The influence of large-scale climate patterns on sediment loss from agricultural land – exploration using an instrumented field and catchment scale platform

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This dataset contains the data used in the article “The influence of large-scale climate patterns on sediment loss from agricultural land – exploration using an instrumented field and catchment scale platform” (link in the related resources), if it is not available elsewhere. Data includes the Western Europe Pressure Anomaly (WEPA) index, and the water flow, turbidity and suspended sediment concentrations in field and river catchments. The suspended sediment concentrations were estimated from the turbidity measurements, and the data used to calculate the rating curves for these estimations is also provided.

The file WEPAi.csv contains the Western Europe Pressure Anomaly (WEPA) index. The WEPA index uses sea level pressure data from 1943 - 2024 to explain winter wave height variability on the coast of W. Europe. Each monthly value corresponds to the normalised deviation around the mean of that month across all years 1943-2024. The impact of the WEPA index is dependent on the month. For example, a strong positive January WEPA means a stormier, wetter and warmer winter month, with larger waves than usual for January. A strong positive August WEPA means a colder summer month (less anticyclonic conditions), and larger August waves. More information about the WEPA index is available in the paper https://doi.org/10.1002/2016GL072379.

The NWFP.csv contains data that originate from the North Wyke Farm Platform (NWFP), a UK National Biosciences Research Infrastructure in SW England. The NWFP is split into a number of self-contained farms (‘farmlets’) that are managed according to different operation philosophies or practices. Within each farmlet are a number of hydrologically isolated field-scale catchments, and the slope and soil type of the NWFP means that all water falling within a catchment flows out via a flume. The flume is instrumented for the determination of various parameters, including water chemistry, turbidity, and flow rate, at 15-minute intervals. The data presented here are from two catchments with different pasture types. Metadata on the design of the NWFP are available at https://doi.org/10.23637/rothamsted.98y1x, with details about the collection of water samples at https://doi.org/10.23637/rothamsted.98y34.

The Taw.csv contains data from the landscape scale catchments of the Taw River. A map and more information about the project can be found at https://www.rothamsted.ac.uk/project/upper-river-taw-observatory-urto. Information about the collection of data in these catchments, and full data from the 2018-2019 years, can be found at https://doi.org/10.23637/rothamsted.9882v.

The NWFP.csv and Taw.csv files both contain flow, turbidity and suspended sediment concentrations. In each case, automated flow and turbidity measurements were taken in-situ, every 15 minutes. From these, the suspended sediment concentration was estimated, using the rating curve equations presented in Column_units_and_descriptors.csv. These equations are specific to the catchment.

The file Taw_rating.csv contains in-situ turbidity readings and suspended sediment concentrations measured in the laboratory, in waters from the Taw catchment. These values were used to produce the rating curves (turbidity v suspended sediment), which in turn were used to estimate the suspended sediment concentrations in the Taw catchment in the larger dataset, presented in Taw.csv.

The raw data used to generate the rating curve equations used in NWFP.csv are available at https://rres-td.shinyapps.io/Suspended_sediment_versus_turbidity_rating_curves/. To isolate the data used to generate the arable cover rating curve, users should select study = FP083, Catchment = 15, and Ploughing status = recent; other options are immaterial. To isolate the data used to generate the grassland rating curve, users should select study = FP083, Catchment = 13; other options are immaterial. Please note that the rating curve equation applied to the NWFP.csv data is not the same as appears on this external dataset, as we have applied a regression equation that better fits the data, and the equations can be found in column_units_and_descriptors.csv.

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