park" = "Unit_Code",
"SiteCode" = "MOJN_SpringCode",
"SiteName" = "LocationName",
"VisitDate" = "EventDate",
"DischargeClass_L_per_s" = "DischargeClass_Description",
"SpringbrookWidth_m" = "WaterWidth_m",
"VisitType" = "VisitType_Label",
"FlowCondition" = "SpringHabitat_Label") %>%
dplyr::mutate(FieldSeason = NA,
SpringbrookType = NA,
SpringbrookLengthFlag = NA,
DiscontinuousSpringbrookLengthFlag = NA,
DiscontinuousSpringbrookLength_m = NA) %>%
dplyr::left_join(inv.app, by = "SiteCode") %>%
dplyr::relocate(SampleFrame, .after = "FieldSeason") %>%
dplyr::select(Park,
SiteCode,
SiteName,
VisitDate,
FieldSeason,
SampleFrame,
VisitType,
SpringType,
FlowCondition,
VolDischarge_L_per_s,
DischargeClass_L_per_s,
SpringbrookType,
SpringbrookLengthFlag,
SpringbrookLength_m,
SpringbrookWidth_m,
DiscontinuousSpringbrookLengthFlag,
DiscontinuousSpringbrookLength_m,
Notes,
ElevationDEM_m) %>%
dplyr::mutate(VisitDate = as.Date(VisitDate, format = "%m/%d/%Y")) %>%
dplyr::mutate(SpringbrookLength_m = dplyr::case_when(SiteCode == "MOJA_P_WHI0220" ~ 3,
SiteCode == "MOJA_P_GOL0111" ~ 2,
SiteCode == "MOJA_P_OAK0157" ~ 1,
TRUE ~ SpringbrookLength_m)) %>%
dplyr::mutate(SpringbrookWidth_m = dplyr::case_when(SiteCode == "MOJA_P_WHI0220" ~ 0,
SiteCode == "MOJA_P_GOL0111" ~ 0,
SiteCode == "MOJA_P_OAK0157" ~ as.double(NA_integer_),
TRUE ~ SpringbrookWidth_m)) %>%
dplyr::mutate(FlowCondition = dplyr::case_when(FlowCondition == "Dry" ~ "dry",
SiteCode == "PARA_P_LAV0006" ~ "dry",
SiteCode == "PARA_P_ORS0041" ~ "dry",
SiteCode == "PARA_P_EDS0199" ~ "dry",
SiteCode == "MOJA_P_COT0063" ~ "dry",
SiteCode == "MOJA_P_GOL0107" ~ "dry",
SiteCode == "MOJA_P_RUF0171" ~ "dry",
SiteCode == "MOJA_P_SIL0178" ~ "dry",
SiteCode == "MOJA_P_TWI0190" ~ "dry",
SiteCode == "CAMO_P_QUA0302" ~ "dry",
SiteCode == "MOJA_P_UNN0030" ~ NA_character_,
SiteCode == "DEVA_P_NOG0740" ~ NA_character_,
TRUE ~ "standing water")) %>%
dplyr::mutate(SpringType = dplyr::case_when(SpringType == "Dry" ~ NA_character_,
SpringType == "[No Data]" ~ NA_character_,
TRUE ~ as.character(SpringType))) %>%
dplyr::mutate(VisitType = dplyr::case_when(VisitType == "First Visit" ~ "Primary",
VisitType == "Revisit" ~ "Replicate",
VisitType == "No Visit" ~ NA_character_,
TRUE ~ "Primary")) %>%
dplyr::mutate(DischargeClass_L_per_s = dplyr::case_when(DischargeClass_L_per_s == "<= 1 L/sec" ~ "<1.0 L/s",
DischargeClass_L_per_s == "1.1 L/sec to 10 L/sec" ~ "1.0 - <10 L/s",
DischargeClass_L_per_s == ">= 10 L/sec" ~ ">10 L/s",
TRUE ~ NA_character_)) %>%
dplyr::filter(!(SiteCode == "LAKE_P_FER0090"))
mon.app <- inv.tidy %>%
dplyr::select(SiteCode, ElevationDEM_m)
mon.tidy <- mon %>%
dplyr::left_join(type, by = c("SiteCode", "VisitDate")) %>%
dplyr::relocate(SpringType, .after = "VisitType") %>%
dplyr::left_join(mon.app, by = "SiteCode") %>%
dplyr::filter(!(Park == "CAMO" & FieldSeason == "2017")) %>%
dplyr::select(-SpringbrookNotes)
wy22.app <- mon.tidy %>%
dplyr::select(SiteCode, SiteName, SampleFrame, ElevationDEM_m)
new_row <- c("LAKE_P_PUP0007", "Pupfish Hot Spring", "3Yr", 252)
new_row2 <- c("LAKE_P_ARI0003", "Arizona Seep", "3Yr", 238)
wy22.app %<>%
rbind(new_row) %>%
rbind(new_row2) %>%
dplyr::mutate(ElevationDEM_m = as.numeric(ElevationDEM_m))
wy22.tidy <- wy22 %>%
dplyr::select(Park, SiteCode, DateTime, VisitType, SpringType, FlowCondition, VolDischarge_L_per_s, DischargeClass_L_per_s, SpringbrookType, SpringbrookLengthFlag, SpringbrookLength_m, SpringbrookWidth_m, DiscontinuousSpringbrookLengthFlag, DiscontinuousSpringbrookLength_m, Notes) %>%
dplyr::left_join(wy22.app, by = "SiteCode") %>%
dplyr::relocate(SiteName, .after = "SiteCode") %>%
dplyr::relocate(SampleFrame, .before = "VisitType") %>%
dplyr::mutate(Park = dplyr::case_when(Park == "Lake Mead NRA" ~ "LAKE",
Park == "Joshua Tree NP" ~ "JOTR",
Park == "Death Valley NP" ~ "DEVA",
Park == "Mojave NPRES" ~ "MOJA",
Park == "Parashant NM" ~ "PARA",
Park == "Castle Mountains NM" ~ "CAMO",
TRUE ~ NA_character_)) %>%
dplyr::mutate(VisitDate = sub(" .*", "", DateTime)) %>%
dplyr::mutate(VisitDate = as.Date(VisitDate, "%m/%d/%Y")) %>%
dplyr::relocate(VisitDate, .after = SiteName) %>%
dplyr::select(-DateTime) %>%
dplyr::filter(VisitDate > "2021-10-01") %>%
dplyr::mutate(FieldSeason = "2022") %>%
dplyr::relocate(FieldSeason, .after = "VisitDate") %>%
dplyr::mutate(SpringbrookLength_m = as.numeric(SpringbrookLength_m),
VolDischarge_L_per_s = as.numeric(VolDischarge_L_per_s),
SpringbrookType = as.character(SpringbrookType),
DiscontinuousSpringbrookLengthFlag = as.character(DiscontinuousSpringbrookLengthFlag),
DiscontinuousSpringbrookLength_m = as.numeric(DiscontinuousSpringbrookLength_m))
full <- rbind(mon.tidy, inv.tidy, wy22.tidy) %>%
dplyr::mutate(ElevationDEM_ft = ElevationDEM_m * 3.2808) %>%
dplyr::filter(VisitType == "Primary",
SampleFrame %in% c("Annual", "3Yr", "Over")) %>%
dplyr::mutate(SpringbrookLength_m = dplyr::case_when(is.na(SpringbrookLength_m) & FlowCondition == "dry" ~ 0,
TRUE ~ SpringbrookLength_m)) %>%
dplyr::mutate(SpringbrookLengthFlag = dplyr::case_when(is.na(SpringbrookLengthFlag) & SpringbrookLength_m > 50 ~ ">50m",
is.na(SpringbrookLengthFlag) & SpringbrookLength_m <= 50 ~ "Measured",
TRUE ~ SpringbrookLengthFlag)) %>%
dplyr::mutate(SpringbrookLength_m = dplyr::case_when(SpringbrookLengthFlag == ">50m" ~ as.double(NA_integer_),
TRUE ~ SpringbrookLength_m)) %>%
dplyr::mutate(VolDischarge_L_per_s = round(VolDischarge_L_per_s, 3)) %>%
dplyr::mutate(FieldSeason = dplyr::case_when(is.na(FieldSeason) & VisitDate >= lubridate::ymd("2004-10-01") & VisitDate <= lubridate::ymd("2005-09-30") ~ "2005",
is.na(FieldSeason) & VisitDate >= lubridate::ymd("2005-10-01") & VisitDate <= lubridate::ymd("2006-09-30") ~ "2006",
is.na(FieldSeason) & VisitDate >= lubridate::ymd("2006-10-01") & VisitDate <= lubridate::ymd("2007-09-30") ~ "2007",
is.na(FieldSeason) & VisitDate >= lubridate::ymd("2016-10-01") & VisitDate <= lubridate::ymd("2017-09-30") ~ "2017",
is.na(VisitDate) & Park == "MOJA" ~ "2006",
TRUE ~ FieldSeason)) %>%
unique()
return(full)
}
FullFlowCategoriesDiscontinuous <- function(park, site, field.season) {
joined <- FullSpringDischarge(park = park, site = site, field.season = field.season)
categorized <- joined %>%
dplyr::filter(VisitType == "Primary") %>%
dplyr::mutate(FlowCategory = dplyr::case_when(FlowCondition == "dry" ~ "Dry",
FlowCondition == "wet soil only" | (!(FlowCondition %in% c("dry", "wet soil only")) & (SpringbrookLength_m == 0 | SpringbrookWidth_m == 0)) ~ "Wet Soil",
(SpringbrookType == "D" & DiscontinuousSpringbrookLength_m > 0 & DiscontinuousSpringbrookLength_m < 10) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLength_m > 0 & SpringbrookLength_m < 10) ~ "< 10 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == "Measured" & (DiscontinuousSpringbrookLength_m >= 10 & DiscontinuousSpringbrookLength_m <= 50)) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == "Measured" & (SpringbrookLength_m >= 10 & SpringbrookLength_m <= 50)) ~ "10 - 50 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == ">50m") | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == ">50m") ~ "> 50 m",
TRUE ~ "NA")) %>%
dplyr::mutate(FlowCategory = dplyr::case_when(SiteCode == "PARA_P_COY0069" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_EAS0160" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_PIN0216" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_QUE0109" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_WIL0222" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2016" ~ "< 10 m",
SiteCode == "MOJA_P_HOR0121" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "LAKE_P_WHI0030" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_LOS0009" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_NEV0035" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_BLA0053" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_ARI0003" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "DEVA_P_HOL0706" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_EAS0201" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_SED1050" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_MES0218" & FieldSeason == "2005" ~ "10 - 50 m",
