DEFRA Research Project PE0202

Appendix 3. Spatial and temporal information on catchment soil characteristics

Philip N. Owens, Gavin A. Wood, Lynda K. Deeks and Mike Hann National Soil Resources Institute (NSRI), Cranfield University

1. Introduction

The delivery of phosphorus (P) and sediment from land to watercourses depends on many factors, including slope of the land, soil type and the P content of the topsoil. Information on these variables was needed for the development of the risk assessment tool and also to assist with the catchment monitoring programme within the PSYCHIC project. NSRI provided information on slope, soil type and soil-P content based on several NSRI databases for the two study catchments: the Herefordshire Wye and the Hampshire Avon. This report provides a brief overview of this information.

2. Soil type Figure 1 illustrates the distribution of soils within the Wye catchment (4020 km2 area), and is based on the national vector soil map (NSRI, 2001), which is at 1 km2 grid cell resolution. There are clearly differences in soil type within the catchment, with argillic brown earths dominating in the eastern half of the catchment, with podzolic and raw peat soils dominating in the far western part of the catchment, and with brown earths and stagnogley soils dominating in between these two regions. Brown soils (mainly brown earths and argillic brown earths) cover about 62% of the catchment, and are typically associated with permeable materials at elevations below 300 m.

Figure 1. Distribution of soils within the Herefordshire Wye catchment.

1 Figure 2 shows the spatial distribution of soils in the Hampshire Avon catchment (1716 km2 area). Soils are dominated by rendzinas (56% of catchment), in the middle and northern part of the catchment, with a complex mixture of soils (including gley podzols, stagnogley soils and argillic brown earths) occurring in the southern part of the catchment. Alluvial gley soils clearly occur within the valley of the main channel. Rendzinas typically are shallow and have formed over bedrock or unconsolidated material at or within 30 cm depth.

Figure 2. Distribution of soils in the Hampshire Avon catchment.

3. Soil phosphorus content

3.1 Depth profiles of soil-P NSRI provided information on the P (total and Olsen) content of soils in the two study catchments, based on relationships with soil type and land use (Fraser, 2001; Owens and Wood, 2003). The soil-P data are based on the National Soil Inventory (NSI) database, which represents bulked values for the 0-15 cm topsoil layer for samples collected at 5 km grid intervals throughout England and Wales between 1978 and 1983 (McGrath and Loveland, 1992). However, Owens and Wood (2003) identified that because most P is delivered to rivers via surface pathways, accurate values of the P content of topsoil are vital for the ability of the PSYCHIC model to predict P delivery to rivers. Thus, detailed depth profiles of P were determined for the dominant soil subgroups in the two study catchments (Owens and Deeks,

2 2003, 2004). In most cases, samples were collected from soils under both arable and grassland. Table 1 lists the soils examined in the Avon and Wye catchments, and Figures 3 and 4 illustrate the depth profiles of Olsen-P and total-P for these soils.

Table 1. Description of the soils examined in the Avon and Wye catchments.

Site Soil subgroup† Soil description† % of Number Name catchment Avon catchment A1 3.43 Brown rendzina Shallow well-drained calcareous 32 silty soils A2 3.41 Humic rendzina Shallow, mostly humose, well 14 drained calcareous soils A3 5.11 Typical brown Well-drained calcareous fine silty 10 calcareous earth soils A4 5.71 Typical argillic Well-drained fine and coarse 9 brown earth loamy glauconitic soils Wye catchment W1 5.71 Typical argillic Well drained reddish fine silty 31 brown earth soils W2 5.41 Typical brown Well drained reddish coarse loamy 27 earth soils W3 6.11 Typical brown Well drained fine loamy or fine 12 podzolic soil silty soils W4 7.13 Cambic Slowly permeable seasonally 9 stagnogley soil waterlogged fine silty and clayey soils W5 6.54 Ferric Loamy permeable upland soils 6 stagnopodzols †Based on Avery (1980)

The depth profiles of total-P and Olsen-P shown in Figures 3 and 4 clearly demonstrate that there are variations in soil-P concentrations with depth in uncultivated grassland soils, particularly in the case of Olsen-P. The depth profiles are consistent with expectations for uncultivated grassland soils, with both surface maxima and the marked decreases in soil-P with depth, reflecting inputs of P to the soil surface due to additions of P-based fertilizers, manures and other artificial inputs, and the return of P in dead plants and storage in soil organic matter (Haygarth et al., 1998).

