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Nitrate leaching to groundwater under agricultural land uses – a case study from Israel
Daniel Kurtzman, Yehuda Levi & Roi Shapira
MARSOL, Water Quality meeting, Algarve Portugal, 26-6-2015
100 years of intensive agriculture with available mineral
nitrogen
“… improved nitrogen fertilization of the soil brings new nutritive riches to
mankind … the chemical industry comes to the aid of the farmer who, in the
good earth, changes stones into bread.”
Fritz Haber ended his Nobel Prize (1918) lecture with the following words
Erisman et al., 2008, Nature
Geoscience
“The situation has, however,
developed into overuse of nitrogen
in agriculture as a straightforward
‘cheap’ insurance against low
yields with all the concomitant
negative side effects.”
Kourakos et al., 2012 Water Resources Research
“Nitrate-nitrogen is by far the most common type of
groundwater contamination associated with agricultural
activities [e.g., Spalding and Exner, 1993; Harter et al.,
2002; Spruill et al., 2002; Van Drecht et al., 2003; Burow et
al., 2010; Sutton et al., 2011; United States Environmental
Protection Agency Science Advisory Board (USEPA), 2011].”
Nitrate problems in the Israeli Coastal Aquifer are
concentrated in cultivated land on lighter soils
Kurtzman et al., 2013
Water and nitrate fluxes are calibrated to deep vadose-
zone data
Strawberry
Persimmon
Potato
Citrus
����������4���� + ����������4
���� = �������������������4
���� � − ����������4���� − ������4��������4 − ����������������4 − ����������������4
������4 = ����−����4������4
����������3���� = ��
�����������������3���� � − ����������3
���� − ������3��������3 + ����������������4 − ������������������3
ShK
z
hhK
zt
h −
+∂∂
∂∂=
∂∂
)()()(θ
Flow – Richards Eq. with root uptake (van Genuchten-Mualem hydraulic functions)
Transport – ADE Eq. with sink\source terms (linear adsorption for NH4)
Nitrogen transient transport modeling (Hydrus1D)
root zone CNO3
Up
-ta
ken
CN
O3
Up-scaling to a groundwater flow and nitrate-transport model
(MODFLOW, MT3DMSU)
Model area
13 km2
Vegetables
Deciduous
Citrus
Boundary C.
Flow Calib.
Transport C.
Landuse coverage
2000 – Survey of
Israel
Flow model
Nitrate transport model model
Top layer of the ground water model
1) Land use (color)
2) Depth of the
unsaturated zone (m)
Each landuse
unsaturated model was
extended to all the
depths that it appears
Duration of runs
Unsaturated models
1962-2012
Groundwater model
1992-2012
Vegetables Deciduous Citrus Non-
cultivated
Water flux - recharge (mm/yr) 330 400 200 170
NO3- flux to water table
(kg-N/ha/yr)200 130 120 10
NO3- concentration (mg/l) 268 144 266 20
Long-term average fluxes
Average Conc.Bias MAE
N Well nameCalculated Measured
67.7 20.0 -47.8 47.8 14
63.6 51.1 -12.5 12.5 10
54.6 52.9 -1.7 14.6 31
68.6 54.1 -14.5 14.5 24
73.3 59.3 -14.0 14 9
73.3 60.5 -12.8 15.1 13
75.1 65 -10 12.7 13
63 66.5 3.6 9.3 17
75.9 70 -5.9 11.4 10
75.3 75 -0.3 9.9 15
76.8 87 10.2 11.6 13
70.3 100.5 30.1 30.1 14
89.5 115.2 25.7 26 11
71.6 130.4 58.8 58.8 14
71.3 72.0 0.3 20.1 13 Average
8.1 28.5 Standard Dev.