SiteCode == "DEVA_P_SAL0168" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0746" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0486" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_FLY0494" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HAL0809" & FieldSeason == "2006" ~ "> 50 m",
TRUE ~ FlowCategory)) %>%
dplyr::mutate(SampleFrame = dplyr::case_when(SiteCode == "MOJA_P_WHI0220" ~ "Over",
SiteCode == "MOJA_P_CUT0081" ~ "Over",
# SiteCode == "LAKE_P_ARI0003" ~ "Inactive",
# SiteCode == "LAKE_P_NEV0035" ~ "Inactive",
SiteCode == "JOTR_P_BLA0045" ~ "Inactive",
TRUE ~ SampleFrame)) %>%
dplyr::select(Park, SiteCode, SiteName, VisitDate, FieldSeason, SampleFrame, FlowCondition, FlowCategory) %>%
dplyr::group_by(Park, FieldSeason, SampleFrame, FlowCategory) %>%
dplyr::summarize(Count = dplyr::n()) %>%
dplyr::ungroup() %>%
dplyr::filter(SampleFrame %in% c("Annual", "3Yr")) %>%
dplyr::arrange(Park, FieldSeason, SampleFrame, FlowCategory)
return(categorized)
}
FullFlowCategoriesAnnualPlot <- function(park, site, field.season) {
data <- FullFlowCategoriesDiscontinuous(park = park, site = site, field.season = field.season)
data$FlowCategory <- factor(data$FlowCategory, levels = c("> 50 m", "10 - 50 m", "< 10 m", "Wet Soil", "Dry"))
data %<>% filter(!is.na(FlowCategory)) %>%
dplyr::mutate(FieldSeason = dplyr::case_when(FieldSeason %in% c("2005", "2006", "2007") ~ "2000s",
TRUE ~ FieldSeason))
plot <- ggplot2::ggplot(data %>% filter(SampleFrame == "Annual"), aes(x = FieldSeason, y = Count, fill = FlowCategory)) +
geom_bar(stat = "identity") +
facet_grid(~Park) +
scale_fill_manual(values = c("Dry" = "red",
"Wet Soil" = "gold",
"< 10 m" = "lightskyblue",
"10 - 50 m" = "royalblue1",
"> 50 m" = "navy")) +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 90)) +
labs(x = "Field Season",
y = "Number of Springs",
fill = "Flow Category")
return(plot)
}
FullFlowCategoriesThreeYearPlot <- function(park, site, field.season) {
data <- FullFlowCategoriesDiscontinuous(park = park, site = site, field.season = field.season)
data$FlowCategory <- factor(data$FlowCategory, levels = c("> 50 m", "10 - 50 m", "< 10 m", "Wet Soil", "Dry"))
data %<>% filter(!is.na(FlowCategory)) %>%
dplyr::mutate(FieldSeason = dplyr::case_when(FieldSeason %in% c("2005", "2006", "2007") ~ "2000s",
TRUE ~ FieldSeason))
plot <- ggplot2::ggplot(data %>% filter(SampleFrame == "3Yr"), aes(x = FieldSeason, y = Count, fill = FlowCategory)) +
geom_bar(stat = "identity") +
facet_grid(~Park, scales = "free", space = "free_x") +
scale_fill_manual(values = c("Dry" = "red",
"Wet Soil" = "gold",
"< 10 m" = "lightskyblue",
"10 - 50 m" = "royalblue1",
"> 50 m" = "navy")) +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 90)) +
labs(x = "Field Season",
y = "Number of Springs",
fill = "Flow Category")
return(plot)
}
FullFlowCategoriesAnnualHeatMap <- function(park, site, field.season) {
joined <- FullSpringDischarge(park = park, site = site, field.season = field.season)
data <- joined %>%
dplyr::filter(VisitType == "Primary") %>%
dplyr::mutate(FlowCategory = dplyr::case_when(FlowCondition == "dry" ~ "Dry",
FlowCondition == "wet soil only" | (!(FlowCondition %in% c("dry", "wet soil only")) & (SpringbrookLength_m == 0 | SpringbrookWidth_m == 0)) ~ "Wet Soil",
(SpringbrookType == "D" & DiscontinuousSpringbrookLength_m > 0 & DiscontinuousSpringbrookLength_m < 10) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLength_m > 0 & SpringbrookLength_m < 10) ~ "< 10 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == "Measured" & (DiscontinuousSpringbrookLength_m >= 10 & DiscontinuousSpringbrookLength_m <= 50)) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == "Measured" & (SpringbrookLength_m >= 10 & SpringbrookLength_m <= 50)) ~ "10 - 50 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == ">50m") | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == ">50m") ~ "> 50 m",
TRUE ~ "NA")) %>%
dplyr::mutate(FlowCategory = dplyr::case_when(SiteCode == "PARA_P_COY0069" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_EAS0160" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_PIN0216" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_QUE0109" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_WIL0222" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2016" ~ "< 10 m",
SiteCode == "MOJA_P_HOR0121" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "LAKE_P_WHI0030" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_LOS0009" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_NEV0035" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_BLA0053" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_ARI0003" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "DEVA_P_HOL0706" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_EAS0201" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_SED1050" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_MES0218" & FieldSeason == "2005" ~ "10 - 50 m",
SiteCode == "DEVA_P_SAL0168" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0746" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0486" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_FLY0494" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HAL0809" & FieldSeason == "2006" ~ "> 50 m",
TRUE ~ FlowCategory))
data$FlowCategory <- factor(data$FlowCategory, levels = c("> 50 m", "10 - 50 m", "< 10 m", "Wet Soil", "Dry"))
data %<>% filter(!is.na(FlowCategory)) %>%
dplyr::mutate(FieldSeason = dplyr::case_when(FieldSeason %in% c("2005", "2006", "2007") ~ "Inventory",
TRUE ~ FieldSeason))
data$FieldSeason <- factor(data$FieldSeason, levels = c("Inventory", "2016", "2017", "2018", "2019", "2020", "2021", "2022"))
heatmap <- ggplot2::ggplot(data %>% filter(SampleFrame == "Annual"), aes(x = FieldSeason,
y = reorder(SiteCode, desc(SiteCode)),
fill = FlowCategory)) +
geom_tile(color = "white") +
scale_fill_manual(values = c("navy", "royalblue1", "lightskyblue", "gold", "red"), name = "Flow Category") +
labs(x = "Field Season",
y = "Annual Spring") +
theme(legend.position = "bottom") +
facet_grid(Park~., scales = "free", space = "free_y")
return(heatmap)
}
FullFlowCategoriesThreeYearHeatMap <- function(park, site, field.season) {
joined <- FullSpringDischarge(park = park, site = site, field.season = field.season)
data <- joined %>%
dplyr::filter(VisitType == "Primary") %>%
dplyr::mutate(FlowCategory = dplyr::case_when(FlowCondition == "dry" ~ "Dry",
FlowCondition == "wet soil only" | (!(FlowCondition %in% c("dry", "wet soil only")) & (SpringbrookLength_m == 0 | SpringbrookWidth_m == 0)) ~ "Wet Soil",
(SpringbrookType == "D" & DiscontinuousSpringbrookLength_m > 0 & DiscontinuousSpringbrookLength_m < 10) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLength_m > 0 & SpringbrookLength_m < 10) ~ "< 10 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == "Measured" & (DiscontinuousSpringbrookLength_m >= 10 & DiscontinuousSpringbrookLength_m <= 50)) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == "Measured" & (SpringbrookLength_m >= 10 & SpringbrookLength_m <= 50)) ~ "10 - 50 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == ">50m") | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == ">50m") ~ "> 50 m",
TRUE ~ "NA")) %>%
dplyr::mutate(FlowCategory = dplyr::case_when(SiteCode == "PARA_P_COY0069" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_EAS0160" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_PIN0216" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_QUE0109" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_WIL0222" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2016" ~ "< 10 m",
SiteCode == "MOJA_P_HOR0121" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "LAKE_P_WHI0030" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_LOS0009" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_NEV0035" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_BLA0053" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_ARI0003" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "DEVA_P_HOL0706" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_EAS0201" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_SED1050" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_MES0218" & FieldSeason == "2005" ~ "10 - 50 m",
