Water chemistry of combined surface and subsurface runoff from the North Wyke Farm Platform, with hydrologically isolated catchments sown with different pasture types

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This dataset contains water quality information of combined surface and subsurface runoff, taken from catchments on the NWFP. The NWFP is separated into three self-contained farms (“farmlets”) which are managed according to different operational philosophies or practices, and these farming systems are updated periodically. During the period over which this dataset was collected, the three 22ha farmlets were all pasture based and used for livestock production in the form of a beef herd and sheep flock. From 2010 to between 2013 and 2015 (depending on the catchment) the farmlets were all under permanent pasture and are referred to as the ‘baseline’ period in the Treatment column of the data. The first system change period (2013/5 to 2019) was either a reseed with innovative grass species with desirable traits, reseeded with a mixture of white clover and the same innovative grass species (‘legumes’), or continued permanent pasture (‘permanent pasture’).

This dataset contains water quality information of combined surface and subsurface runoff, taken from catchments on the NWFP. The NWFP is separated into three self-contained farms (“farmlets”) which are managed according to different operational philosophies or practices, and these farming systems are updated periodically. During the period over which this dataset was collected, the three 22ha farmlets were all pasture based and used for livestock production in the form of a beef herd and sheep flock. From 2010 to between 2013 and 2015 (depending on the catchment) the farmlets were all under permanent pasture (map 1 in figure) and are referred to as the ‘baseline’ period in the Treatment column of the data. The first system change period (2013/5 to 2019, map 2 in figure) was either a reseed with innovative grass species with desirable traits (‘reseed’ in the Treatment column of the data), reseeded with a mixture of white clover and the same innovative grass species (‘legumes’), or continued permanent pasture (‘permanent pasture’).

The catchments of the NWFP are hydrologically isolated, and the highly impermeable subsoil means that water moving as surface or subsurface runoff is captured by a bounding drainage system and directed towards a flume, with one flume per catchment. Each farmlet consists of five catchments (with each consisting of one or two fields) and are highly instrumented and monitored, allowing the collection of a wide variety of environmental data to complement agricultural production data. Core NWFP datasets are open and include in-situ water flow and chemistry taken at 15-minute intervals; 15-minute Met measurements; 15-minute soil moisture measurements; 30-minute GHG emissions; soils, crop and botanical field survey data; livestock and crop performance data; and farm operational activities (see related output).
In this dataset, samples were collected either as grab-samples (bottles put under the flow of water at the flume) or via ISCO autosamplers set up to sample the flume water. The date and time of the sample being taken is recorded in Datetime_lab. Brief descriptions of laboratory analyses conducted on these samples are given in Column_units_and_descriptions.csv.

In addition to the experimental data, where the water quality was assessed in the lab, in-situ data (available via the NWFP data portal, see related information for the link) have been included where they were felt to complement the dataset. As some measurements were made both in the lab and in-situ, column names include the subscripts ‘_lab’ or ‘_portal’ for clarity. In-situ data includes discharge (flow) rate, conductivity, dissolved organic matter, ammonium, ammonia, nitrogen oxides, pH, reactive and total phosphorus, turbidity, flume temperature and precipitation, where available. However, as in-situ measurements cannot be performed at very low flows, there are gaps in this in-situ data. Users should note that the manual samples were taken on no particular schedule (recorded in Datetime_lab) and are matched with the closest in-situ measurement, identified in Datetime_portal. Therefore, potentially there could be an error of up to 7.5 minutes between the two, although typically it is far less than this.

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