0
20
40
60
80
100
120
0 50 100 150
Ca
lcu
late
d m
g/l
Measured mg/l
Calibration of the nitrate-transport model (1)
AverageBias MAE
NCalculated measured
18.3 20.0 1.6 8.2 14
54.0 51.1 -2.9 4.0 10
52.3 52.9 0.6 14.2 31
64.4 54.1 -10.3 10.3 24
63.4 59.3 -4.0 4.7 9
53.2 60.5 7.3 8.0 13
68.1 65.0 -3.1 10.6 13
67.2 66.5 -0.6 10.8 17
78.8 70.0 -8.8 13.2 10
77.3 75.0 -2.3 10.4 15
91.1 87.0 -4.1 11.5 13
104.1 93.5 -10.6 10.6 1
97.0 100.5 3.5 11.6 14
107.4 115.2 7.8 14.8 11
118.9 130.4 11.5 18.9 14
72.2 72.0 -0.6 11.2 13 Average
25.8 28.5 Standard Dev.0
40
80
120
160
0 40 80 120 160
Ca
lcu
late
d m
g/l
Measured mg/l
0
50
100
150
200
250
300
350
0,1 0,6 1 2,8 5 10
Nu
mb
er
of
mo
de
l ce
lls
Nitrate Flux multiplier
Calibration of the nitrate-transport model (2)
Simulations of the future with different N-
Fertilization rates
30
40
50
60
70
80
90
100
110
120
2012 2017 2022 2027 2032 2037 2042 2047 2052
NO
3 m
g/l
Year
1
0.75
0.5
70 mg/l
Fertilization Level
Average NO3 in all wells
Conclusions
• Nitrate contamination in groundwater is a worldwide problem concentrated in aquifers under cultivated land in relatively light soils.
• At the 10 km2 scale – the fluxes obtained by vadose-zone analysis on the field scale and farmers reports, classified to a small number of crops, were sufficient for reproduce the total mass of water in the aquifer.
• Nevertheless, it can not reproduce the spatial variability of groundwater nitrate concentrations – Only extremely high nitrate fluxes at the water-table can explain the very high concentrations – this is probably partly due to problems or extreme practices in the near vicinity of the well.
–
0
100
200
300
400
500
600
700
0 20 40 60 80 100 120 140 160
N u
pta
ke (
mg
-N/d
ay
)
N in root zone (mg/L)
--
RU_N = In_N - Dr._N - Sinks_N
Sinks_N= In_N - Dr._N
Kurtzman et al., 2013
0
100
200
300
400
500
600
700
800
900
0 10 20 30
Dep
th (c
m)
0
100
200
300
400
500
600
700
800
900
0 100 200 300 400 500
Dep
th (c
m)
0
100
200
300
400
500
600
700
800
900
4% 9% 14% 19%
Dep
th (c
m)
O1
Sandy loam
Effluents
TI1 TI2 TI3TI1 TI2 TI3TI1 TI2 TI3
0
100
200
300
400
500
600
700
800
900
0 5 10 15
De
pth
(cm
)
0
100
200
300
400
500
600
700
800
900
20 40 60 80 100 120
De
pth
(cm
)
0
100
200
300
400
500
600
700
800
900
0% 10% 20% 30% 40%
Dep
th (
cm)
O2
Sandy loam
Effluents
Water content (g g-1) Cl- (mg kg-1) NO3 -N(mg kg-1)
0
100
200
300
400
500
600
700
800
900
0 10 20 30 40
De
pth
(cm
)
0
100
200
300
400
500
600
700
800
900
0 100 200 300
De
pth
(cm
)
0
100
200
300
400
500
600
700
800
900
0% 5% 10% 15% 20% 25%
De
pth
(cm
)
O3
Sandy loam
Fresh, local
well
-
0
50
100
150
200
250
300
0
200
400
600
800
1000
1200
19
85
-19
86
19
86
-19
87
19
87
-19
88
19
88
-19
89
19
89
-19
90
19
90
-19
91
19
91
-19
92
19
92
-19
93
19
93
-19
94
19
94
-19
95
19
95
-19
96
19
96
-19
97
19
97
-19
98
19
98
-19
99
19
99
-20
00
20
00
-20
01
20
01
-20
02
20
02
-20
03
20
03
-20
04
20
04
-20
05
20
05
-20
06
20
06
-20
07
20
07
-20
08
20
08
-20
09
20
09
-20
10
NO
3-N
flu