SiteCode == "DEVA_P_SAL0168" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0746" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0486" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_FLY0494" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HAL0809" & FieldSeason == "2006" ~ "> 50 m",
TRUE ~ FlowCategory)) %>%
dplyr::mutate(SampleFrame = dplyr::case_when(SiteCode == "MOJA_P_WHI0220" ~ "Over",
SiteCode == "MOJA_P_CUT0081" ~ "Over",
SiteCode == "LAKE_P_ARI0003" ~ "Inactive",
SiteCode == "LAKE_P_NEV0035" ~ "Inactive",
SiteCode == "JOTR_P_BLA0045" ~ "Inactive",
TRUE ~ SampleFrame)) %>%
dplyr::mutate(Visit = dplyr::case_when((Park %in% c("LAKE", "MOJA") & FieldSeason == "2016") | (Park %in% c("PARA", "JOTR", "CAMO") & FieldSeason == "2017") | (Park %in% c("DEVA") & FieldSeason == "2018") ~ "First",
(Park %in% c("LAKE", "MOJA", "CAMO") & FieldSeason == "2019") | (Park %in% c("PARA", "JOTR") & FieldSeason == "2020") | (Park %in% c("DEVA") & FieldSeason == "2021") ~ "Second",
(Park %in% c("LAKE", "MOJA", "CAMO") & FieldSeason == "2022") | (Park %in% c("PARA", "JOTR") & FieldSeason == "2023") | (Park %in% c("DEVA") & FieldSeason == "2024") ~ "Third",
FieldSeason %in% c("2005", "2006", "2007") ~ "Inventory",
TRUE ~ NA_character_))
data$FlowCategory <- factor(data$FlowCategory, levels = c("> 50 m", "10 - 50 m", "< 10 m", "Wet Soil", "Dry"))
data$Visit <- factor(data$Visit, levels = c("Inventory", "First", "Second", "Third"))
data %<>% filter(!is.na(FlowCategory))
heatmap <- ggplot2::ggplot(data %>% filter(SampleFrame == "3Yr"), aes(x = Visit,
y = reorder(SiteCode, desc(SiteCode)),
fill = FlowCategory)) +
geom_tile(color = "white") +
scale_fill_manual(values = c("navy", "royalblue1", "lightskyblue", "gold", "red"), name = "Flow Category") +
labs(x = "Revisit Cycle",
y = "Three-Year Spring") +
theme(legend.position = "bottom") +
facet_grid(Park~., scales = "free", space = "free_y")
return(heatmap)
}
TempElevPlot <- function(park, site, field.season) {
name <- "C:/Users/jbailard/Documents/R/desertsprings/inventorydata/qSumB_SpringInventoryEvents_20220216.csv"
name2 <- "C:/Users/jbailard/Documents/R/desertsprings/inventorydata/DSVisitRawData.csv"
inv <- readr::read_csv(name, show_col_types = FALSE)
sites <- ReadAndFilterData(park = park, site = site, field.season = field.season, data.name = "Site")
wq <- WqMedian(park = park, site = site, field.season = field.season)
coords <- sites %>%
dplyr::select(SiteCode, Lat_WGS84, Lon_WGS84, X_UTM_NAD83_11N, Y_UTM_NAD83_11N)
elev <- inv %>%
dplyr::rename("SiteCode" = "MOJN_SpringCode") %>%
dplyr::select(SiteCode, ElevationDEM_m) %>%
dplyr::mutate(ElevationDEM_ft = ElevationDEM_m * 3.2808)
wq.elev <- wq %>%
dplyr::left_join(elev, by = "SiteCode") %>%
dplyr::filter(Park != "CAMO",
SampleFrame %in% c("Annual", "3Yr"))
wq.elev.med <- wq.elev %>%
dplyr::group_by(Park, SiteCode, VisitType, SampleFrame, ElevationDEM_ft, ElevationDEM_m) %>%
dplyr::summarize(T_Med = median(TemperatureMedian_C, na.rm = TRUE),
SpCond_Med = median(SpCondMedian_microS_per_cm, na.rm = TRUE),
pH_Med = median(pHMedian, na.rm = TRUE),
DO_Med = median(DOMedian_mg_per_L, na.rm = TRUE)) %>%
dplyr::ungroup()
temp.elev.plot <- ggplot2::ggplot(wq.elev.med,
aes(x = ElevationDEM_m,
y = T_Med,
# color = Park,
# shape = Park
# label = SiteCode,
# label2 = FieldSeason
)) +
geom_point(size = 4) +
# geom_smooth(method = "lm"
## aes(fill = Park)
# ) +
ggpmisc::stat_poly_line() +
ggpmisc::stat_poly_eq(aes(label = paste(after_stat(eq.label),
after_stat(rr.label),
after_stat(p.value.label),
# after_stat(n.label),
sep = '*", "*'))) +
scale_color_brewer(palette = "Dark2") +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1, size = 20, color = "black"),
axis.text.y = element_text(size = 20, color = "black"),
axis.title = element_text(size = 24, face = "bold"),
legend.text = element_text(size = 24),
legend.title = element_text(size = 24, face = "bold"),
axis.title.x = element_text(margin = margin (t = 10)),
axis.title.y = element_text(margin = margin (r = 15)),
strip.text.x = ggplot2::element_text(size = 20),
legend.key = element_blank()) +
labs(y = "Water Temperature (C)",
x = "Elevation of Spring (m)") +
# xlim(min = -500, 8000) +
facet_grid(.~Park, scales = "free", space = "free_y")
temp.elev.plot
return(temp.elev.plot)
}
SpCondElevPlot <- function(park, site, field.season) {
inv <- readr::read_csv(name, show_col_types = FALSE)
sites <- ReadAndFilterData(park = park, site = site, field.season = field.season, data.name = "Site")
wq <- WqMedian(park = park, site = site, field.season = field.season)
coords <- sites %>%
dplyr::select(SiteCode, Lat_WGS84, Lon_WGS84, X_UTM_NAD83_11N, Y_UTM_NAD83_11N)
elev <- inv %>%
dplyr::rename("SiteCode" = "MOJN_SpringCode") %>%
dplyr::select(SiteCode, ElevationDEM_m) %>%
dplyr::mutate(ElevationDEM_ft = ElevationDEM_m * 3.2808)
wq.elev <- wq %>%
dplyr::left_join(elev, by = "SiteCode") %>%
dplyr::filter(Park != "CAMO",
SampleFrame %in% c("Annual", "3Yr"))
wq.elev.med <- wq.elev %>%
dplyr::group_by(Park, SiteCode, VisitType, SampleFrame, ElevationDEM_ft, ElevationDEM_m) %>%
dplyr::summarize(T_Med = median(TemperatureMedian_C, na.rm = TRUE),
SpCond_Med = median(SpCondMedian_microS_per_cm, na.rm = TRUE),
pH_Med = median(pHMedian, na.rm = TRUE),
DO_Med = median(DOMedian_mg_per_L, na.rm = TRUE)) %>%
dplyr::ungroup() # %>%
# dplyr::filter(SpCond_Med < 30000)
spcond.elev.plot <- ggplot2::ggplot(wq.elev.med,
aes(x = ElevationDEM_m,
y = SpCond_Med,
# color = Park,
# shape = Park
# label = SiteCode,
# label2 = FieldSeason
)) +
geom_point(size = 4) +
# geom_smooth(method = "lm"
## aes(fill = Park)
# ) +
ggpmisc::stat_poly_line() +
ggpmisc::stat_poly_eq(aes(label = paste(after_stat(eq.label),
after_stat(rr.label),
# after_stat(n.label),
after_stat(p.value.label),
sep = '*", "*'))) +
# ggpmisc::stat_correlation(mapping = aes(label = paste(after_stat(p.value.label),
# after_stat(n.label),
# sep = '*"; "*'))) +
scale_color_brewer(palette = "Dark2") +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1, size = 20, color = "black"),
axis.text.y = element_text(size = 20, color = "black"),
axis.title = element_text(size = 24, face = "bold"),
legend.text = element_text(size = 24),
legend.title = element_text(size = 24, face = "bold"),
axis.title.x = element_text(margin = margin (t = 10)),
axis.title.y = element_text(margin = margin (r = 15)),
strip.text.x = ggplot2::element_text(size = 20),
legend.key = element_blank()) +
# scale_y_log10() +
labs(y = "Specific Conductance (uS/cm)",
x = "Elevation of Spring (m)") +
coord_cartesian(ylim = c(-5000, 20000)) +
#ylim(min = 0, max = 20000) +
# xlim(min = -500, 8000) +
facet_grid(.~Park, scales = "free_x")
spcond.elev.plot
return(spcond.elev.plot)
}
FullFlowCategoriesPlot <- function(park, site, field.season) {
data <- FullFlowCategoriesDiscontinuous(park = park, site = site, field.season = field.season)
data$FlowCategory <- factor(data$FlowCategory, levels = c("> 50 m", "10 - 50 m", "< 10 m", " ", "Wet Soil", "Dry"))
data %<>% filter(!is.na(FlowCategory)) %>%
dplyr::filter((Park %in% c("LAKE", "MOJA") & FieldSeason %in% c("2016", "2019", "2022")) |
(Park %in% c("JOTR", "PARA") & FieldSeason %in% c("2017", "2020", "2023")) |
(Park %in% c("DEVA") & FieldSeason %in% c("2018", "2021", "2024")) |
(FieldSeason %in% c("2005", "2006", "2007"))) %>%
dplyr::mutate(FieldSeason = dplyr::case_when(FieldSeason %in% c("2005", "2006", "2007") ~ "Inventory",
TRUE ~ FieldSeason))
data$FieldSeason <- factor(data$FieldSeason, levels = c("Inventory", "2016", "2017", "2018", "2019", "2020", "2021", "2022"))
plot <- ggplot2::ggplot(data %>% filter(Park == "MOJA"), aes(x = FieldSeason, y = Count, fill = FlowCategory)) +
geom_bar(stat = "identity") +
facet_grid(~Park) +
scale_fill_manual(values = c("Dry" = "red",
"Wet Soil" = "gold",
" " = "white",
"< 10 m" = "lightskyblue",
"10 - 50 m" = "royalblue1",
"> 50 m" = "navy")) +
theme(legend.position = "bottom",
# axis.text.x = element_text(angle = 90),
axis.text = element_text(size = 28, color = "black"),
axis.title = element_text(size = 28, face = "bold"),
legend.text = element_text(size = 20),
legend.title = element_text(size = 20, face = "bold"),
axis.title.x = element_text(margin = margin (t = 10)),
