## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----message=FALSE------------------------------------------------------------ # load the GREENeR package library(GREENeR) ## ----------------------------------------------------------------------------- # load the topological sequence of catchments and complementary info data(catch_data_TN) head(catch_data_TN) ## ----------------------------------------------------------------------------- # load the sources of TN for each year and catchment data(annual_data_TN) head(annual_data_TN) # load the sources of TP for each year and catchment data(annual_data_TP) head(annual_data_TP) ## ----------------------------------------------------------------------------- # load the geographical information of the basin (require for some functionalities) data(sh_file) head(sh_file) ## ----message=FALSE, eval=FALSE------------------------------------------------ # # the barplot for the Lay TN and TP Scenarios # input_plot(annual_data_TN, sh_file, "Lay", "B") # input_plot(annual_data_TP, sh_file, "Lay", "B") ## ----echo=FALSE, out.width='100%', fig.cap="Barplot for the Lay TN scenario."---- knitr::include_graphics('figures/barplot_LayTN.png') ## ----echo=FALSE, out.width='100%', fig.cap="Barplot for the Lay TP scenario."---- knitr::include_graphics('figures/barplot_LayTP.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # # the density plots for the Lay TN and TP Scenarios # input_plot(annual_data_TN, "Lay", "D",coef_SD=1, sh_file) # input_plot(annual_data_TP, "Lay", "D",coef_SD=1, sh_file) ## ----echo=FALSE, out.width='100%', fig.cap="Density plot for the Lay TN scenario."---- knitr::include_graphics('figures/densityplot_LayTN.png') ## ----echo=FALSE, out.width='100%', fig.cap="Density plot for the Lay TP scenario."---- knitr::include_graphics('figures/densityplot_LayTP.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # # the time serie plot type 1 (areas) # input_Tserie(catch_data_TN, annual_data_TN, "Lay", "gr1") # input_Tserie(catch_data_TP, annual_data_TP, "Lay", "gr1") ## ----echo=FALSE, out.width="45%", out.height="25%",fig.cap="Time series plot type 1 (areas) for TN and TP.",fig.show='hold',fig.align='center'---- knitr::include_graphics(c("figures/timeserieTN_type1.png","figures/timeserieTP_type1.png")) ## ----message=FALSE, eval=FALSE------------------------------------------------ # # the time serie plot type 2 (lines) # input_Tserie(catch_data_TN, annual_data_TN, "Lay", "gr2") # input_Tserie(catch_data_TP, annual_data_TP, "Lay", "gr2") ## ----echo=FALSE, out.width="45%", out.height="25%",fig.cap="Time series plot type 2 (lines) for TN and TP.",fig.show='hold',fig.align='center'---- knitr::include_graphics(c("figures/timeserieTN_type2.png","figures/timeserieTP_type2.png")) ## ----echo=FALSE, eval=FALSE--------------------------------------------------- # # the time serie plot type 3 (areas by year and km2) # input_Tserie_area(catch_data_TN, annual_data_TN, sh_file, "Lay", "gr1") # input_Tserie_area(catch_data_TP, annual_data_TP, sh_file, "Lay", "gr1") ## ----echo=FALSE, out.width="45%", out.height="25%",fig.cap="Time series plot type 3 (areas by year and km2) for TN and TP.",fig.show='hold',fig.align='center'---- knitr::include_graphics(c("figures/timeserieTN_type3.png","figures/timeserieTP_type3.png")) ## ----message=FALSE, eval=FALSE------------------------------------------------ # # the time serie plot type 4 (by km2 and Shreve) # input_Tserie_area(catch_data_TN, annual_data_TN, sh_file, "Lay", "gr2") # input_Tserie_area(catch_data_TP, annual_data_TP, sh_file, "Lay", "gr2") ## ----echo=FALSE, out.width="45%", out.height="25%",fig.cap="Time series plot type 4, thatcompares the levels of nutrient inputs in three zones of the basin.",fig.show='hold',fig.align='center'---- knitr::include_graphics(c("figures/timeserieTN_type4.png","figures/timeserieTP_type4.png")) ## ----message=FALSE, eval=FALSE------------------------------------------------ # # the Input Load Map by source type 1 (kt/year) # input_maps(catch_data_TN, annual_data_TN, sh_file, "gr1", legend_position = 3) ## ----echo=FALSE, out.width='100%', fig.cap="Input map by source type 1 for TN scenario"---- #![Input maps.](figures/input_maps.png){width=75%} #300px for HTML knitr::include_graphics('figures/input_mapsTN_type1.