Merge pull request #13 from KWB-R/dev

Reduce irrigation area (closes #12)

Author: mrustl

DESCRIPTION

@@ -1,10 +1,12 @@
 Package: flextreat.hydrus1d
 Title: R Package for Soil Water Balance and Solute Transport Modelling
     Scenarios for Project Flextreat
-Version: 0.0.0.9000
+Version: 0.1.0
 Authors@R: c(
     person("Michael", "Rustler", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0003-0647-7726")),
+    person("Hauke", "Sonnenberg", , "[email protected]", role = "ctb",
+           comment = c(ORCID = "0000-0001-9134-2871")),
     person("FlexTreat", role = "fnd"),
     person("Kompetenzzentrum Wasser Berlin gGmbH (KWB)", role = "cph")
   )
@@ -35,9 +37,9 @@ Suggests:
     covr,
     DT,
     knitr,
-    plotly,
     kwb.dwd,
     kwb.python,
+    plotly,
     reticulate,
     rmarkdown,
     soilDB

NEWS.md

@@ -1,4 +1,20 @@
-# flextreat.hydrus1d 0.0.0.9000
+# [flextreat.hydrus1d 0.1.0](https://github.com/KWB-R/flextreat.hydrus1d/releases/tag/v0.1.0) <small>2022-11-17</small>
+
+Improvements before Knowledge Exchange with Project [PU2R](https://bmbf-wave.de/Verbundprojekte+nach+Themenfeldern/Kommunales+Abwasser/PU2R.html) on `2022-11-22`
+
+* Reduce `irrigation_area_sqm` (closes [#12](https://github.com/KWB-R/flextreat.hydrus1d/issues/12))
+
+* Improve documentation website
+
+* Fix GitHub actions workflows
+
+# [flextreat.hydrus1d 0.0.0.9000](https://github.com/KWB-R/flextreat.hydrus1d/releases/tag/v0.0.0.9000) <small>2022-10-05</small>
+
+Results as presented by @mrustl at Flextreat Projektreffen on 2022-10-05. **Important Note:** for scenario `status quo` (i.e. with irrigation wrong, due to 
+overestimation of irrigation area, see unresolved issue [#12](https://github.com/KWB-R/flextreat.hydrus1d/issues/12))
+
+* Added [R workflows](../articles/index.html) for two HYDRUS-1D model scenarios (`status quo`, i.e. with irrigation and `no-irrigation`) for period `2017-05-01` - `2020-10-31` with conservative transport only (i.e. tracing `clearwater` share). 
+Presented on 
 
 * Added a `NEWS.md` file to track changes to the package.
 

R/data_atmosphere.R

@@ -21,7 +21,11 @@
 #' irrigation_file <- system.file("extdata/input-data/Beregnungsmengen_AVB.csv",
 #' package = "flextreat.hydrus1d")
 #'
-#' irrigation_area <- rgdal::readOGR(dsn = shape_file)
+#'# irrigation_area <- rgdal::readOGR(dsn = shape_file)
+#'# irrigation_area_sqm <- irrigation_area$area  # 44111068m2
+#'
+#'## 2700ha (https://www.abwasserverband-bs.de/de/was-wir-machen/verregnung/)
+#'irrigation_area_sqm <- 27000000
 #'
 #' irrigation <- read.csv2(irrigation_file) %>%
 #'   dplyr::select(- .data$Monat) %>%
@@ -41,7 +45,7 @@
 #'                                                     replacements = list("Grundwasser" = "groundwater.mmPerDay",
 #'                                                                         "Klarwasser" = "clearwater.mmPerDay")),
 #'                 irrigation_cbmPerDay = .data$irrigation_m3/.data$days_in_month,
-#'                 irrigation_area_sqm = irrigation_area$area,
+#'                 irrigation_area_sqm = irrigation_area_sqm,
 #'                 irrigation_mmPerDay = 1000*irrigation_cbmPerDay/irrigation_area_sqm) %>%
 #'   dplyr::select(.data$year,
 #'                 .data$month,

R/data_irrigation.R

@@ -2,6 +2,9 @@ url: https://kwb-r.github.io/flextreat.hydrus1d
 authors:
   Michael Rustler:
     href: https://www.kompetenz-wasser.de/en/ueber-uns/team/michael-rustler
+  Hauke Sonnenberg:
+    href: https://www.kompetenz-wasser.de/en/ueber-uns/team/hauke-sonnenberg
+
   FlexTreat:
     href: https://www.kompetenz-wasser.de/en/forschung/projekte/flextreat
     html: <img src='https://bmbf-wave.de/Verbundprojekte+nach+Themenfeldern/Kommunales+Abwasser/FlexTreat-height-394-width-1389/_/Flextreat-Logo-300dpi.png'
@@ -27,7 +30,6 @@ reference:
     desc: >
       Datasets availabe for HYDRUS-1D model
     contents:
-      - atmosphere
       - evapo_p
       - irrigation
       - materials