axis.title.y = element_text(margin = margin (r = 15)),
legend.key = element_blank()) +
labs(x = "Field Season",
y = "Number of Springs",
fill = "Flow Category") +
guides(fill = guide_legend(nrow = 2, byrow = TRUE))
return(plot)
}
FullFlowCategoriesHeatMap <- function(park, site, field.season) {
joined <- FullSpringDischarge(park = park, site = site, field.season = field.season)
data <- joined %>%
dplyr::filter(VisitType == "Primary") %>%
dplyr::mutate(FlowCategory = dplyr::case_when(FlowCondition == "dry" ~ "Dry",
FlowCondition == "wet soil only" | (!(FlowCondition %in% c("dry", "wet soil only")) & (SpringbrookLength_m == 0 | SpringbrookWidth_m == 0)) ~ "Wet Soil",
(SpringbrookType == "D" & DiscontinuousSpringbrookLength_m > 0 & DiscontinuousSpringbrookLength_m < 10) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLength_m > 0 & SpringbrookLength_m < 10) ~ "< 10 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == "Measured" & (DiscontinuousSpringbrookLength_m >= 10 & DiscontinuousSpringbrookLength_m <= 50)) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == "Measured" & (SpringbrookLength_m >= 10 & SpringbrookLength_m <= 50)) ~ "10 - 50 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == ">50m") | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == ">50m") ~ "> 50 m",
TRUE ~ "NA")) %>%
dplyr::mutate(FlowCategory = dplyr::case_when(SiteCode == "PARA_P_COY0069" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_EAS0160" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_PIN0216" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_QUE0109" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_WIL0222" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2016" ~ "< 10 m",
SiteCode == "MOJA_P_HOR0121" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "LAKE_P_WHI0030" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_LOS0009" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_NEV0035" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_BLA0053" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_ARI0003" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "DEVA_P_HOL0706" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_EAS0201" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_SED1050" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_MES0218" & FieldSeason == "2005" ~ "10 - 50 m",
SiteCode == "DEVA_P_SAL0168" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0746" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0486" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_FLY0494" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HAL0809" & FieldSeason == "2006" ~ "> 50 m",
TRUE ~ FlowCategory)) %>%
dplyr::mutate(SampleFrame = dplyr::case_when(SiteCode == "MOJA_P_WHI0220" ~ "Over",
SiteCode == "MOJA_P_CUT0081" ~ "Over",
# SiteCode == "LAKE_P_ARI0003" ~ "Inactive",
# SiteCode == "LAKE_P_NEV0035" ~ "Inactive",
SiteCode == "JOTR_P_BLA0045" ~ "Inactive",
TRUE ~ SampleFrame)) %>%
dplyr::mutate(Visit = dplyr::case_when((Park %in% c("LAKE", "MOJA") & FieldSeason == "2016") | (Park %in% c("PARA", "JOTR", "CAMO") & FieldSeason == "2017") | (Park %in% c("DEVA") & FieldSeason == "2018") ~ "First",
(Park %in% c("LAKE", "MOJA", "CAMO") & FieldSeason == "2019") | (Park %in% c("PARA", "JOTR") & FieldSeason == "2020") | (Park %in% c("DEVA") & FieldSeason == "2021") ~ "Second",
(Park %in% c("LAKE", "MOJA", "CAMO") & FieldSeason == "2022") | (Park %in% c("PARA", "JOTR") & FieldSeason == "2023") | (Park %in% c("DEVA") & FieldSeason == "2024") ~ "Third",
FieldSeason %in% c("2005", "2006", "2007") ~ "Inventory",
TRUE ~ NA_character_))
data$FlowCategory <- factor(data$FlowCategory, levels = c("> 50 m", "10 - 50 m", "< 10 m", "Wet Soil", "Dry"))
data$Visit <- factor(data$Visit, levels = c("Inventory", "First", "Second", "Third"))
data %<>% filter(!is.na(FlowCategory))
heatmap <- ggplot2::ggplot(data %>% filter(Park == "MOJA",
SampleFrame %in% c("Annual", "3Yr"),
Visit %in% c("Inventory", "First", "Second", "Third")),
aes(x = Visit,
y = reorder(SiteCode, desc(SiteCode)),
fill = FlowCategory)) +
geom_tile(color = "white") +
scale_fill_manual(values = c("navy", "royalblue1", "lightskyblue", "gold", "red"), name = "Flow Category") +
labs(x = "Revisit Cycle",
y = "Spring Code") +
theme(legend.position = "bottom",
# axis.text.x = element_text(angle = 90),
axis.text.x = element_text(size = 28, color = "black"),
axis.text.y = element_text(size = 12, color = "black"),
axis.title = element_text(size = 28, face = "bold"),
legend.text = element_text(size = 28),
legend.title = element_text(size = 28, face = "bold"),
axis.title.x = element_text(margin = margin (t = 10)),
axis.title.y = element_text(margin = margin (r = 15))) +
guides(fill = guide_legend(reverse = TRUE)) +
facet_grid(Park~., scales = "free", space = "free_y")
return(heatmap)
}
FlowCatElevPlot <- function(park, site, field.season) {
joined <- FullSpringDischarge(park = park, site = site, field.season = field.season)
flowcatelev <- joined %>%
dplyr::filter(VisitType == "Primary") %>%
dplyr::mutate(FlowCategory = dplyr::case_when(FlowCondition == "dry" ~ "Dry",
FlowCondition == "wet soil only" | (!(FlowCondition %in% c("dry", "wet soil only")) & (SpringbrookLength_m == 0 | SpringbrookWidth_m == 0)) ~ "Wet Soil",
(SpringbrookType == "D" & DiscontinuousSpringbrookLength_m > 0 & DiscontinuousSpringbrookLength_m < 10) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLength_m > 0 & SpringbrookLength_m < 10) ~ "< 10 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == "Measured" & (DiscontinuousSpringbrookLength_m >= 10 & DiscontinuousSpringbrookLength_m <= 50)) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == "Measured" & (SpringbrookLength_m >= 10 & SpringbrookLength_m <= 50)) ~ "10 - 50 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == ">50m") | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == ">50m") ~ "> 50 m",
TRUE ~ "NA")) %>%
dplyr::mutate(FlowCategory = dplyr::case_when(SiteCode == "PARA_P_COY0069" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_EAS0160" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_PIN0216" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_QUE0109" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_WIL0222" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2016" ~ "< 10 m",
SiteCode == "MOJA_P_HOR0121" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "LAKE_P_WHI0030" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_LOS0009" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_NEV0035" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_BLA0053" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_ARI0003" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "DEVA_P_HOL0706" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_EAS0201" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_SED1050" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_MES0218" & FieldSeason == "2005" ~ "10 - 50 m",
SiteCode == "DEVA_P_SAL0168" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0746" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0486" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_FLY0494" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HAL0809" & FieldSeason == "2006" ~ "> 50 m",
TRUE ~ FlowCategory)) %>%
dplyr::mutate(SampleFrame = dplyr::case_when(SiteCode == "MOJA_P_WHI0220" ~ "Over",
SiteCode == "MOJA_P_CUT0081" ~ "Over",
# SiteCode == "LAKE_P_ARI0003" ~ "Inactive",
# SiteCode == "LAKE_P_NEV0035" ~ "Inactive",
SiteCode == "JOTR_P_BLA0045" ~ "Inactive",
TRUE ~ SampleFrame)) %>%
dplyr::select(Park, SiteCode, SiteName, VisitDate, FieldSeason, SampleFrame, FlowCondition, FlowCategory, ElevationDEM_m, ElevationDEM_ft) %>%
dplyr::filter(SampleFrame %in% c("Annual", "3Yr"),
Park != "CAMO",
FieldSeason %in% c("2016", "2017", "2018", "2019", "2020", "2021", "2022")) %>%
dplyr::arrange(SiteCode, FieldSeason, SampleFrame, FlowCategory)
flowcatelev$FlowCategory <- factor(flowcatelev$FlowCategory, levels = c("Dry", "Wet Soil", "< 10 m", "10 - 50 m", "> 50 m"))
plot <- ggplot2::ggplot(flowcatelev, aes(x = FlowCategory, y = ElevationDEM_ft)) +
geom_boxplot() +
facet_grid(Park~.)
}
nationalparkservice/mojn-ds-rpackage documentation built on Oct. 5, 2023, 6:21 p.m.