For soils under arable, values of total-P are broadly constant within the plough layer. Concentrations of Olsen-P, however, exhibit maximum values near the soil surface reflecting inputs of fertilisers and manures to the soil surface between consecutive ploughing events. Table 2 demonstrates the differences in the values of soil-P content based on the 0-5 cm increment compared to those based on the 0-15 cm increment for the NSI database for the soils in the Avon and Wye. In most cases, the soil-P concentrations of the surface layers (0-5 cm) are greater (in several instances >100%) than theconcentrations for the 0-15 cm depth.

3 a) b) -1 -1 Total P (mg P kg dry soil) Total P (mg P kg dry soil) 0 1000 2000 3000 0 1000 2000 3000 0 0

30 30 c) d) -1 -1 Olsen P (mg P kg dry soil) Olsen P (mg P kg dry soil) 0 40 80 120 0 40 80 120 0 0

A1 A2 A3 A4

Figure 3. The depth distribution of total-P in (a) arable and (b) grassland soils, and Olsen-P in (c) arable and (d) grassland soils for the Hampshire Avon catchment.

4 a) b) -1 -1 Total P (mg P kg dry soil) Total P (mg P kg dry soil) 0 1000 2000 3000 0 1000 2000 3000 0 0

30 30 c) d) -1 -1 Olsen P (mg P kg dry soil) Olsen P (mg P kg dry soil) 0 40 80 120 0 40 80 120 0 0

W1 W2 W3 W4 W5

Figure 4. The depth distribution of total-P in (a) arable and (b) grassland soils, and Olsen-P in (c) arable and (d) grassland soils for the Herefordshire Wye catchment.

5 Table 2. Comparison of total-P and Olsen-P concentrations for topsoil (0 to 5 cm) and NSI data (averaged for 0 to 15 cm) for the dominant soil types in the Avon and Wye catchment.

Total-P Olsen-P (mg kg-1) (mg kg-1) Site Landuse Topsoil (0-5 cm) NSI Topsoil (0-5 cm) NSIa Avon A1 Arable 1708.6 1157.0 (115) 85.7 29.6 (113) Pasture 1579.9 1476.4 (18) 20.1 32.9 (18) A2 Arable 1796.7 1481.3 (4) 70.0 34.5 (4) Pasture 2317.5 1452.7 (9) 93.0 18.4 (9) A3 Arable 1327.7 1026.7 (130) 66.9 33.0 (127) Pasture - 1130.7 (33) - 21.2 (33) A4 Arable 537.4 767.6 (101) 49.4 37.1 (98) Pasture - 812.0 (56) - 23.8 (56) Wye W1 Arable 822.7 767.6 (101) 63.5 37.1 (98) Pasture 947.2 812.0 (56) 30.7 23.8 (56) W2 Arable 752.9 834.0 (115) 70.1 35.7 (113) Pasture 867.3 976.7 (237) 55.2 20.9 (232) W3 Arable - 1282.0 (6) - 30.7 (6) Pasture 1681.7 1115.9 (86) 57.9 19.8 (83) W4 Arable 1213.9 708.0 (64) 20.8 25.2 (63) Pasture 1216.9 879.2 (160) 17.9 21.7 (157) W5 Arable - - - - Pasture 1173.4 791.0 (21) 61.3 13.9 (21) a It is assumed that mg l-1 approximately equates to mg kg-1 for this database. b(n) numbers in brackets = number of samples

Based on the values of soil-P determined for the soil samples collected in the Avon and Wye catchments, the PSYCHIC model has been run using these to examine the effect of soil-P values on model predictions of P delivery to waters, and the results are shown in Table 3. These results are not definitive for the model as it continues to develop but they indicate the significance of soil-P values to the modelling output. When the new sampled data collected specifically in the two catchments is used in the PSYCHIC model, in the Avon there is a significant increase in the estimated losses, especially when the topsoil-P data are used where there is a 13% increase in P losses reflecting the build-up of soil-P at the surface of untilled soils as discussed above. In the Wye, the difference is much less marked from the sampled data compared to the original NSI assessment, potentially due to the much larger size of the catchment being more representative of the national average. However, as the Wye land use is dominated by permanent pasture the use of the upper 5 cm of topsoil-P does produce an increase in the overall loss from the catchment.

