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emoval varied between periods from –84% to 20% and –183% to 46%, respectively. The area is therefore at times a source of nutrients, particularly during low flows. The removal of FIOs is good (e.g. 83% for Escherichia coli bacteria; Vinten, pers. comm.). A positive (but not significant) relationship was observed between % removal of SS, total P and total N and hydraulic load which was attributed to the entry of larger particles (with faster settling velocity and containing total P and N) into the pond at higher flows. Marginally significant relationships between total P (P = 0.088) and total N (P = 0.075) removal and SS removal suggest that designing a pond/wetland to maximise SS removal should also result in good total P and N removal. In order to elucidate P retention within farm ponds/wetlands, the fractionation of P needs to be explored in more detail, although this was not possible at Langside because of the field storage of water samples. Figure 1: Inlet discharge and total P concentrations at the inlet and outlet to Langside pond/wetland, days 138-180 of 2005. Horizontal bars on total P values show the time period represented by each sample 65
Table 1: Hydraulic load, mean water quality and overall mass removal efficiency of pollutants for Langside pond/wetland for five periods, 2005 Start time End time Hydraulic load Mean concentration (mg/L) inlet/outlet (Days 2005) (m 3 /day) SS NH 4 - N TN TP 138.6 144.6 0.32 115/47.8 0.17/0.32 2.78/2.77 0.24/0.30 150.7 158.6 1.27 44.0/22.4 0.31/0.39 3.04/2.93 0.15/0.20 158.6 161.3 0.41 10.9/13.8 0.30/0.11 1.41/2.60 0.06/0.17 161.3 164.3 0.58 20.4/15.5 0.36/0.23 2.83/2.15 0.18/0.12 171.6 172.5 1.40 121/37.3 0.34/0.14 3.20/2.57 0.41/0.22 Overall removal efficiency 53% -15% 4% -12% Comparison of Biodiversity between existing Farm Pond/Wetland Systems Measures of the abundance, richness and diversity (the Shannon diversity index, commonly used to describe the value of a habitat) for vegetation and macroinvertebrates are shown in Table 2 for the three farm wetland/pond systems surveyed in July 2005. For vegetation, the highest species richness is found at Langside, the highest abundance and Shannon diversity at Old Castle, while Black Loch has the lowest abundance, richness and diversity. Although the Old Castle system is considerably younger than Langside, vegetation is clearly very well established. For macroinvertebrates, the highest richness and Shannon diversity occurs at Old Castle and Langside, while the lowest diversity is at Black Loch and the lowest abundance at Langside. Table 2: Measures of vegetation and macroinvertebrate abundance, richness and diversity from sampling of three Scottish farm wetland/pond systems, July 2005 Measure Pond/wetland system Old Castle Langside Black Loch Vegetation Total abundance 22337 21771 13018 Density (individuals m -2 ) 745 726 434 Richness (No. of species) 17 23 15 Shannon diversity index 2.01 1.55 1.42 Macroinvertebrates Total abundance 814 90 1340 Richness (No. of families) 20 13 11 BMWP (Biological Monitoring Working Party) score 37 33 24 Shannon diversity index 2.30 2.29 1.18 ASPT (average score per taxon) 4.63 4.71 4.00 Most measures of abundance and diversity are similar at Old Castle and Langside (apart from macroinvertebrate abundance and the Shannon diversity index for vegetation which are both considerably lower at Langside) but the species 66
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International Water Association AGR
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2006 Conference Organising Committe
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Theme 2: Cost-effectiveness of Best
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Poster Presentations The Farm Soils
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viii
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managers need support in understand
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During the past 20 years, it became
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infiltration); and (4) capture, sto
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DOMINATING PARAMETERS OF IMPAIRMENT
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Using the results of the unsupervis
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Kohonen T (2001). Self-Organizing M
Page 23 and 24: WATER FRAMEWORK DIRECTIVE IMPLEMENT
Page 25 and 26: Table 1: Modelled total annual loss
Page 27 and 28: • It should be possible to apply
Page 29 and 30: Scottish Executive against 18 measu
Page 31 and 32: REFERENCES Anthony S, Betson M, Lor
Page 33 and 34: ased on the ‘drainage basin’ in
Page 35 and 36: management practices’ (BMPs) toge
Page 37 and 38: It is envisaged that these data wil
Page 39 and 40: testing (including climate change)
Page 41 and 42: Council of the European Communities
Page 43 and 44: DECREASING THE NITROGEN SOIL SURFAC
Page 45 and 46: Table 1: Overview of the measures c
Page 47 and 48: Table 2: Costs (C), effects (E) and
Page 49 and 50: Figure 2: Combination of ‘best av
Page 51 and 52: MATERIALS AND METHODS At the 5-km 2
Page 53 and 54: REFERENCES Jordan P, Menary W, Daly
Page 55 and 56: Although the TMDL programme origina
Page 57 and 58: grassland and heather moorland, sup
Page 59 and 60: Given that the release of P from th
Page 61 and 62: to the underlying causes, and thus
Page 63 and 64: All water body use attainment infor
Page 65 and 66: indicate the possible presence of p
Page 67 and 68: DEVELOPMENT AND IMPLEMENTATION OF M
Page 69 and 70: BMP is being implemented and the ap
Page 71 and 72: THE USE OF PONDS TO REDUCE POLLUTIO
Page 73: established pond/wetland for nutrie
Page 77 and 78: Comparable SS removals have been re
Page 79 and 80: Reddy GB, Hunt PG, Phillips R, Ston
Page 81 and 82: In general, the combinations of mea
Page 83 and 84: final word on the POMs selection an
Page 85 and 86: CONCLUSIONS The ERBD project team i
Page 87 and 88: Table 1: A summary of the measures
Page 89 and 90: Table 3: A summary of the represent
Page 91 and 92: cost (£'000/farm) or reduction in
Page 93 and 94: ECONOMIC IMPLICATIONS OF MINIMISING
Page 95 and 96: spread cattle slurry in the autumn
Page 97 and 98: £25,000. The investment in trailin
Page 99 and 100: Studies on a drained clay soil at B
Page 101 and 102: REFERENCES Anon (2000). Fertiliser
Page 103 and 104: (Haygarth and Jarvis, 1999). The vo
Page 105 and 106: Application Representative farm sys
Page 107 and 108: Table 2: Modelled cost-curve for th
Page 109 and 110: ASSESSING THE SIGNIFICANCE OF DIFFU
Page 111 and 112: In the absence of data on the sourc
Page 113 and 114: Magnitude of Impacts The magnitude
Page 115 and 116: D. Use relative area of farm and wh
Page 117 and 118: ADAS has developed a matrix for Def
Page 119 and 120: Dickson JW, Edwards T, Jeffrey WA,
Page 121 and 122: 60% phosphorus and 50% nitrogen of
Page 123 and 124: RESULTS AND DISCUSSION Landscape St
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was contributed to the low vegetati
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iological uptake in a grassed area.