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Defines functions FlowCatElevPlot FullFlowCategoriesHeatMap FullFlowCategoriesPlot SpCondElevPlot TempElevPlot FullFlowCategoriesThreeYearHeatMap FullFlowCategoriesAnnualHeatMap FullFlowCategoriesThreeYearPlot FullFlowCategoriesAnnualPlot FullFlowCategoriesDiscontinuous FullSpringDischarge
FullSpringDischarge <- function(park, site, field.season) {
name <- "C:/Users/jbailard/Documents/R/desertsprings/inventorydata/qSumB_SpringInventoryEvents_20220216.csv"
name2 <- "C:/Users/jbailard/Documents/R/desertsprings/inventorydata/DSVisitRawData.csv"
mon <- SpringDischarge(park = park, site = site, field.season = field.season)
inv <- readr::read_csv(name, show_col_types = FALSE)
sites <- ReadAndFilterData(park = park, site = site, field.season = field.season, data.name = "Site")
visit <- ReadAndFilterData(park = park, site = site, field.season = field.season, data.name = "Visit")
wy22 <- readr::read_csv(name2, show_col_types = FALSE)
coords <- sites %>%
dplyr::select(SiteCode, Lat_WGS84, Lon_WGS84, X_UTM_NAD83_11N, Y_UTM_NAD83_11N)
type <- visit %>%
dplyr::select(SiteCode, VisitDate, SpringType)
inv.app <- sites %>%
dplyr::select(SiteCode, SampleFrame)
inv.tidy <- inv %>%
dplyr::mutate(VolDischarge_L_per_s = Discharge_liters_per_minute / 60) %>%
dplyr::mutate(SpringType = SpringHabitat_Label) %>%
dplyr::rename("Park" = "Unit_Code",
"SiteCode" = "MOJN_SpringCode",
"SiteName" = "LocationName",
"VisitDate" = "EventDate",
"DischargeClass_L_per_s" = "DischargeClass_Description",
"SpringbrookWidth_m" = "WaterWidth_m",
"VisitType" = "VisitType_Label",
"FlowCondition" = "SpringHabitat_Label") %>%
dplyr::mutate(FieldSeason = NA,
SpringbrookType = NA,
SpringbrookLengthFlag = NA,
DiscontinuousSpringbrookLengthFlag = NA,
DiscontinuousSpringbrookLength_m = NA) %>%
dplyr::left_join(inv.app, by = "SiteCode") %>%
dplyr::relocate(SampleFrame, .after = "FieldSeason") %>%
dplyr::select(Park,
SiteCode,
SiteName,
VisitDate,
FieldSeason,
SampleFrame,
VisitType,
SpringType,
FlowCondition,
VolDischarge_L_per_s,
DischargeClass_L_per_s,
SpringbrookType,
SpringbrookLengthFlag,
SpringbrookLength_m,
SpringbrookWidth_m,
DiscontinuousSpringbrookLengthFlag,
DiscontinuousSpringbrookLength_m,
Notes,
ElevationDEM_m) %>%
dplyr::mutate(VisitDate = as.Date(VisitDate, format = "%m/%d/%Y")) %>%
dplyr::mutate(SpringbrookLength_m = dplyr::case_when(SiteCode == "MOJA_P_WHI0220" ~ 3,
SiteCode == "MOJA_P_GOL0111" ~ 2,
SiteCode == "MOJA_P_OAK0157" ~ 1,
TRUE ~ SpringbrookLength_m)) %>%
dplyr::mutate(SpringbrookWidth_m = dplyr::case_when(SiteCode == "MOJA_P_WHI0220" ~ 0,
SiteCode == "MOJA_P_GOL0111" ~ 0,
SiteCode == "MOJA_P_OAK0157" ~ as.double(NA_integer_),
TRUE ~ SpringbrookWidth_m)) %>%
dplyr::mutate(FlowCondition = dplyr::case_when(FlowCondition == "Dry" ~ "dry",
SiteCode == "PARA_P_LAV0006" ~ "dry",
SiteCode == "PARA_P_ORS0041" ~ "dry",
SiteCode == "PARA_P_EDS0199" ~ "dry",
SiteCode == "MOJA_P_COT0063" ~ "dry",
SiteCode == "MOJA_P_GOL0107" ~ "dry",
SiteCode == "MOJA_P_RUF0171" ~ "dry",
SiteCode == "MOJA_P_SIL0178" ~ "dry",
SiteCode == "MOJA_P_TWI0190" ~ "dry",
SiteCode == "CAMO_P_QUA0302" ~ "dry",
SiteCode == "MOJA_P_UNN0030" ~ NA_character_,
SiteCode == "DEVA_P_NOG0740" ~ NA_character_,
TRUE ~ "standing water")) %>%
dplyr::mutate(SpringType = dplyr::case_when(SpringType == "Dry" ~ NA_character_,
SpringType == "[No Data]" ~ NA_character_,
TRUE ~ as.character(SpringType))) %>%
dplyr::mutate(VisitType = dplyr::case_when(VisitType == "First Visit" ~ "Primary",
VisitType == "Revisit" ~ "Replicate",
VisitType == "No Visit" ~ NA_character_,
TRUE ~ "Primary")) %>%
dplyr::mutate(DischargeClass_L_per_s = dplyr::case_when(DischargeClass_L_per_s == "<= 1 L/sec" ~ "<1.0 L/s",
DischargeClass_L_per_s == "1.1 L/sec to 10 L/sec" ~ "1.0 - <10 L/s",
DischargeClass_L_per_s == ">= 10 L/sec" ~ ">10 L/s",
TRUE ~ NA_character_)) %>%
dplyr::filter(!(SiteCode == "LAKE_P_FER0090"))
mon.app <- inv.tidy %>%
dplyr::select(SiteCode, ElevationDEM_m)
mon.tidy <- mon %>%
dplyr::left_join(type, by = c("SiteCode", "VisitDate")) %>%
dplyr::relocate(SpringType, .after = "VisitType") %>%
dplyr::left_join(mon.app, by = "SiteCode") %>%
dplyr::filter(!(Park == "CAMO" & FieldSeason == "2017")) %>%
dplyr::select(-SpringbrookNotes)
wy22.app <- mon.tidy %>%
dplyr::select(SiteCode, SiteName, SampleFrame, ElevationDEM_m)
new_row <- c("LAKE_P_PUP0007", "Pupfish Hot Spring", "3Yr", 252)
new_row2 <- c("LAKE_P_ARI0003", "Arizona Seep", "3Yr", 238)
wy22.app %<>%
rbind(new_row) %>%
rbind(new_row2) %>%
dplyr::mutate(ElevationDEM_m = as.numeric(ElevationDEM_m))
wy22.tidy <- wy22 %>%
dplyr::select(Park, SiteCode, DateTime, VisitType, SpringType, FlowCondition, VolDischarge_L_per_s, DischargeClass_L_per_s, SpringbrookType, SpringbrookLengthFlag, SpringbrookLength_m, SpringbrookWidth_m, DiscontinuousSpringbrookLengthFlag, DiscontinuousSpringbrookLength_m, Notes) %>%
dplyr::left_join(wy22.app, by = "SiteCode") %>%
dplyr::relocate(SiteName, .after = "SiteCode") %>%
dplyr::relocate(SampleFrame, .before = "VisitType") %>%
dplyr::mutate(Park = dplyr::case_when(Park == "Lake Mead NRA" ~ "LAKE",
Park == "Joshua Tree NP" ~ "JOTR",
Park == "Death Valley NP" ~ "DEVA",
Park == "Mojave NPRES" ~ "MOJA",
Park == "Parashant NM" ~ "PARA",
Park == "Castle Mountains NM" ~ "CAMO",
TRUE ~ NA_character_)) %>%
dplyr::mutate(VisitDate = sub(" .*", "", DateTime)) %>%
dplyr::mutate(VisitDate = as.Date(VisitDate, "%m/%d/%Y")) %>%
dplyr::relocate(VisitDate, .after = SiteName) %>%
dplyr::select(-DateTime) %>%
dplyr::filter(VisitDate > "2021-10-01") %>%
dplyr::mutate(FieldSeason = "2022") %>%
dplyr::relocate(FieldSeason, .after = "VisitDate") %>%
dplyr::mutate(SpringbrookLength_m = as.numeric(SpringbrookLength_m),
VolDischarge_L_per_s = as.numeric(VolDischarge_L_per_s),
SpringbrookType = as.character(SpringbrookType),
DiscontinuousSpringbrookLengthFlag = as.character(DiscontinuousSpringbrookLengthFlag),
DiscontinuousSpringbrookLength_m = as.numeric(DiscontinuousSpringbrookLength_m))
full <- rbind(mon.tidy, inv.tidy, wy22.tidy) %>%
dplyr::mutate(ElevationDEM_ft = ElevationDEM_m * 3.2808) %>%
dplyr::filter(VisitType == "Primary",
SampleFrame %in% c("Annual", "3Yr", "Over")) %>%
dplyr::mutate(SpringbrookLength_m = dplyr::case_when(is.na(SpringbrookLength_m) & FlowCondition == "dry" ~ 0,
TRUE ~ SpringbrookLength_m)) %>%
dplyr::mutate(SpringbrookLengthFlag = dplyr::case_when(is.na(SpringbrookLengthFlag) & SpringbrookLength_m > 50 ~ ">50m",
is.na(SpringbrookLengthFlag) & SpringbrookLength_m <= 50 ~ "Measured",
TRUE ~ SpringbrookLengthFlag)) %>%
dplyr::mutate(SpringbrookLength_m = dplyr::case_when(SpringbrookLengthFlag == ">50m" ~ as.double(NA_integer_),
TRUE ~ SpringbrookLength_m)) %>%
dplyr::mutate(VolDischarge_L_per_s = round(VolDischarge_L_per_s, 3)) %>%
dplyr::mutate(FieldSeason = dplyr::case_when(is.na(FieldSeason) & VisitDate >= lubridate::ymd("2004-10-01") & VisitDate <= lubridate::ymd("2005-09-30") ~ "2005",
is.na(FieldSeason) & VisitDate >= lubridate::ymd("2005-10-01") & VisitDate <= lubridate::ymd("2006-09-30") ~ "2006",
is.na(FieldSeason) & VisitDate >= lubridate::ymd("2006-10-01") & VisitDate <= lubridate::ymd("2007-09-30") ~ "2007",
is.na(FieldSeason) & VisitDate >= lubridate::ymd("2016-10-01") & VisitDate <= lubridate::ymd("2017-09-30") ~ "2017",
is.na(VisitDate) & Park == "MOJA" ~ "2006",
TRUE ~ FieldSeason)) %>%
unique()
return(full)
}
FullFlowCategoriesDiscontinuous <- function(park, site, field.season) {
joined <- FullSpringDischarge(park = park, site = site, field.season = field.season)
categorized <- joined %>%
dplyr::filter(VisitType == "Primary") %>%
dplyr::mutate(FlowCategory = dplyr::case_when(FlowCondition == "dry" ~ "Dry",
FlowCondition == "wet soil only" | (!(FlowCondition %in% c("dry", "wet soil only")) & (SpringbrookLength_m == 0 | SpringbrookWidth_m == 0)) ~ "Wet Soil",
(SpringbrookType == "D" & DiscontinuousSpringbrookLength_m > 0 & DiscontinuousSpringbrookLength_m < 10) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLength_m > 0 & SpringbrookLength_m < 10) ~ "< 10 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == "Measured" & (DiscontinuousSpringbrookLength_m >= 10 & DiscontinuousSpringbrookLength_m <= 50)) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == "Measured" & (SpringbrookLength_m >= 10 & SpringbrookLength_m <= 50)) ~ "10 - 50 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == ">50m") | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == ">50m") ~ "> 50 m",
TRUE ~ "NA")) %>%