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # # the Input Load Map by source type 1 (kt/year) # input_maps(catch_data_TP, annual_data_TP, sh_file, "gr1", legend_position = 3) ## ----echo=FALSE, out.width='100%', fig.cap="Input map by source type 1 for TP scenario"---- #![Input maps.](figures/input_maps.png){width=75%} #300px for HTML knitr::include_graphics('figures/input_mapsTP_type1.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # # the Input Load Map by source type 2 (kt/y/km2) # input_maps(catch_data_TN, annual_data_TN, sh_file, "gr2", legend_position = 3) ## ----echo=FALSE, out.width='100%', fig.cap="Input map by source type 2 for TN scenario"---- knitr::include_graphics('figures/input_mapsTN_type2.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # # the Input Load Map by source type 2 (kt/y/km2) # input_maps(catch_data_TP, annual_data_TP, sh_file, "gr2", legend_position = 3) ## ----echo=FALSE, out.width='100%', fig.cap="Input map by source type 2 for TP scenario"---- knitr::include_graphics('figures/input_mapsTP_type2.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # LakeRetent_plot(catch_data_TN) ## ----echo=FALSE, out.width='100%', fig.cap="Lake retention values distribution for TN scenario"---- knitr::include_graphics('figures/LakeRetent_plot.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # TN_ref_values <- annual_data_TN[!is.na(annual_data_TN$YearlyMass),] # nrow(TN_ref_values) # table(TN_ref_values$HydroID,TN_ref_values$YearValue) # # references_plot(annual_data_TN) ## ----echo=FALSE, out.width='100%', fig.cap="Observed references distribution for TN scenario"---- knitr::include_graphics('figures/references.png') ## ----message=FALSE------------------------------------------------------------ # Parameter for the calibration of the model # the lower limits for all params (alpha_P, alpha_L, sd_coef) low <- c(10, 0.000, 0.1) # the upper limits for all params (alpha_P, alpha_L, sd_coef) upp <- c(50, 0.08, 0.9) # number of iterations n_iter <- 200 # years in which the model should be executed years <- c(2003:2009) ## ----message=FALSE, eval=FALSE------------------------------------------------ # # execution of the calibration # DF_calib_TN <- calib_green(catch_data_TN, annual_data_TN, n_iter, low, upp, years) # DF_calib <- data.frame(DF_calib) ## ----message=FALSE, eval=FALSE------------------------------------------------ # # Generating the box plots # rateBS <- 5 # percent of parameters selected from the whole calibration set # calib_boxplot(DF_calib_TN, rateBS) ## ----echo=FALSE, out.width='100%'--------------------------------------------- knitr::include_graphics('figures/calibration_boxplotTN.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # # Generating the dot plots # Gof_mes <- "NSE" # calib_dot(DF_calib_TN, Gof_mes) ## ----echo=FALSE, out.width='100%'--------------------------------------------- knitr::include_graphics('figures/calibration_dotTN.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # # Generating the scatter plots # Gof_mes <- "NSE" # scatter_plot(DF_calib_TN, Gof_mes) ## ----echo=FALSE, out.width='100%'--------------------------------------------- knitr::include_graphics('figures/calibration_scatterTN.