_pkgdown.yml

@@ -33,30 +33,84 @@ precipitation_daily <- precipitation_hourly %>%
 usethis::use_data(precipitation_daily)
 
 
-## Potential Evaporation
-remotes::install_github("kwb-r/kwb.dwd@dev")
+## DWD datasets
+remotes::install_github("kwb-r/kwb.dwd")
 
 
 shape_file <- system.file("extdata/input-data/gis/Abwasserverregnungsgebiet.shp",
                           package = "flextreat.hydrus1d")
 
+
+yearmonth_start <- "201611"
+yearmonth_end <- "202204"
+
+kwb.dwd:::list_daily_grids_germany_tgz("x")
+
+
 # Only data of full months can currently be read!
-evapo_p <- kwb.dwd::read_daily_data_over_shape(
+dwd_daily_vars <- c("evaporation, potential" = "evapo_p",
+                    "evaporation, real" = "evapo_r",
+                    "soil moisture" = "soil_moist",
+                    "soil moisture" = "soil_temperature_5cm")
+dwd_daily_list <- stats::setNames(lapply(dwd_daily_vars, function(dwd_var) {
+  kwb.dwd::read_daily_data_over_shape(
   file = shape_file,
-  variable = "evapo_p",
-  from = "201701",
-  to = "202012"
+  variable = dwd_var,
+  from = yearmonth_start,
+  to = yearmonth_end,
+  quiet = TRUE
 )
+}), nm = dwd_daily_vars)
+
+
+dwd_daily <- dplyr::bind_rows(dwd_daily_list, .id = "parameter")
+"soil moisture" =
+
+
+kwb.dwd:::list_monthly_grids_germany_asc_gz("x")
+
 
-usethis::use_data(evapo_p)
+dwd_monthly_vars <- c("air temperature (mean)" = "air_temperature_mean",
+  "drought index" = "drought_index",
+  "evaporation, potential" = "evapo_p",
+  "evaporation, real" = "evapo_r",
+  "precipitation" = "precipitation",
+  "soil moisture" = "soil_moist",
+  "soil temperature (5 cm)" = "soil_temperature_5cm")
+
+dwd_monthly_list <- stats::setNames(lapply(dwd_monthly_vars, function(dwd_var) {
+  kwb.dwd::read_monthly_data_over_shape(
+    file = shape_file,
+    variable = dwd_var,
+    from = yearmonth_start,
+    to = yearmonth_end,
+    quiet = TRUE
+  )
+}), nm = dwd_monthly_vars)
+
+
+dwd_monthly <- dplyr::bind_rows(dwd_monthly_list, .id = "parameter")
+
+dwd_monthly <- tibble::tibble(parameter_name = names(dwd_monthly_vars),
+                              parameter = as.character(dwd_monthly_vars)) %>%
+  dplyr::left_join(dwd_monthly)
+
+usethis::use_data(dwd_monthly )
 
 
 irrigation_file <- system.file("extdata/input-data/Beregnungsmengen_AVB.csv",
                           package = "flextreat.hydrus1d")
 
 
-irrigation_area <- rgdal::readOGR(dsn = shape_file)
+irrigation_file <- system.file("extdata/input-data/Beregnungsmengen_AVB.csv",
+                               package = "flextreat.hydrus1d")
+
 
+# irrigation_area <- rgdal::readOGR(dsn = shape_file)
+# irrigation_area_sqm <- irrigation_area$area  # 44111068m2
+
+## 2700ha (https://www.abwasserverband-bs.de/de/was-wir-machen/verregnung/)
+irrigation_area_sqm <- 27000000
 
 irrigation <- read.csv2(irrigation_file) %>%
   dplyr::select(- .data$Monat) %>%
@@ -65,8 +119,8 @@ irrigation <- read.csv2(irrigation_file) %>%
                 month = .data$Monat_num,
                 year = .data$Jahr) %>%
   dplyr::mutate(date_start = as.Date(sprintf("%d-%02d-01",
-                               .data$year,
-                               .data$month)),
+                                             .data$year,
+                                             .data$month)),
                 days_in_month = as.numeric(lubridate::days_in_month(.data$date_start)),
                 date_end =  as.Date(sprintf("%d-%02d-%02d",
                                             .data$year,
@@ -76,7 +130,7 @@ irrigation <- read.csv2(irrigation_file) %>%
                                                     replacements = list("Grundwasser" = "groundwater.mmPerDay",
                                                                         "Klarwasser" = "clearwater.mmPerDay")),
                 irrigation_cbmPerDay = .data$irrigation_m3/.data$days_in_month,
-                irrigation_area_sqm = irrigation_area$area,
+                irrigation_area_sqm = irrigation_area_sqm,
                 irrigation_mmPerDay = 1000*irrigation_cbmPerDay/irrigation_area_sqm) %>%
   dplyr::select(.data$year,
                 .data$month,
@@ -89,6 +143,5 @@ irrigation <- read.csv2(irrigation_file) %>%
   tidyr::pivot_wider(names_from = .data$source,
                      values_from = .data$irrigation_mmPerDay)
 