dplyr::mutate(FlowCategory = dplyr::case_when(SiteCode == "PARA_P_COY0069" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_EAS0160" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_PIN0216" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_QUE0109" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_WIL0222" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2016" ~ "< 10 m",
SiteCode == "MOJA_P_HOR0121" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "LAKE_P_WHI0030" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_LOS0009" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_NEV0035" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_BLA0053" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_ARI0003" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "DEVA_P_HOL0706" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_EAS0201" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_SED1050" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_MES0218" & FieldSeason == "2005" ~ "10 - 50 m",
SiteCode == "DEVA_P_SAL0168" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0746" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0486" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_FLY0494" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HAL0809" & FieldSeason == "2006" ~ "> 50 m",
TRUE ~ FlowCategory)) %>%
dplyr::mutate(SampleFrame = dplyr::case_when(SiteCode == "MOJA_P_WHI0220" ~ "Over",
SiteCode == "MOJA_P_CUT0081" ~ "Over",
# SiteCode == "LAKE_P_ARI0003" ~ "Inactive",
# SiteCode == "LAKE_P_NEV0035" ~ "Inactive",
SiteCode == "JOTR_P_BLA0045" ~ "Inactive",
TRUE ~ SampleFrame)) %>%
dplyr::select(Park, SiteCode, SiteName, VisitDate, FieldSeason, SampleFrame, FlowCondition, FlowCategory) %>%
dplyr::group_by(Park, FieldSeason, SampleFrame, FlowCategory) %>%
dplyr::summarize(Count = dplyr::n()) %>%
dplyr::ungroup() %>%
dplyr::filter(SampleFrame %in% c("Annual", "3Yr")) %>%
dplyr::arrange(Park, FieldSeason, SampleFrame, FlowCategory)
return(categorized)
}
FullFlowCategoriesAnnualPlot <- function(park, site, field.season) {
data <- FullFlowCategoriesDiscontinuous(park = park, site = site, field.season = field.season)
data$FlowCategory <- factor(data$FlowCategory, levels = c("> 50 m", "10 - 50 m", "< 10 m", "Wet Soil", "Dry"))
data %<>% filter(!is.na(FlowCategory)) %>%
dplyr::mutate(FieldSeason = dplyr::case_when(FieldSeason %in% c("2005", "2006", "2007") ~ "2000s",
TRUE ~ FieldSeason))
plot <- ggplot2::ggplot(data %>% filter(SampleFrame == "Annual"), aes(x = FieldSeason, y = Count, fill = FlowCategory)) +
geom_bar(stat = "identity") +
facet_grid(~Park) +
scale_fill_manual(values = c("Dry" = "red",
"Wet Soil" = "gold",
"< 10 m" = "lightskyblue",
"10 - 50 m" = "royalblue1",
"> 50 m" = "navy")) +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 90)) +
labs(x = "Field Season",
y = "Number of Springs",
fill = "Flow Category")
return(plot)
}
FullFlowCategoriesThreeYearPlot <- function(park, site, field.season) {
data <- FullFlowCategoriesDiscontinuous(park = park, site = site, field.season = field.season)
data$FlowCategory <- factor(data$FlowCategory, levels = c("> 50 m", "10 - 50 m", "< 10 m", "Wet Soil", "Dry"))
data %<>% filter(!is.na(FlowCategory)) %>%
dplyr::mutate(FieldSeason = dplyr::case_when(FieldSeason %in% c("2005", "2006", "2007") ~ "2000s",
TRUE ~ FieldSeason))
plot <- ggplot2::ggplot(data %>% filter(SampleFrame == "3Yr"), aes(x = FieldSeason, y = Count, fill = FlowCategory)) +
geom_bar(stat = "identity") +
facet_grid(~Park, scales = "free", space = "free_x") +
scale_fill_manual(values = c("Dry" = "red",
"Wet Soil" = "gold",
"< 10 m" = "lightskyblue",
"10 - 50 m" = "royalblue1",
"> 50 m" = "navy")) +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 90)) +
labs(x = "Field Season",
y = "Number of Springs",
fill = "Flow Category")
return(plot)
}
FullFlowCategoriesAnnualHeatMap <- function(park, site, field.season) {
joined <- FullSpringDischarge(park = park, site = site, field.season = field.season)
data <- joined %>%
dplyr::filter(VisitType == "Primary") %>%
dplyr::mutate(FlowCategory = dplyr::case_when(FlowCondition == "dry" ~ "Dry",
FlowCondition == "wet soil only" | (!(FlowCondition %in% c("dry", "wet soil only")) & (SpringbrookLength_m == 0 | SpringbrookWidth_m == 0)) ~ "Wet Soil",
(SpringbrookType == "D" & DiscontinuousSpringbrookLength_m > 0 & DiscontinuousSpringbrookLength_m < 10) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLength_m > 0 & SpringbrookLength_m < 10) ~ "< 10 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == "Measured" & (DiscontinuousSpringbrookLength_m >= 10 & DiscontinuousSpringbrookLength_m <= 50)) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == "Measured" & (SpringbrookLength_m >= 10 & SpringbrookLength_m <= 50)) ~ "10 - 50 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == ">50m") | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == ">50m") ~ "> 50 m",
TRUE ~ "NA")) %>%
dplyr::mutate(FlowCategory = dplyr::case_when(SiteCode == "PARA_P_COY0069" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_EAS0160" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_PIN0216" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_QUE0109" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_WIL0222" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2016" ~ "< 10 m",
SiteCode == "MOJA_P_HOR0121" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "LAKE_P_WHI0030" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_LOS0009" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_NEV0035" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_BLA0053" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_ARI0003" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "DEVA_P_HOL0706" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_EAS0201" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_SED1050" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_MES0218" & FieldSeason == "2005" ~ "10 - 50 m",
SiteCode == "DEVA_P_SAL0168" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0746" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0486" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_FLY0494" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HAL0809" & FieldSeason == "2006" ~ "> 50 m",
TRUE ~ FlowCategory))
data$FlowCategory <- factor(data$FlowCategory, levels = c("> 50 m", "10 - 50 m", "< 10 m", "Wet Soil", "Dry"))
data %<>% filter(!is.na(FlowCategory)) %>%
dplyr::mutate(FieldSeason = dplyr::case_when(FieldSeason %in% c("2005", "2006", "2007") ~ "Inventory",
TRUE ~ FieldSeason))
data$FieldSeason <- factor(data$FieldSeason, levels = c("Inventory", "2016", "2017", "2018", "2019", "2020", "2021", "2022"))
heatmap <- ggplot2::ggplot(data %>% filter(SampleFrame == "Annual"), aes(x = FieldSeason,
y = reorder(SiteCode, desc(SiteCode)),
fill = FlowCategory)) +
geom_tile(color = "white") +
scale_fill_manual(values = c("navy", "royalblue1", "lightskyblue", "gold", "red"), name = "Flow Category") +
labs(x = "Field Season",
y = "Annual Spring") +
theme(legend.position = "bottom") +
facet_grid(Park~., scales = "free", space = "free_y")
return(heatmap)
}
FullFlowCategoriesThreeYearHeatMap <- function(park, site, field.season) {
joined <- FullSpringDischarge(park = park, site = site, field.season = field.season)
data <- joined %>%
dplyr::filter(VisitType == "Primary") %>%
dplyr::mutate(FlowCategory = dplyr::case_when(FlowCondition == "dry" ~ "Dry",
FlowCondition == "wet soil only" | (!(FlowCondition %in% c("dry", "wet soil only")) & (SpringbrookLength_m == 0 | SpringbrookWidth_m == 0)) ~ "Wet Soil",
(SpringbrookType == "D" & DiscontinuousSpringbrookLength_m > 0 & DiscontinuousSpringbrookLength_m < 10) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLength_m > 0 & SpringbrookLength_m < 10) ~ "< 10 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == "Measured" & (DiscontinuousSpringbrookLength_m >= 10 & DiscontinuousSpringbrookLength_m <= 50)) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == "Measured" & (SpringbrookLength_m >= 10 & SpringbrookLength_m <= 50)) ~ "10 - 50 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == ">50m") | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == ">50m") ~ "> 50 m",
TRUE ~ "NA")) %>%
dplyr::mutate(FlowCategory = dplyr::case_when(SiteCode == "PARA_P_COY0069" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_EAS0160" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_PIN0216" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_QUE0109" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_WIL0222" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2016" ~ "< 10 m",