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # Gof_mes <- "NSE" # according the NSE goodness of fit metric # NSE_bestParams <- select_params(DF_calib_TN, Gof_mes) # NSE_bestParams # Param_NSE2 <- as.numeric(NSE_bestParams[2:4]) ## ----message=FALSE, eval=FALSE------------------------------------------------ # Gof_mes <- "rNSE" # rNSE_bestParams <- select_params(DF_calib_TN,Gof_mes) # rNSE_bestParams # Param_rNSE2 <- as.numeric(rNSE_bestParams[2:4]) ## ----message=FALSE, eval=FALSE------------------------------------------------ # # annual scatter plot comparing observed vs modeled loads by year # label_plot <- "NSE best params for TN in the Lay" # Themx <- max(annual_data_TN$YearlyMass, na.rm = TRUE) # simobs_annual_plot(catch_data_TN, annual_data_TN, Param_NSE2[1], Param_NSE2[2], Param_NSE2[3], years, label_plot, Themx) ## ----echo=FALSE, out.width='100%'--------------------------------------------- knitr::include_graphics('figures/annual_scatter_vs_modeled_loadsTN.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # setPlabels <- c("NSE", "rNSE") # label_plot <- "Comparing two sets of parameters for Lay TN" # compare_calib(catch_data_TN, annual_data_TN, Param_NSE2[1], Param_NSE2[2], Param_NSE2[3], Param_rNSE2[1], Param_rNSE2[2], Param_rNSE2[3], years, label_plot, setPlabels) ## ----echo=FALSE, out.width='100%'--------------------------------------------- knitr::include_graphics('figures/comparing_twosets_paramsTN.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # # Computing the nutrient balance # years <- c(2003:2009) # Nut_bal_TN <- region_nut_balance(catch_data_TN, annual_data_TN, Param_NSE2[1], Param_NSE2[2], Param_NSE2[3], years, atm_coeff = 0.38) # # Plot the sankey plot with the result of the balance # sank <- N4_sankey(Nut_bal_TN) ## ----echo=FALSE, out.width='100%'--------------------------------------------- knitr::include_graphics('figures/n4sankey.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # years <- c(2003:2009) # basin_sa <- green_shares(catch_data_TN, annual_data_TN, Param_NSE2[1], Param_NSE2[2], Param_NSE2[3], years) ## ----message=FALSE, eval=FALSE------------------------------------------------ # # The title of the plot # plot_title <- "Time series Load Output for the Lay Basin" # outFile <- tempfile(pattern = "OutletLoad", fileext = ".csv") # nutrient_tserie(basin_sa, plot_title, "gr1", outFile) ## ----echo=FALSE, out.width='100%'--------------------------------------------- knitr::include_graphics('figures/timeserie_loadoutputLay_type1.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # # Output Load Basin average time series (lines) # nutrient_tserie(basin_sa, plot_title, "gr2") ## ----echo=FALSE, out.width='100%'--------------------------------------------- knitr::include_graphics('figures/timeserie_loadoutputLay_type2.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # # Total Load in the Basin Outlet by source apportionment time series (lines) # nutrient_tserie_darea(basin_sa, sh_file, "Lay Basin", "gr1") ## ----echo=FALSE, out.width='100%'--------------------------------------------- knitr::include_graphics('figures/timeserie_totalloadLay.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # style <- "log10" # nutrient_maps(basin_sa, sh_file, "gr1", style, legend_position = 3) ## ----echo=FALSE, out.width='100%'--------------------------------------------- knitr::include_graphics('figures/nutrient_maps_outputLoadsType1.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # # Basin Output Total Load Maps # nutrient_maps(basin_sa, sh_file, style, "gr2", legend_position = 3) ## ----echo=FALSE, out.width='100%'--------------------------------------------- knitr::include_graphics('figures/nutrient_maps_outputLoadsType2.png') ## ----message=FALSE, eval=FALSE------------------------------------------------ # # Basin Output Specific Load by km2 Maps # nutrient_maps(basin_sa, sh_file, style, "gr3", legend_position = 3) ## ----echo=FALSE, out.width='100%'--------------------------------------------- knitr::include_graphics('figures/nutrient_maps_outputLoadsType3.png')