x (
kg
/ha
/ye
ar)
Wa
ter
flu
x (m
m/y
r)
Precipitation Recharge (21 m) NO3-N bottom flux
(a)
0
50
100
150
200
250
300
0
200
400
600
800
1000
1200
19
85
-19
86
19
86
-19
87
19
87
-19
88
19
88
-19
89
19
89
-19
90
19
90
-19
91
19
91
-19
92
19
92
-19
93
19
93
-19
94
19
94
-19
95
19
95
-19
96
19
96
-19
97
19
97
-19
98
19
98
-19
99
19
99
-20
00
20
00
-20
01
20
01
-20
02
20
02
-20
03
20
03
-20
04
20
04
-20
05
20
05
-20
06
20
06
-20
07
20
07
-20
08
20
08
-20
09
20
09
-20
10
NO
3-N
flu
x (
kg
/ha
/ye
ar)
Wa
ter
flu
x (m
m/y
r)
Precipitation Recharge (11 m) NO3-N bottom flux
(b)
Kurtzman et al., 2013
Fertilizer
addition
N
Irrigation
water
N
Fertilizers
N
Root uptake
Nitrate Flux to
GW
Orchard 1 – irrigated with treated waste water
100% 70 320 230 110
75% 70 240 220 60
50% 70 160 180 30
25% 70 80 130 20
0 70 0 60 20
Orchard 2 – Irrigated with local groundwater
100% 90 240 230 70
75% 90 180 210 30
50% 90 120 180 20
25% 90 60 120 10
0 90 0 80 10
Simulation of reduced fertilization with the calibrated model - N Fluxes•Averages of 25 years starting 25 years after the change in fertilization
•100% - current reported fertilization rate
•N Fluxes in kg/ha/yr
Simulated NO3-N vadose-zone profiles
Where do we want to be from the aquifer management point of view?
Black vertical lines – nitrate drinking water standard (Israel)
ABCABCABc
–211464335359397378421424374
328363368
425279279207233337574112170
202921172129541114
203113
454520
40-6035-5540-50
-Kurtzman et al. 2013
-100
-80
-60
-40
-20
0
De
pth
Be
low
Se
a L
eve
l (m
)
Bias MAE
18.3 20.0 1.6 8.2 14
54.0 51.1 -2.9 4.0 10
52.3 52.9 0.6 14.2 31
64.4 54.1 -10.3 10.3 24
63.4 59.3 -4.0 4.7 9
53.2 60.5 7.3 8.0 13
68.1 65.0 -3.1 10.6 13
67.2 66.5 -0.6 10.8 17
78.8 70.0 -8.8 13.2 10
77.3 75.0 -2.3 10.4 15
91.1 87.0 -4.1 11.5 13
104.1 93.5 -10.6 10.6 1
97.0 100.5 3.5 11.6 14
107.4 115.2 7.8 14.8 11
118.9 130.4 11.5 18.9 14
72.2 72.0 -0.6 11.2 208
25.8 28.50
40
80
120
160
0 40 80 120 160
0
50
100
150
200
250
300
350
0,1 0,6 1 2,8 5 10
-- –
50% 75% 100%
19 21 27 16
57 64 77 60
61 68 82 60
60 67 79 69
59 68 83 70
62 73 96 73
66 77 101 79
71 80 99 78
73 84 107 88
75 86 109 90
84 101 138 106
78 98 139 122
89 103 130 128
86 108 157 129
88 112 164 134
69 81 106 87
11.5 16.5 29.1 26.7
1)
2)
3)
1)
2)
3)
-
–
Dahan et al. 2014
P value (two tail)2*10-5
•
•-
--
•
•
•
•
-
•
•
Thanks
Collaborations
Bridget Scanlon – University of Texas, Austin
Ofer Dahan – Ben Gurion University of the Negev, Israel
Research Students
Roi Shapira – Hebrew University of Jerusalem
Shahar Baram - Ben Gurion University of the Negev
Funding
Chief Scientist of Ministry of Agriculture - Israel
Israel Water Authority
Jackson School of Geosciences, University of Texas, Austin
Farmers who let me sample their soils and vadose zones
Depth (cm) 0 - 15 15 - 30 30 - 45 45 - 60 60 - 75 75 -90O1 0.60 0.03 0.13 0.20 0.08 0.17O3 1.27 0.48 0.24 0.08 0.05 0.03
Table 2. Nitrification potential at different depths, average of3 samples in each depth (mg-N-NO2
- L-1 d-1).