SiteCode == "MOJA_P_HOR0121" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "LAKE_P_WHI0030" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_LOS0009" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_NEV0035" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_BLA0053" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_ARI0003" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "DEVA_P_HOL0706" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_EAS0201" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_SED1050" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_MES0218" & FieldSeason == "2005" ~ "10 - 50 m",
SiteCode == "DEVA_P_SAL0168" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0746" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0486" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_FLY0494" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HAL0809" & FieldSeason == "2006" ~ "> 50 m",
TRUE ~ FlowCategory)) %>%
dplyr::mutate(SampleFrame = dplyr::case_when(SiteCode == "MOJA_P_WHI0220" ~ "Over",
SiteCode == "MOJA_P_CUT0081" ~ "Over",
SiteCode == "LAKE_P_ARI0003" ~ "Inactive",
SiteCode == "LAKE_P_NEV0035" ~ "Inactive",
SiteCode == "JOTR_P_BLA0045" ~ "Inactive",
TRUE ~ SampleFrame)) %>%
dplyr::mutate(Visit = dplyr::case_when((Park %in% c("LAKE", "MOJA") & FieldSeason == "2016") | (Park %in% c("PARA", "JOTR", "CAMO") & FieldSeason == "2017") | (Park %in% c("DEVA") & FieldSeason == "2018") ~ "First",
(Park %in% c("LAKE", "MOJA", "CAMO") & FieldSeason == "2019") | (Park %in% c("PARA", "JOTR") & FieldSeason == "2020") | (Park %in% c("DEVA") & FieldSeason == "2021") ~ "Second",
(Park %in% c("LAKE", "MOJA", "CAMO") & FieldSeason == "2022") | (Park %in% c("PARA", "JOTR") & FieldSeason == "2023") | (Park %in% c("DEVA") & FieldSeason == "2024") ~ "Third",
FieldSeason %in% c("2005", "2006", "2007") ~ "Inventory",
TRUE ~ NA_character_))
data$FlowCategory <- factor(data$FlowCategory, levels = c("> 50 m", "10 - 50 m", "< 10 m", "Wet Soil", "Dry"))
data$Visit <- factor(data$Visit, levels = c("Inventory", "First", "Second", "Third"))
data %<>% filter(!is.na(FlowCategory))
heatmap <- ggplot2::ggplot(data %>% filter(SampleFrame == "3Yr"), aes(x = Visit,
y = reorder(SiteCode, desc(SiteCode)),
fill = FlowCategory)) +
geom_tile(color = "white") +
scale_fill_manual(values = c("navy", "royalblue1", "lightskyblue", "gold", "red"), name = "Flow Category") +
labs(x = "Revisit Cycle",
y = "Three-Year Spring") +
theme(legend.position = "bottom") +
facet_grid(Park~., scales = "free", space = "free_y")
return(heatmap)
}
TempElevPlot <- function(park, site, field.season) {
name <- "C:/Users/jbailard/Documents/R/desertsprings/inventorydata/qSumB_SpringInventoryEvents_20220216.csv"
name2 <- "C:/Users/jbailard/Documents/R/desertsprings/inventorydata/DSVisitRawData.csv"
inv <- readr::read_csv(name, show_col_types = FALSE)
sites <- ReadAndFilterData(park = park, site = site, field.season = field.season, data.name = "Site")
wq <- WqMedian(park = park, site = site, field.season = field.season)
coords <- sites %>%
dplyr::select(SiteCode, Lat_WGS84, Lon_WGS84, X_UTM_NAD83_11N, Y_UTM_NAD83_11N)
elev <- inv %>%
dplyr::rename("SiteCode" = "MOJN_SpringCode") %>%
dplyr::select(SiteCode, ElevationDEM_m) %>%
dplyr::mutate(ElevationDEM_ft = ElevationDEM_m * 3.2808)
wq.elev <- wq %>%
dplyr::left_join(elev, by = "SiteCode") %>%
dplyr::filter(Park != "CAMO",
SampleFrame %in% c("Annual", "3Yr"))
wq.elev.med <- wq.elev %>%
dplyr::group_by(Park, SiteCode, VisitType, SampleFrame, ElevationDEM_ft, ElevationDEM_m) %>%
dplyr::summarize(T_Med = median(TemperatureMedian_C, na.rm = TRUE),
SpCond_Med = median(SpCondMedian_microS_per_cm, na.rm = TRUE),
pH_Med = median(pHMedian, na.rm = TRUE),
DO_Med = median(DOMedian_mg_per_L, na.rm = TRUE)) %>%
dplyr::ungroup()
temp.elev.plot <- ggplot2::ggplot(wq.elev.med,
aes(x = ElevationDEM_m,
y = T_Med,
# color = Park,
# shape = Park
# label = SiteCode,
# label2 = FieldSeason
)) +
geom_point(size = 4) +
# geom_smooth(method = "lm"
## aes(fill = Park)
# ) +
ggpmisc::stat_poly_line() +
ggpmisc::stat_poly_eq(aes(label = paste(after_stat(eq.label),
after_stat(rr.label),
after_stat(p.value.label),
# after_stat(n.label),
sep = '*", "*'))) +
scale_color_brewer(palette = "Dark2") +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1, size = 20, color = "black"),
axis.text.y = element_text(size = 20, color = "black"),
axis.title = element_text(size = 24, face = "bold"),
legend.text = element_text(size = 24),
legend.title = element_text(size = 24, face = "bold"),
axis.title.x = element_text(margin = margin (t = 10)),
axis.title.y = element_text(margin = margin (r = 15)),
strip.text.x = ggplot2::element_text(size = 20),
legend.key = element_blank()) +
labs(y = "Water Temperature (C)",
x = "Elevation of Spring (m)") +
# xlim(min = -500, 8000) +
facet_grid(.~Park, scales = "free", space = "free_y")
temp.elev.plot
return(temp.elev.plot)
}
SpCondElevPlot <- function(park, site, field.season) {
inv <- readr::read_csv(name, show_col_types = FALSE)
sites <- ReadAndFilterData(park = park, site = site, field.season = field.season, data.name = "Site")
wq <- WqMedian(park = park, site = site, field.season = field.season)
coords <- sites %>%
dplyr::select(SiteCode, Lat_WGS84, Lon_WGS84, X_UTM_NAD83_11N, Y_UTM_NAD83_11N)
elev <- inv %>%
dplyr::rename("SiteCode" = "MOJN_SpringCode") %>%
dplyr::select(SiteCode, ElevationDEM_m) %>%
dplyr::mutate(ElevationDEM_ft = ElevationDEM_m * 3.2808)
wq.elev <- wq %>%
dplyr::left_join(elev, by = "SiteCode") %>%
dplyr::filter(Park != "CAMO",
SampleFrame %in% c("Annual", "3Yr"))
wq.elev.med <- wq.elev %>%
dplyr::group_by(Park, SiteCode, VisitType, SampleFrame, ElevationDEM_ft, ElevationDEM_m) %>%
dplyr::summarize(T_Med = median(TemperatureMedian_C, na.rm = TRUE),
SpCond_Med = median(SpCondMedian_microS_per_cm, na.rm = TRUE),
pH_Med = median(pHMedian, na.rm = TRUE),
DO_Med = median(DOMedian_mg_per_L, na.rm = TRUE)) %>%
dplyr::ungroup() # %>%
# dplyr::filter(SpCond_Med < 30000)
spcond.elev.plot <- ggplot2::ggplot(wq.elev.med,
aes(x = ElevationDEM_m,
y = SpCond_Med,
# color = Park,
# shape = Park
# label = SiteCode,
# label2 = FieldSeason
)) +
geom_point(size = 4) +
# geom_smooth(method = "lm"
## aes(fill = Park)
# ) +
ggpmisc::stat_poly_line() +
ggpmisc::stat_poly_eq(aes(label = paste(after_stat(eq.label),
after_stat(rr.label),
# after_stat(n.label),
after_stat(p.value.label),
sep = '*", "*'))) +
# ggpmisc::stat_correlation(mapping = aes(label = paste(after_stat(p.value.label),
# after_stat(n.label),
# sep = '*"; "*'))) +
scale_color_brewer(palette = "Dark2") +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1, size = 20, color = "black"),
axis.text.y = element_text(size = 20, color = "black"),
axis.title = element_text(size = 24, face = "bold"),
legend.text = element_text(size = 24),
legend.title = element_text(size = 24, face = "bold"),
axis.title.x = element_text(margin = margin (t = 10)),
axis.title.y = element_text(margin = margin (r = 15)),
strip.text.x = ggplot2::element_text(size = 20),
legend.key = element_blank()) +
# scale_y_log10() +
labs(y = "Specific Conductance (uS/cm)",
x = "Elevation of Spring (m)") +
coord_cartesian(ylim = c(-5000, 20000)) +
#ylim(min = 0, max = 20000) +
# xlim(min = -500, 8000) +
facet_grid(.~Park, scales = "free_x")
spcond.elev.plot
return(spcond.elev.plot)
}
FullFlowCategoriesPlot <- function(park, site, field.season) {
data <- FullFlowCategoriesDiscontinuous(park = park, site = site, field.season = field.season)
data$FlowCategory <- factor(data$FlowCategory, levels = c("> 50 m", "10 - 50 m", "< 10 m", " ", "Wet Soil", "Dry"))
data %<>% filter(!is.na(FlowCategory)) %>%
dplyr::filter((Park %in% c("LAKE", "MOJA") & FieldSeason %in% c("2016", "2019", "2022")) |
(Park %in% c("JOTR", "PARA") & FieldSeason %in% c("2017", "2020", "2023")) |
(Park %in% c("DEVA") & FieldSeason %in% c("2018", "2021", "2024")) |
(FieldSeason %in% c("2005", "2006", "2007"))) %>%
dplyr::mutate(FieldSeason = dplyr::case_when(FieldSeason %in% c("2005", "2006", "2007") ~ "Inventory",
TRUE ~ FieldSeason))
data$FieldSeason <- factor(data$FieldSeason, levels = c("Inventory", "2016", "2017", "2018", "2019", "2020", "2021", "2022"))
plot <- ggplot2::ggplot(data %>% filter(Park == "MOJA"), aes(x = FieldSeason, y = Count, fill = FlowCategory)) +
geom_bar(stat = "identity") +
facet_grid(~Park) +
scale_fill_manual(values = c("Dry" = "red",
"Wet Soil" = "gold",
" " = "white",
"< 10 m" = "lightskyblue",
"10 - 50 m" = "royalblue1",
"> 50 m" = "navy")) +
theme(legend.position = "bottom",
