Using the Limnotrack API • aemetools

library(AEME)
library(aemetools)
library(tmap)
tmap_mode("view")
tmap_options(basemap.server = c("Esri.WorldImagery", "Esri.WorldGrayCanvas",
                                "OpenStreetMap", "Esri.WorldTopoMap"))

The Limnotrack API provides access to various environmental data layers, including meteorological data from ERA5-Land. This vignette demonstrates how to use the Limnotrack API to extract ERA5-Land data for specific locations in New Zealand.

First, it is always good to check the status of the API to ensure it is operational.

check_api_status()
#> API is available
#> Database connection is healthy
#> [1] TRUE

Lake shape data

There are shape files for all lakes in the LimnoTrack database. These can be accessed using the get_lake_shape() function. You need to provide the lake ID (e.g. FENZ ID or Lernzmp ID).

lake <- get_lake_shape(id = 15022)
print(lake)
#> Simple feature collection with 1 feature and 14 fields
#> Geometry type: POLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 1799818 ymin: 5813534 xmax: 1800664 ymax: 5814705
#> Projected CRS: NZGD2000 / New Zealand Transverse Mercator 2000
#>   z_max  source       v  id depth_meas  region  area_ha elevation  id_final
#> 1 5.798 LERNZmp 1295012 156       TRUE Waikato 53.23887  37.99752 LID 15022
#>   gm_type              name_final       dv   z_mean lernzmp_id
#> 1    Peat Rotoroa (Hamilton Lake) 1.248453 2.412844   LID15022
#>                         geometry
#> 1 POLYGON ((1800633 5813535, ...

tm_shape(lake) +
  tm_borders(col = "blue", lwd = 2) +
  tm_basemap("Esri.WorldImagery")

Lake catchment data

Lake catchment data can be accessed using the get_catchment_data() function. You need to provide the lake ID (e.g. FENZ ID or Lernzmp ID). The downloaded data is a list which includes the catchment, reaches, lakes, subcatchments, and LCDB data.

catchment <- get_catchment_data(id = 15022)
names(catchment)
#> [1] "catchment"     "reaches"       "lakes"         "subcatchments"
#> [5] "lcdb"

tm_shape(catchment$catchment, name = "Catchment") +
  tm_borders(col = "red", lwd = 2) +
  tm_shape(catchment$reaches, name = "Reaches") +
  tm_lines(col = "reachtype2") +
  tm_shape(catchment$lakes, name = "Lake") +
  tm_borders(col = "cyan", lwd = 2) +
  tm_shape(catchment$subcatchments, name = "Subcatchments") +
  tm_borders(col = "green", lwd = 2) +
  tm_shape(catchment$lcdb, name = "Land cover") +
  tm_fill(id = "Name_2018", fill = "Name_2018", fill_alpha = 0.5)

Aeme object

For many lakes in the LimnoTrack database, there is an associated Aeme object that contains model parameters and other information. You can access the Aeme object using the get_aeme() function. You need to provide the lake ID (e.g. FENZ ID or Lernzmp ID).

aeme <- get_aeme(id = 15022)
aeme
#>             AEME 
#> -------------------------------------------------------------------
#>   Lake
#> RotoroaHamilton (ID: LID15022); Lat: -37.8; Lon: 175.27; Elev: 38m; Depth: 5.8m;
#> Area: 536716 m2
#> -------------------------------------------------------------------
#>   Time
#> Start: 2013-07-01; Stop: 2023-06-30; Time step: 3600
#>  Spin up (days): GLM: 1095; GOTM: 1095; DYRESM: 1095
#> -------------------------------------------------------------------
#>   Configuration
#>     Model controls: Present
#>     Use biogeochemical model: 
#>           Physical   |   Biogeochemical
#> DY-CD    : Absent     |   Absent 
#> GLM-AED  : Present    |   Present
#> GOTM-WET : Present    |   Present
#> -------------------------------------------------------------------
#>   Observations
#> Lake: Present; Level: Absent
#> -------------------------------------------------------------------
#>   Input
#> Inital profile: Present; Inital depth: 5.798m; Hypsograph: Present (n=33);
#> Meteo: Present; Use longwave: TRUE; Kw: 1.075949
#> -------------------------------------------------------------------
#>   Inflows
#> Data: Present; Scaling factors: DY-CD: 1; GLM-AED: 1; GOTM-WET: 1
#> -------------------------------------------------------------------
#>   Outflows
#> Data: Present; Scaling factors: DY-CD: 1; GLM-AED: 1; GOTM-WET: 1
#> -------------------------------------------------------------------
#>   Water balance
#> Method: 2; Use: obs; Modelled: Absent; Water balance: Present
#> -------------------------------------------------------------------
#>   Parameters: 
#> Number of parameters: 0
#> -------------------------------------------------------------------
#>   Output: 
#> 
#> DY-CD:    
#> GLM-AED:  
#> GOTM-WET:

You can plot the lake hypsograph from the Aeme object using the plot_hyps() function.

plot_hyps(aeme, y = "depth")

You can also plot the meteorological data from the Aeme object using the plot_met() function.

plot_met_tile(aeme, var_inp = "MET_tmpair")