-9
-6
-3
0
5% 15% 25% 35%
De
pth
(m
)
θ (L3/L3)
Water content
Observed Modeled
-9
-6
-3
0
5% 15% 25%
De
pth
(m
)
θ (L3/L3)
Water content
Observed Model
-9
-6
-3
0
0 500 1000 1500 2000
De
pth
(m
)
Concentration (mg/l)
Cl pore water concentration
Observed Model
-9
-6
-3
0
0 50 100 150 200 250
De
pth
(m
)
Concentration (mg/l)
N-NO3 pore water concentration
Observed Model
-9
-6
-3
0
0 500 1000 1500
De
pth
(m
)
Concentration (mg/l)
Cl pore water concentration
Observed Model
-9
-6
-3
0
0 100 200 300
De
pth
(m
)
Concentration (mg/l)
N-NO3 pore water concentration
Observed Model
Model fittings
Orchard 1 Orchard 2
nitrate-NO3
-nitrate-nitrogen–NO3-N
[NO3-] = 4.43[NO3-N]
–
•–
•–
•–-•--•-•-•-
-R
��= ��������+��������� � ���������2��10��
� ��������������������2��10��
(1)
������3−�� = ��� ���������3−�������������2��10��
� ���������2��10��
(2)
����������4���� + ����������4
���� = �������������������4
���� � − ����������4���� − ������4��������4 − ����������������4 − ����������������4
������4 = ����−����4������4
����������3���� = ��
�����������������3���� � − ����������3
���� − ������3��������3 + ����������������4 − ������������������3
ShK
z
hhK
zt
h −
+∂∂
∂∂=
∂∂
)()()(θ
Flow – Richards Eq. with root uptake (van Genuchten-Mualem hydraulic functions)
Transport – ADE Eq. with sink\source terms (linear adsorption for NH4)
Nitrogen transient transport modeling
root zone CNO3
Up
-ta
ken
CN
O3
–
Hydrus-1D
) –
first
arrival
Russo et al., 2013
Recharge flux (mm yr-1)
N-NO3- flux (kg
ha-1 yr-1)r* between Cl- and N-NO3
- profilesO1 (sandy loam) 170 - 230 80 - 130 0.54 – 0.98O2 (sandy loam) 190 - 330 50 - 220 0.44 – 0.67O3 (sandy loam) 90 - 150 70 - 140 0.82 – 0.99O4 (clay) -0.25 – 0.39
Russo et al., 2013
–––
4.79.8
16.5
-N
170 200 400 330 mm/year
1 12 13 20 Kg-N/dunam/year
20 266 144 268 mg/l
1962-2012
-0.00
2.00
4.00
6.00
8.00
19
70
19
72
19
74
19
76
19
78
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
20
06
20
08
20
10
20
12
י לאו
רדהי
ד מ
עו)
רט
מ(
שנה
-100
-80
-60
-40
-20
0
De
pth
Be
low
Se
a L
eve
l (m
)
30
15
10
4.5
K m/dayBias (m) MAE (m)
0.15 0.31 8
0.21 0.4 6
0.29 0.48 20
-0.008 0.25 9
-0.31 0.31 1
-0.31 0.34 18
0.49 0.61 20
-0.56 0.72 27
0.097 0.19 8
0.45 0.45 6
0.003 0.48 123
2
4
6
8
10
2 4 6 8 10
Bias MAE
67.7 20.0 -47.8 47.8 14
63.6 51.1 -12.5 12.5 10
54.6 52.9 -1.7 14.6 31
68.6 54.1 -14.5 14.5 24
73.3 59.3 -14.0 14 9
73.3 60.5 -12.8 15.1 13
75.1 65 -10 12.7 13
63 66.5 3.6 9.3 17
75.9 70 -5.9 11.4 10
75.3 75 -0.3 9.9 15
76.8 87 10.2 11.6 13
70.3 100.5 30.1 30.1 14
89.5 115.2 25.7 26 11
71.6 130.4 58.8 58.8 14
71.3 72.0 0.3 20.1 208
8.1 28.5
0
20
40
60
80
100
120
0 50 100 150
ABCABCABC
-12471105
-81011
-Cl 421192 266 198 179 188 234 232 263
R-211 464 335 359 397 378 424 374
(NO3-
N 96 63 63 47 53 76 25 38
FNO3-N-
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