R: NIOZ monitoring data of Westerschelde estuary.

NIOZ Westerschelde monitoring {OceanView} | R Documentation

## NIOZ monitoring data of Westerschelde estuary.

### Description

Part of the long-term monitoring data of the Westerschelde estuary, from 1996 till 2004.

A total of 17 stations were monitored on a monthly basis.

The dataset `WSnioz` is in long format and contains the following variables: oxygen, temperature, salinity, nitrate, ammonium, nitrite, phosphate, silicate and chlorophyll.

The dataset `WSnioz.table` is in tabular format.

The full dataset can be downloaded from: `https://www.nioz.nl/monitoring-data-downloads`

### Usage

    data(WSnioz)
    data(WSnioz.table)

### Format

`WSnioz` is a `data.frame` with the following columns:

- `SamplingDateTime`, a string with the date and time of sampling.

- `SamplingDateTimeREAL`, a numeric value with day as per 1900.

- `Station`, the station number.

- `Latitude`, `Longitude`, the station position.

- `VariableName`, the variable acronym.

- `VariableDesc`, description of the variable.

- `VariableUnits`, units of measurement.

- `DataValue`, the actual measurement.

### Author(s)

Karline Soetaert <karline.soetaert@nioz.nl>

### References

Soetaert, K., Middelburg, JJ, Heip, C, Meire, P., Van Damme, S., Maris, T., 2006. Long-term change in dissolved inorganic nutrients in the heterotrophic Scheldt estuary (Belgium, the Netherlands). Limnology and Oceanography 51: 409-423. DOI: 10.4319/lo.2006.51.1_part_2.0409

`http://aslo.org/lo/toc/vol_51/issue_1_part_2/0409.pdf`

### See Also

image2D for plotting images, package `plot3D`.

ImageOcean for an image of the ocean's bathymetry, package `plot3D`.

scatter2D for making scatterplots, package `plot3D`.

Oxsat for a 3-D data set, package `plot3D`.

### Examples

    # save plotting parameters
     pm <- par("mfrow")
     mar <- par("mar")

    ## =============================================================================
    ## Show stations and measured variables
    ## =============================================================================
     unique(WSnioz[,c("Station", "Latitude", "Longitude")])
     unique(WSnioz[,c("VariableName", "VariableDesc")])

    ## =============================================================================
    ## An image for Nitrate:
    ## =============================================================================

    # 1. use db2cross to make a cross table of the nitrate data
    # assume that samples that were taken within 5 days belong to the same
    # monitoring campaign (df.row).

     NO3 <- db2cross(WSnioz, row = "SamplingDateTimeREAL",
           col = "Station", val = "DataValue",
           subset = (VariableName == "WNO3"), df.row = 5)

    # 2. plot the list using image2D; increase resolution
     image2D(NO3, resfac = 3)

    ## =============================================================================
    ## All timeseries for one station
    ## =============================================================================

     st1 <- db2cross(WSnioz, row = "SamplingDateTimeREAL",
           col = "VariableName", val = "DataValue",
           subset = (WSnioz$Station == 1), df.row = 5)

     Mplot(cbind(st1$x/365+1900,st1$z))

    ## =============================================================================
    ## All timeseries for multiple stations
    ## =============================================================================

     dat <- NULL
     for (st in 1:17) {
       dd <- db2cross(WSnioz, row = "SamplingDateTimeREAL",
              col = "VariableName", val = "DataValue",
              subset = (WSnioz$Station == st), df.row = 5)
       dat <- rbind(dat,  cbind(st, time = dd$x/365+1900, dd$z))
     }

    # select data for station 1, 17
     dat2 <- Msplit(dat, split = "st", subset = st %in% c(1, 17))
     names(dat2)

     Mplot(dat2, lty = 1)

    ## =============================================================================
    ## tabular format of the same data
    ## =============================================================================
     head(WSnioz.table)

    # plot all data from station 1:
     Mplot(WSnioz.table, select = 3:11, subset = Station == 1, legend = FALSE)

     Mplot(Msplit(WSnioz.table, "Station", subset = Station %in% c(1, 13)) ,
       select = c("WNO3", "WNO2", "WNH4", "WO2"), lty = 1, lwd = 2,
       xlab = "Daynr", log = c("y", "y", "y", ""),
       legend = list(x = "left", title = "Station"))

    # reset plotting parameters
     par(mar = mar)
     par(mfrow = pm)

[Package OceanView version 1.0.6 Index]