# axis.text.x = element_text(angle = 90),
axis.text = element_text(size = 28, color = "black"),
axis.title = element_text(size = 28, face = "bold"),
legend.text = element_text(size = 20),
legend.title = element_text(size = 20, face = "bold"),
axis.title.x = element_text(margin = margin (t = 10)),
axis.title.y = element_text(margin = margin (r = 15)),
legend.key = element_blank()) +
labs(x = "Field Season",
y = "Number of Springs",
fill = "Flow Category") +
guides(fill = guide_legend(nrow = 2, byrow = TRUE))
return(plot)
}
FullFlowCategoriesHeatMap <- function(park, site, field.season) {
joined <- FullSpringDischarge(park = park, site = site, field.season = field.season)
data <- joined %>%
dplyr::filter(VisitType == "Primary") %>%
dplyr::mutate(FlowCategory = dplyr::case_when(FlowCondition == "dry" ~ "Dry",
FlowCondition == "wet soil only" | (!(FlowCondition %in% c("dry", "wet soil only")) & (SpringbrookLength_m == 0 | SpringbrookWidth_m == 0)) ~ "Wet Soil",
(SpringbrookType == "D" & DiscontinuousSpringbrookLength_m > 0 & DiscontinuousSpringbrookLength_m < 10) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLength_m > 0 & SpringbrookLength_m < 10) ~ "< 10 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == "Measured" & (DiscontinuousSpringbrookLength_m >= 10 & DiscontinuousSpringbrookLength_m <= 50)) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == "Measured" & (SpringbrookLength_m >= 10 & SpringbrookLength_m <= 50)) ~ "10 - 50 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == ">50m") | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == ">50m") ~ "> 50 m",
TRUE ~ "NA")) %>%
dplyr::mutate(FlowCategory = dplyr::case_when(SiteCode == "PARA_P_COY0069" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_EAS0160" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_PIN0216" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_QUE0109" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_WIL0222" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2016" ~ "< 10 m",
SiteCode == "MOJA_P_HOR0121" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "LAKE_P_WHI0030" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_LOS0009" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_NEV0035" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_BLA0053" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_ARI0003" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "DEVA_P_HOL0706" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_EAS0201" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_SED1050" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_MES0218" & FieldSeason == "2005" ~ "10 - 50 m",
SiteCode == "DEVA_P_SAL0168" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0746" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0486" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_FLY0494" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HAL0809" & FieldSeason == "2006" ~ "> 50 m",
TRUE ~ FlowCategory)) %>%
dplyr::mutate(SampleFrame = dplyr::case_when(SiteCode == "MOJA_P_WHI0220" ~ "Over",
SiteCode == "MOJA_P_CUT0081" ~ "Over",
# SiteCode == "LAKE_P_ARI0003" ~ "Inactive",
# SiteCode == "LAKE_P_NEV0035" ~ "Inactive",
SiteCode == "JOTR_P_BLA0045" ~ "Inactive",
TRUE ~ SampleFrame)) %>%
dplyr::mutate(Visit = dplyr::case_when((Park %in% c("LAKE", "MOJA") & FieldSeason == "2016") | (Park %in% c("PARA", "JOTR", "CAMO") & FieldSeason == "2017") | (Park %in% c("DEVA") & FieldSeason == "2018") ~ "First",
(Park %in% c("LAKE", "MOJA", "CAMO") & FieldSeason == "2019") | (Park %in% c("PARA", "JOTR") & FieldSeason == "2020") | (Park %in% c("DEVA") & FieldSeason == "2021") ~ "Second",
(Park %in% c("LAKE", "MOJA", "CAMO") & FieldSeason == "2022") | (Park %in% c("PARA", "JOTR") & FieldSeason == "2023") | (Park %in% c("DEVA") & FieldSeason == "2024") ~ "Third",
FieldSeason %in% c("2005", "2006", "2007") ~ "Inventory",
TRUE ~ NA_character_))
data$FlowCategory <- factor(data$FlowCategory, levels = c("> 50 m", "10 - 50 m", "< 10 m", "Wet Soil", "Dry"))
data$Visit <- factor(data$Visit, levels = c("Inventory", "First", "Second", "Third"))
data %<>% filter(!is.na(FlowCategory))
heatmap <- ggplot2::ggplot(data %>% filter(Park == "MOJA",
SampleFrame %in% c("Annual", "3Yr"),
Visit %in% c("Inventory", "First", "Second", "Third")),
aes(x = Visit,
y = reorder(SiteCode, desc(SiteCode)),
fill = FlowCategory)) +
geom_tile(color = "white") +
scale_fill_manual(values = c("navy", "royalblue1", "lightskyblue", "gold", "red"), name = "Flow Category") +
labs(x = "Revisit Cycle",
y = "Spring Code") +
theme(legend.position = "bottom",
# axis.text.x = element_text(angle = 90),
axis.text.x = element_text(size = 28, color = "black"),
axis.text.y = element_text(size = 12, color = "black"),
axis.title = element_text(size = 28, face = "bold"),
legend.text = element_text(size = 28),
legend.title = element_text(size = 28, face = "bold"),
axis.title.x = element_text(margin = margin (t = 10)),
axis.title.y = element_text(margin = margin (r = 15))) +
guides(fill = guide_legend(reverse = TRUE)) +
facet_grid(Park~., scales = "free", space = "free_y")
return(heatmap)
}
FlowCatElevPlot <- function(park, site, field.season) {
joined <- FullSpringDischarge(park = park, site = site, field.season = field.season)
flowcatelev <- joined %>%
dplyr::filter(VisitType == "Primary") %>%
dplyr::mutate(FlowCategory = dplyr::case_when(FlowCondition == "dry" ~ "Dry",
FlowCondition == "wet soil only" | (!(FlowCondition %in% c("dry", "wet soil only")) & (SpringbrookLength_m == 0 | SpringbrookWidth_m == 0)) ~ "Wet Soil",
(SpringbrookType == "D" & DiscontinuousSpringbrookLength_m > 0 & DiscontinuousSpringbrookLength_m < 10) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLength_m > 0 & SpringbrookLength_m < 10) ~ "< 10 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == "Measured" & (DiscontinuousSpringbrookLength_m >= 10 & DiscontinuousSpringbrookLength_m <= 50)) | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == "Measured" & (SpringbrookLength_m >= 10 & SpringbrookLength_m <= 50)) ~ "10 - 50 m",
(SpringbrookType == "D" & DiscontinuousSpringbrookLengthFlag == ">50m") | ((SpringbrookType != "D" | is.na(SpringbrookType)) & SpringbrookLengthFlag == ">50m") ~ "> 50 m",
TRUE ~ "NA")) %>%
dplyr::mutate(FlowCategory = dplyr::case_when(SiteCode == "PARA_P_COY0069" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_EAS0160" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_PIN0216" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "JOTR_P_QUE0109" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_WIL0222" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "MOJA_P_BUD0021" & FieldSeason == "2016" ~ "< 10 m",
SiteCode == "MOJA_P_HOR0121" & FieldSeason == "2006" ~ "< 10 m",
SiteCode == "LAKE_P_WHI0030" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_LOS0009" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_NEV0035" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_BLA0053" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "LAKE_P_ARI0003" & FieldSeason == "2007" ~ "< 10 m",
SiteCode == "DEVA_P_HOL0706" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_EAS0201" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_SED1050" & FieldSeason == "2005" ~ "< 10 m",
SiteCode == "DEVA_P_MES0218" & FieldSeason == "2005" ~ "10 - 50 m",
SiteCode == "DEVA_P_SAL0168" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0746" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HUN0486" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_FLY0494" & FieldSeason == "2005" ~ "> 50 m",
SiteCode == "DEVA_P_HAL0809" & FieldSeason == "2006" ~ "> 50 m",
TRUE ~ FlowCategory)) %>%
dplyr::mutate(SampleFrame = dplyr::case_when(SiteCode == "MOJA_P_WHI0220" ~ "Over",
SiteCode == "MOJA_P_CUT0081" ~ "Over",
# SiteCode == "LAKE_P_ARI0003" ~ "Inactive",
# SiteCode == "LAKE_P_NEV0035" ~ "Inactive",
SiteCode == "JOTR_P_BLA0045" ~ "Inactive",
TRUE ~ SampleFrame)) %>%
dplyr::select(Park, SiteCode, SiteName, VisitDate, FieldSeason, SampleFrame, FlowCondition, FlowCategory, ElevationDEM_m, ElevationDEM_ft) %>%
dplyr::filter(SampleFrame %in% c("Annual", "3Yr"),
Park != "CAMO",
FieldSeason %in% c("2016", "2017", "2018", "2019", "2020", "2021", "2022")) %>%
dplyr::arrange(SiteCode, FieldSeason, SampleFrame, FlowCategory)
flowcatelev$FlowCategory <- factor(flowcatelev$FlowCategory, levels = c("Dry", "Wet Soil", "< 10 m", "10 - 50 m", "> 50 m"))
plot <- ggplot2::ggplot(flowcatelev, aes(x = FlowCategory, y = ElevationDEM_ft)) +
geom_boxplot() +
facet_grid(Park~.)
}
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