These findings have important implications for the use of soil-P data based on bulked 0-15 cm soil cores for modelling surface transfers of P in river systems, and raise an important question about the relevant soil depth to use in the PSYCHIC (and similar) model.

6 Table 3. Results from the Avon and Wye catchments using the current version of the PSYCHIC modelling methodology and based on using soil-P values from the original NSI data (average for 0-15 cm depth) and those from the soils collected in Table 1 for both topsoil (0-5 cm) and bulked (0-15 cm) depth (see Owens et al., in prep, for further details).

Original Catchment samples Catchment samples NSI from top 5 cm from bulked 15 cm Avon catchment Mean (kg ha-1) 0.21 0.24 0.24 Standard Deviation 0.30 0.35 0.34 Change from original NSI (%) 0 13 10 Wye catchment Mean (kg ha-1) 0.65 0.71 0.67 Standard Deviation 0.61 0.68 0.65 Change from original NSI (%) 0 5 0

3.2 Temporal changes in soil-P The original NSI data are based on samples collected and analysed in the 1970s and 1980s. In the 1990s, NSRI resampled many of the original NSI sites in order to examine whether soil properties (including soil-P) had changed over time. A comparison of the two sets of data revealed that there had been a change over time, due to both real changes in soil-P content and, in the case of total-P, also differences in the use of measuring equipment between the two time periods. As an example, Figure 5 shows the values of Olsen-P for grassland and arable sites for England and Wales. It is clear from Figure 5, and from statistical analysis, that values of Olsen-P have increased over time, especially for soils under arable and ley grass, reflecting additions to soils from artificial fertilisers etc.

Available Phosphorus (arable and ley grass) Available phosphorus (permanent grass)

100 100

80 80 original data original data resampled data resampled data t t n n e e c c r r

e 60 e 60 p p

e e v v i i t t a a l l u u m m u u

C 40 C 40

0 0 0 100 200 300 400 500 600 0 100 200 300 400 500 600 Available P Available P

Figure 5. Changes in soil Olsen-P content based on original (1970s/1980s) and resampled (1990s) NSI data for arable and ley grassland sites (left) and permanent grassland sites (right) in England and Wales (from Loveland, 2000).

Due to the changes in soil-P over time (Figure 5) and due to estimates of the soil-P content of topsoil (0-5 cm) when compared to bulked (0-15 cm) values (Table 2), revised tables of Olsen-P and total-P content of soils were provided to ADAS for use in the PSYCHIC model (Owens and Deeks, 2003).

7 4. Soil and slope characterisation In Owens and Wood (2003), the issue of poor characterisation of soils and slopes within each 1 km square was raised and subsequent work was undertaken.

4.1 Soil slope and topography It is generally accepted that simple averaging of slope gradient to a 1 km resolution model could lead to a loss of important data and lead to a misrepresentative estimate of soil erosion potential. An early version of the PSYCHIC model used such an average. Subsequently, NSRI and ADAS developed an approach to incorporate a characterisation of slope gradient distribution in each 1 km square, where the range of slope was grouped into classes representing important ranges of slope with regard to soil erosion processes (Figure 6). The model runs iteratively on each class, and the modelled output values are averaged according to their area-weighting in each 1 km square. This approach was developed in parallel with the Environment Agency (EA) sediment delivery project (P2-0209) (McHugh et al., 2002) which used the same slope distribution data in a more simplified erosion model.

Figure 6. Characterisation of slope distribution within each 1 km pixel. The inset shows a 1 km x 1 km area with its respective slope distribution histogram indicating the frequency of each slope class.

4.2 Soil characterisation Typically, only the predominant soil series in each 1 km2 area was used in the estimation procedure, which can account for as little as 17% of the total area of all soils. Exploratory work had been investigated in the EA report, P2-209 (McHugh et al., 2002) to include a more representative list of soils for at least 95% of the 1 km2 area. This work was carried through into the PSYCHIC model.

