1 drainage and environment, results of the monitoring of non point source pollution viesturs jansons...
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Drainage and Environment, Results of
the Monitoring of Non Point Source Pollution
Viesturs Jansons
Department of Environmental Engineering and Water Management
Latvia University of Agriculture
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Water pollution sources
Point source pollution Non-point source pollution
• hard to determine the nature, extent, transport and fate of contaminants from agriculture
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The contribution of Agriculture to N and P inputs into surface water in EU countries
Country N P
Belgium 66*
Denmark 77 26
France 55 No data
Germany 57 48
Italy 69 31
Sweden 45 No data
UK 89** N and P from the agriculture to air, soil and wter
Source: P.De Clercq et.all. Nutrient Management legislation in European countries. 2001, Wageningen. Netherlands.
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Monitoring of agricultural non-point source pollution , Bērze monitoring site
Small catchment station - 368 ha, Field drainage station - 77 ha,
•Constructed 1966. •In operation (hydrological data) since 1967. •Water quality sampling programme since 1994. •Renovated measurement structure and new equipment installed in 2006.
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Bērze monitoring station 2005
Berze.kmz
Moldova, 3.10 - 6. 10. 2006 6
Berze monitoring siteMeasurement structure V–shape Crump weir
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Berze monitoring site
Measurement equipment - YSI data loggers, powered from solar panels. GSM data transfer with mobile phone from stations to university PC.
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Results: Nutrient concentrations, 1994-2010
11,3 mg/l NO3-N
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Measurements with nitrate zonde
YSI 6000XLM
•Water to
•Conductivity•Dissolved O2
•Nitrate / N•Ammonium /N•ORP
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Impact of the extreme climate conditions on nitrogen run-off (autumn 2006 - winter 2007.)
Dry and hot summer (19.VI.2006)
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Impact of the extreme climate conditions on nitrogen run-off (autumn 2006 - winter 2007.)
Bērze drenu lauks / Berze drainage field
0,00
0,20
0,40
0,60
0,80
1,00
1,20
1,40
1,60
1,80
2006
.11.
0820
06.1
1.09
2006
.11.
10
2006
.11.
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2006
.11.
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2006
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2006
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2006
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2006
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2006
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2006
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2006
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2006
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2006
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0
20
40
60
80
100
120
140
160
180
Caurplūdums / Discharge l / s Nitrāti / Nitrate mg/l
Q, l s-1
N / NO-13 mg l-1
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Impact of the extreme climate conditions on nitrogen run-off (autumn 2006 - winter 2007.)
Content of the mineral nitrogen, mg kg-1 dry soil
2006.g. autumn 2007.g. spring
Field
Soil layer
(cm) NO3- N NH4-N NO3- N NH4-N
0 - 30 21.4 6.6 2.6 4.1
30 - 60 6.8 3.3 6.1 3.1 Silarāji
60 - 90 1.3 2.7 8.2 2.7
0 - 30 2.3 3.6 2.2 3
30 - 60 0.5 3.1 0.8 2.4 Dzelzarāji
60 - 90 0.5 2.9 0.6 2.3
0 - 30 16.6 4.1 7.1 2.9
30 - 60 3.3 3.3 5.7 3.1 Klaipiņi
60 - 90 0.9 3.4 5.1 2.6
0 - 30 11.4 3.9 3.4 3.5
30 - 60 1.7 3.1 3.1 3.2 Puķes
60 - 90 1.3 2.6 2.4 2.7
0 - 30 14 4.1 3.5 3.2
30 - 60 9.6 3.4 5.5 3.4 Vāverītes
60 - 90 1.9 3 4.9 3
0 - 30 34 3.7 5.9 3.7
30 - 60 18.9 3.7 7.9 3.3 Kāpas
60 - 90 7.1 3.2 11.3 3.1
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Nitrogen Run-off / Load L= C Q
0,00
2,00
4,00
6,00
8,00
10,00
12,00
14,00
Janu
ary
Febr
uary
Mar
chA
pril
May
June July
Aug
ust
Sept
embe
rO
ctob
erN
ovem
ber
Dec
embe
rJa
nuar
yFe
brua
ryM
arch
Apr
ilM
ayJu
ne July
Aug
ust
Sept
embe
rO
ctob
erN
ovem
ber
Dec
embe
r
N tot kg/ha year Nitrogen run-off, 2006-2007
Berze catchment
Berze drainage
L dr 2007=37,3 kg N /ha
L dr 1994-2010 = 17,8 kg N /ha
NHF XXVI Riga 2010 14
Water Quality assessment Good water quality (WFD 2015)?
Numeric values of the parameters / standards ?
US EPA method based on percentile selection of data plotted as frequency distribution could be used.
(EU JRC publication: A.C. Cardoso et al; "Criteria for the Identification of Freshwaters Subject to Eutrophication)
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Monitoring sites, drainage field scale
6,2
10,312
3,869
13,225
7,383
4,351
3,166
8,935
1,1
0,16
0,241
1,825
0,01
0,1
1
10
100
0 10 20 30 40 50 60 70 80 90 100
probability %
N-NO3 mg L-1
B?rze drainage field (76.6 ha)Mellup?te drainage field (12.95ha)Vienziemite drainage field (67 ha)GammaBerzeDrGammaMellDrGammaVienzDr
11,2 mg l-1 N-NO3
Probability (Gamma distribution) Curves for the Nitrate Values Evaluation in the Drainage field Run- off
Fair
Good
ExcelentBad
Poor
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Numeric Values for Water Quality Criteria
Ntot (mg L-1) Ptot (mg L-1) Agricultural land Agricultural land
Quality class
Field Drainage
Small catchment
Field Drainage
Small catchment
Excellent 4.5 1.5 0.015 0.025
Good 4.5-5.5 1.5-2.5 0.015-0.020
0.025-0.050
Fair 5.5-10.0 2.5-7.5 0.020-0.075
0.050-0.150
Poor 10.0-12.0 7.5-10.5 0.075-0.135
0.150-0.250
Bad 12.0 10.5 0.135 0.250
Climate change regional models (SMHI) show that in the Northern and Central part of the Baltic region:
•Winter precipitation and temperature could increase, but snow packs will decrease;
•Shorter duration of snow cover, and frequent melting periods may take place;
•Summer temperatures could increase, but rainfall decrease, extreme weather conditions (floods, dry weather) may occur.
Drainage run-off and Climate change
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Conclusions 1. Water quality nutrient criteria may be developed for run-off from farm
land for the field drainage and small catchment.
2. Criteria could be developed taking into account available monitoring information in different geographical scales, and may be adjusted with neighboring EU countries with similar regional climate, soil, and crop management conditions, e.g. Baltic - Nordic countries.
3. Field drainage / small catchments’ water quality assessment should include full scale of water quality classes (excellent poor). Reference values for nutrients concentration (mg L-1) for water quality classification (5 classes according WFD) could be designated using following percentiles: (1) <90% excellent quality, (2) 90 – 75% good quality, (3) 75 – 25% fair quality; (4) 25-10% poor quality; (5). > 10% bad quality.
4. Taking into account climate changes, in future drainage may play more important role in agriculture , but could cause an increase of non-point source pollution from agriculture.
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Thank You for attention! Questions?
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