fetchNASISWebReport(
  projectname,
  rmHzErrors = FALSE,
  fill = FALSE,
  stringsAsFactors = default.stringsAsFactors()
)

get_component_from_NASISWebReport(
  projectname,
  stringsAsFactors = default.stringsAsFactors()
)

get_chorizon_from_NASISWebReport(
  projectname,
  fill = FALSE,
  stringsAsFactors = default.stringsAsFactors()
)

get_legend_from_NASISWebReport(
  mlraoffice,
  areasymbol,
  droplevels = TRUE,
  stringsAsFactors = default.stringsAsFactors()
)

get_lmuaoverlap_from_NASISWebReport(
  areasymbol,
  droplevels = TRUE,
  stringsAsFactors = default.stringsAsFactors()
)

get_mapunit_from_NASISWebReport(
  areasymbol,
  droplevels = TRUE,
  stringsAsFactors = default.stringsAsFactors()
)

get_projectmapunit_from_NASISWebReport(
  projectname,
  stringsAsFactors = default.stringsAsFactors()
)

get_projectmapunit2_from_NASISWebReport(
  mlrassoarea,
  fiscalyear,
  projectname,
  stringsAsFactors = default.stringsAsFactors()
)

get_project_from_NASISWebReport(mlrassoarea, fiscalyear)

get_progress_from_NASISWebReport(mlrassoarea, fiscalyear, projecttypename)

get_project_correlation_from_NASISWebReport(
  mlrassoarea,
  fiscalyear,
  projectname
)

if (requireNamespace("curl") &
    curl::has_internet() &
    require("aqp") &
    require("ggplot2") &
    require("gridExtra")
) {
  # query soil components by projectname
  test = fetchNASISWebReport(
    "EVAL - MLRA 111A - Ross silt loam, 0 to 2 percent slopes, frequently flooded",
    stringsAsFactors = TRUE)
  test = test$spc

  # profile plot
  plot(test)

  # convert the data for depth plot
  clay_slice = horizons(slice(test, 0:200 ~ claytotal_l + claytotal_r + claytotal_h))
  names(clay_slice) <- gsub("claytotal_", "", names(clay_slice))

  om_slice = horizons(slice(test, 0:200 ~ om_l + om_r + om_h))
  names(om_slice) = gsub("om_", "", names(om_slice))

  test2 = rbind(data.frame(clay_slice, var = "clay"),
                data.frame(om_slice, var = "om")
  )

  h = merge(test2, site(test)[c("dmuiid", "coiid", "compname", "comppct_r")],
            by = "coiid",
            all.x = TRUE
  )

  # depth plot of clay content by soil component
  gg_comp <- function(x) {
    ggplot(x) +
      geom_line(aes(y = r, x = hzdept_r)) +
      geom_line(aes(y = r, x = hzdept_r)) +
      geom_ribbon(aes(ymin = l, ymax = h, x = hzdept_r), alpha = 0.2) +
      xlim(200, 0) +
      xlab("depth (cm)") +
      facet_grid(var ~ dmuiid + paste(compname, comppct_r)) +
      coord_flip()
  }
  g1 <- gg_comp(subset(h, var == "clay"))
  g2 <- gg_comp(subset(h, var == "om"))

  grid.arrange(g1, g2)


  # query cosoilmoist (e.g. water table data) by mukey
  # NA depths are interpreted as (???) with impute=TRUE argument
  x <- get_cosoilmoist_from_NASISWebReport(
    "EVAL - MLRA 111A - Ross silt loam, 0 to 2 percent slopes, frequently flooded",
    stringsAsFactors = TRUE)

  ggplot(x, aes(x = as.integer(month), y = dept_r, lty = status)) +
    geom_rect(aes(xmin = as.integer(month), xmax = as.integer(month) + 1,
                  ymin = 0, ymax = max(x$depb_r),
                  fill = flodfreqcl)) +
    geom_line(cex = 1) +
    geom_point() +
    geom_ribbon(aes(ymin = dept_l, ymax = dept_h), alpha = 0.2) +
    ylim(max(x$depb_r), 0) +
    xlab("month") + ylab("depth (cm)") +
    scale_x_continuous(breaks = 1:12, labels = month.abb, name="Month") +
    facet_wrap(~ paste0(compname, ' (', comppct_r , ')')) +
    ggtitle(paste0(x$nationalmusym[1],
                   ': Water Table Levels from Component Soil Moisture Month Data'))


}