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Tim US, Jolly R and Liao HH (1995).
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to control SS and P loads from agri
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Total P inputs in fertilisers and m
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Within the Teme catchment, largest
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A RISK ASSESSMENT AND MITIGATION ST
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Environmental Monitoring The primar
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BMP measure 1 (exclusion of stock f
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(a) With reference to the increase
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ACKNOWLEDGEMENTS SAC acknowledges f
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The Environment Sensitive Farming (
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improved further as a result of att
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to do more to reduce pesticide impa
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MANAGING DIFFUSE POLLUTION FROM A F
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turbulent air mixing. The effect th
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Although nitrate leaching can be re
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infiltration of water sheeting off
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Nisbet TR, Orr H and Broadmeadow S
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anthropogenic activities are pollut
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monitoring is determined up front b
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(USEPA). Nevertheless, by applying
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• Sampling equipment •Laborator
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Reinert RE, Knuth BA, Kamrin MA and
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Tier 3 - Tier 3 of LMCs is planned
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policy literature, although this is
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Figure 1: Individual-collective spe
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• tailoring activities to local c
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ACKNOWLEDGEMENTS The support of the
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THE EFFECT OF DIFFUSE POLLUTION FRO
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equires the Minister to designate a
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protection and restoration, sustain
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expensive. One-to-one contact becom
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farmers. In England, recent policy
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practices but, hopefully, the chang
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A CASE STUDY: ADOPTION OF BEST MANA
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The approaches taken by Brittany to
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MANURE TREATMENT By January 2005, t
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REGULATORY OPTIONS FOR THE MANAGEME
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There are also measures that contro
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widely recognised as needing much a
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ploughed, of rivers and streams tha
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is the only mechanism identified fo
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PHOSPHORUS STORAGE IN FINE CHANNEL
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structure and minimum level of main
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REFERENCES May L, Place C, O’Hea
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LOUND CATCHMENT PROJECT: WORKING WI
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MINIMISING THE PRESSURES AND IMPACT
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Predicting Bathing Water Quality Vi
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Risk of illness percentages were ca
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Table 4: Expected lifetime benefits
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DETERMINATION OF THE VETERINARY ANT
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Thin Layer Chromatography The sampl
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Table 2: Regression functions and c
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OPPORTUNITIES AND CONSTRAINTS FOR U
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to land managers and agency staff t
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stakeholders, together with their i
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REFERENCES EC (2000). Directive 200
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A third scenario was applied to Clu
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Based on a detailed distribution of
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could be misleading. The results of
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TACKLING DIFFUSE NITRATE POLLUTION:
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AMMONIA VOLATILISATION FROM CATTLE
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and 27% of the soil surface at 80 m
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FIELD TESTING OF MITIGATION OPTIONS
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techniques can significantly reduce
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NITRATE CONTAMINATION OF GROUNDWATE
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MATERIALS AND METHODS At two UK sit
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ACKNOWLEDGEMENTS Funding of this wo
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y standard methods and fresh, end o
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comparable to those in water draini
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Results may be influential in deter
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• numbers and distribution of liv
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Using this method of classification
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Table 5: Results of land use scenar
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CONCLUSIONS As a decision support t
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types. This paper reports results f
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N Losses in Drainage Water Mean nit
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SOIL AND CROP MANAGEMENT EFFECTS ON
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treatments, typically 10 storm even
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Tramline Effects In both years, obs
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Notes 278
show all

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