The impact of improved soil characterisation not only affects erosion estimation directly, it also impacts the PSYCHIC model where it derives a representative texture classification for soils in a 1 km square, or when estimating standard percentage run-off, from a soils HOST (Hydrology of Soil Types) class. In order to best estimate sediment and P delivery from soils at a 1 km scale, a complete (or majority) account of soil condition must be obtainable for each mapping unit (MU) – the 1 km pixel.

8 The implications of including at least 95% of soil series in each MU was reviewed based on interim model output. A further, more detailed investigation of the practical effects of better soil characterisation is needed based on the final structure for the PSYCHIC model. This would involve a considerable number of iterations that would be completed by running the model in turn for each soil (along with producing the various derivatives such as the HOST classification). The interim results, however, have highlighted the importance of representative spatial characterisation of soils: for instance, in the Wye catchment, the difference in the estimated value of DP in some cases can be as high as 200% between the estimate if only the predominant soil is taken into account compared with using all soils. The impact is more significant in the spatial patterns that arise.

Figure 7 shows the estimate of DP for the Wye catchment. In the east, the spatial pattern is fragmented, picking up the possibility that soils in this area are more heterogeneous in type than in the west. When all the soils are taken into account, the spatial pattern is smoother and more continuous, and more representative of what one would expect. The most striking effect of only using a single predominant soil per pixel, is to alter the estimates along the river corridors (Figure 8).

Figure 8. A map of the Wye catchment, showing the differences between using a single predominant soil series compared with using all soils. Positive values indicate where the predominant soil method over-estimates output values, which are in percent. The approximate positions of the rivers are indicated.

Figure 7. PSYCHIC model output of P (kg DP ha-1 year-1) for the Herefordshire Wye catchment. The left-hand figure indicates the results obtained using only the predominant soil series in each 1 km pixel. The right hand figure indicates output where all soils are used in the estimation and area- weighted according to their relative proportions.

10 The direct interpretation of this is that the predominant soils in the river corridor areas have a small contribution to diffuse pollution, and it is the other soils present that have the greater impact. This is possibly because the soil characteristics are more heterogeneous in these areas and despite being a predominant soil, that soil may comprise only a small percentage of the 1 km pixel’s total area (as low as 17% in some cases). In these cases, when the remaining soils are included into the model, the result is to increase the general output values.

5. References Fraser, A. (2001). Characterisation of the soils, landuse and phosphorus status of topsoils in the Herefordshire Wye and Hampshire Avon catchments. NSRI Report, National Soil Resources Institute, North Wyke. Haygarth, P.M., Lepworth, L. and Jarvis, S.C. (1998). Forms of phosphorus transfer in hydrological pathways from soil under grazed grassland. European Journal of Soil Science 49, 65-72. Loveland, P.J. (2000). Comparison of original and re-sampled National Soil Inventory data. Final Report to MAFF for Project SP0506. NSRI Report, National Soil Resources Institute, Silsoe. McGrath, S. P. and Loveland, P.J. (1992). The Soil Geochemical Atlas of England and Wales. Blackie, London. McHugh, M., Wood, G.A., Walling, D.E., Morgan, R.P.C., Zhang, Y., Anthony, S. and Hutchins, M. (2002). Prediction of Sediment Delivery to Watercourses from Land, Phase II, Environment Agency R & D Technical Report No P2-209. Owens, P.N. and Wood, G.A. (2003). Phosphorus and sediment yield characterisation in catchments (PSYCHIC): Contribution from the National Soil Resources Institute (NSRI), Cranfield University. NSRI Report, National Soil Resources Institute, North Wyke. Owens, P.N. and Deeks, L.K. (2003). Phosphorus and sediment yield characterisation in catchments (PSYCHIC): Revised phosphorus content of topsoil in the Herefordshire Wye and Hampshire Avon catchments. NSRI Report, National Soil Resources Institute, North Wyke. Owens, P.N. and Deeks, L.K. (2004). The role of soil phosphorus in controlling sediment- associated phosphorus transfers in river catchments. In: Sediment Transfer Through the Fluvial System. IAHS Publication 288, IAHS Press, Wallingford, 444-450. Owens, P.N., Deeks, L.K. et al. (in prep). Variations in the depth distribution of phosphorus in soil profiles and implications for model-based catchment-scale predictions of phosphorus delivery to surface waters.