-
 usethis::use_data(irrigation)
 

data-raw/climate_data.R

@@ -209,8 +209,11 @@ irrigation_file <- system.file("extdata/input-data/Beregnungsmengen_AVB.csv",
                           package = "flextreat.hydrus1d")
 
 
-irrigation_area <- rgdal::readOGR(dsn = shape_file)
+# irrigation_area <- rgdal::readOGR(dsn = shape_file) 
+# irrigation_area_sqm <- irrigation_area$area  # 44111068m2
 
+## 2700ha (https://www.abwasserverband-bs.de/de/was-wir-machen/verregnung/)
+irrigation_area_sqm <- 27000000
 
 irrigation <- read.csv2(irrigation_file) %>%
   dplyr::select(- .data$Monat) %>%
@@ -230,7 +233,7 @@ irrigation <- read.csv2(irrigation_file) %>%
                                                     replacements = list("Grundwasser" = "groundwater.mmPerDay",
                                                                         "Klarwasser" = "clearwater.mmPerDay")),
                 irrigation_cbmPerDay = .data$irrigation_m3/.data$days_in_month,
-                irrigation_area_sqm = irrigation_area$area,
+                irrigation_area_sqm = irrigation_area_sqm,
                 irrigation_mmPerDay = 1000*irrigation_cbmPerDay/irrigation_area_sqm) %>%
   dplyr::select(.data$year,
                 .data$month,
@@ -243,7 +246,6 @@ irrigation <- read.csv2(irrigation_file) %>%
   tidyr::pivot_wider(names_from = .data$source,
                      values_from = .data$irrigation_mmPerDay)
 
-
 usethis::use_data(irrigation)
 ```
 
@@ -348,43 +350,7 @@ runinf <- kwb.hydrus1d::read_runinf(paths$runinf)
 summary(runinf)
 ```
 
-
-#### Conservative Tracer
-
-
-```{r read_results_solute, eval=is_windows}
-
-solute <- kwb.hydrus1d::read_solute(paths$solute) 
-
-solute_date <- flextreat.hydrus1d::aggregate_solute(solute, 
-                                                    col_aggr = "date") 
-solute_yearmonth <- flextreat.hydrus1d::aggregate_solute(solute, 
-                                                         col_aggr = "yearmonth")
-solute_year_hydrologic <- flextreat.hydrus1d::aggregate_solute(solute,
-                                                               col_aggr = "year_hydrologic") %>%
-  dplyr::filter(.data$diff_time >= 364) ### filter out as only may-october
-
-DT::datatable(solute_year_hydrologic)
-
-
-```
-
-
-```{r plot_results_solute_static, eval=is_windows}
-
-solute_date_plot <- flextreat.hydrus1d::plot_solute(solute_date)
-solute_yearmonth_plot <- flextreat.hydrus1d::plot_solute(solute_yearmonth)
-
-solute_date_plot
-solute_yearmonth_plot
-
-kwb.utils::preparePdf(pdfFile = sprintf("solute_yearmonth_%s.pdf", 
-                                        paths$scenario),
-                      width.cm = 22, 
-                      height.cm = 10)
-solute_yearmonth_plot
-dev.off()
-```
+#### Water Balance 
 
 ```{r read_results_tlevel, eval=is_windows}
 t_level <- kwb.hydrus1d::read_tlevel(paths$t_level)

data/atmosphere.rda

@@ -209,8 +209,11 @@ irrigation_file <- system.file("extdata/input-data/Beregnungsmengen_AVB.csv",
                           package = "flextreat.hydrus1d")
 
 
-irrigation_area <- rgdal::readOGR(dsn = shape_file)
+# irrigation_area <- rgdal::readOGR(dsn = shape_file) 
+# irrigation_area_sqm <- irrigation_area$area  # 44111068m2
 
+## 2700ha (https://www.abwasserverband-bs.de/de/was-wir-machen/verregnung/)
+irrigation_area_sqm <- 27000000
 
 irrigation <- read.csv2(irrigation_file) %>%
   dplyr::select(- .data$Monat) %>%
@@ -230,7 +233,7 @@ irrigation <- read.csv2(irrigation_file) %>%
                                                     replacements = list("Grundwasser" = "groundwater.mmPerDay",
                                                                         "Klarwasser" = "clearwater.mmPerDay")),
                 irrigation_cbmPerDay = .data$irrigation_m3/.data$days_in_month,
-                irrigation_area_sqm = irrigation_area$area,
+                irrigation_area_sqm = irrigation_area_sqm,
                 irrigation_mmPerDay = 1000*irrigation_cbmPerDay/irrigation_area_sqm) %>%
   dplyr::select(.data$year,
                 .data$month,
@@ -384,6 +387,8 @@ solute_yearmonth_plot
 dev.off()
 ```
 
+#### Water Balance 
+
 ```{r read_results_tlevel, eval=is_windows}
 t_level <- kwb.hydrus1d::read_tlevel(paths$t_level)
 t_level