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Irrigation and agriculture development in Africa: Impact on water quality and ecosystem health in the Ethiopian
highlands
Seifu A Tilahun et al., 2019Bahir Dar Institute of Technology
Bahir Dar University
15 July 2019
Study aim
• Purpose: Evaluate the effect of intensification on water quality: shallow groundwater, streams, lake water bodies & biomass
• Location: Amhara region, Ethiopia
Different intensification levels & topographyRobit (intensified)
~1000 haDangishta (less intensified)~5700 ha
• Agricultural land use: 80% (Robit) and 60% (Dangila)• Slope class: 0-43% (Robit) and 0-28% (Dangila)• Irrigation in Robit > Dangila• endosulfan (α+β) 256ml/ha
90Kg/ha DAP & 46Kg/ha UREA
72 Kg/ha DAP & 43Kg/ha Urea
90 Kg/ha DAP & 46 Kg/ha Urea0.4 m3 Organic fertilizer
Watershed land use pH OM(%) TN(%) Avl.P(mg/l)Robit Bata Farm land 6.0±.18 1.9±.8 0.09±.04 7.7±1.9
Grazing land 5.7±.18 3.8±.82 0.188±.04 4.7±1ForestKhat irrig.
5.6±.365.8±.13
3.5±1.83.2±1
0.17±.090.16±.05
5.4±1.79.2±4.4
Dangishta Farm land 5.1±.18 3.2±.6 0.16±.03 15.8±4Grazing land 4.8±.15 4.5±.5 0.23±.02 9.5±2Forest 5.1±.05 3.6±.5 0.18±.02 11.6±1.7
Mean values ±SD of soil chemical parameters from different land uses
Soil characteristics
• Soil pH values were higher in Robit Bata than Dangishta
• Soil OM , TN and available P (Robit < Dangila)
Typical landscape
Groundwater Level Variation Overtime
Groundwater table variations vary across the two watersheds due to
rainfall distribution and irrigation level
Dangishta
Year
1/201
4
5/201
4
9/201
4
1/201
5
5/201
5
9/201
5
1/201
6
5/201
6
9/201
6
1/201
7
5/201
7
9/201
7
1/201
8
5/201
8
9/201
8
1/201
9
Gro
undw
ater
dep
th(m
)
0
2
4
6
8
10
12
14
16
18
20 0102030405060708090100110120130140150
UpslopeMid-slopeValley bottomRainfall
Robit Bata
Year
1/201
4
5/201
4
9/201
4
1/201
5
5/201
5
9/201
5
1/201
6
5/201
6
9/201
6
1/201
7
5/201
7
9/201
7
1/201
8
5/201
8
9/201
8
1/201
9
0
2
4
6
8
10
12
14
16
18
20
Dai
ly R
ainf
all(m
m)
0102030405060708090100110120130140150
UpslopeMid-slopeValley bottomRainfall
Groundwater Nitrate
• Higher level NO3- was
observed during rainy
season
• Irrigation months (Oct-Dec)
higher NO3- compared to dry
non-cropping period (Jan-
May)
• NO3- signficantly lower in
valley bottom and lowest in
Dangila (P<0.001)
• Rainy season: risk of levels
above EPA drinking
guidelines (10 mg l-1)
Groundwater Phosphorus
• Rainfed cropping season
PO43- was significantly
high in both watersheds (
P=.018)
• Higher concentration
levels in Robit likely
related to relase of PO43-
from soil in the landscape
because of low soil OM
(Robit < Dangila in OM)
P-PO
43- (m
g.L-1
)
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35Mid-slope Mid slope
P-PO
43-(m
g.L-1
)
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35Upslope Upslope
Dec/
16
Jan/
17
Feb/
17
Mar
/17
Ap
r/17
M
ay/1
7
Jun/
17
Jul/1
7
Aug/
17
Sep/
17
Oct
/17
No
v/17
De
c/17
Ja
n/18
Fe
b/18
M
ar/1
8
Apr/1
8
May
/18
Ju
n/18
Ju
l/18
Au
g/18
Se
p/18
O
ct/1
8
Nov/
18
Dec/
18
Jan/
19
P-PO
43-(m
g.L-1
)
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35Valley bottom
Dec/
16
Jan/
17
Feb/
17
Mar
/17
Ap
r/17
M
ay/1
7
Jun/
17
Jul/1
7
Aug/
17
Sep/
17
Oct
/17
No
v/17
De
c/17
Ja
n/18
Fe
b/18
M
ar/1
8
Apr/1
8
May
/18
Ju
n/18
Ju
l/18
Au
g/18
Se
p/18
O
ct/1
8
Nov/
18
Dec/
18
Jan/
19
Valley bottom
Processes control contaminants in GW
• MLR analysis produced statistically
significant models( P<05)
• Cloride and ΔH positively contribute to
PO43- in both watersheds
• Chloride, potassium, and fluctuation in
groundwater table (ΔH) positive contribute
to N-NO3- due to dissimilation and
dinitrification
N-NO3-=.5+ (.2Cl-) + (-.317Cl-/N-NO3
-) + (.156K+) + (.232ΔH)
P-PO43- = .027+ (-.006Cl-) + (.008ΔH)
ΔH=monthly groundwater table level fluctuation (m)
0
2
4
6
8
10
0
2
4
6
8
10N
-NO
3-Streams: Nitrate and Ammonium
Both nitrate and ammonia were dominant in stream during rainy period Only nitrate was high during dry period.
0
2
4
6
8
10
Nov
-16
Dec-
16
Jan-
17
Feb-
17
Mar
-17
Apr-
17
May
-17
Jun-
17
Jul-1
7
Aug-
17
Sep-
17
Oct
-17
Nov
-17
N-N
H 4+
0123456789
10
Nov
-16
Dec-
16
Jan-
17
Feb-
17M
ar-1
7
Apr-
17M
ay-1
7
Jun-
17Ju
l-17
Aug-
17
Sep-
17O
ct-1
7
Nov
-17
Dec-
17
Jan-
18
Robit BataDangishta
00.20.40.60.8
Nov
-16
Jan-
17
Feb-
17
Apr-
17
May
-17
Jul-1
7
Sep-
17
P-PO
43-
0
0.2
0.4
0.6
0.8
Nov
-16
Dec-
16
Feb-
17
Apr-
17
May
-17
Jul-1
7
Sep-
17
Oct
-17
Streams : PhosphorusDangila
Dissolved P was high during rainy period in high-flow in the order of 0.6 mgP-PO4
3-.L-1
Robit Bata
Total Nitrogen: spatial
12
August December March
• Concentration of TN is generally lower than WHO permissible limit• Decrease in load and increase in biological activity drive lower TN
concentration.
Ateka et al. (draft)
Total Phosphorus: spatial
13
August December March
• Largest freshwater body (Lake Tana) started to exceed the 0.2 mg/L of P -minimum level for eutrophication
• Increasing trend in TP from Aug 2016 to Mar 2017 could be with high internal loading
Ateka et al. (draft)
Pesticides in groundwater
• Endosulfa-α concentrations were high in rainy period (August) and irrigation (October) period. The values exceeded MAL- value of EU 0.1 µg L-1
• Endosulfa-β in groundwater was not detected during study period
Endosulfa-β
May-16
Aug.-16
Oct.-16
Mar.-17
0.00
0.05
0.10
0.15
0.20
Sampling period
Con
.(µg.
L-1)
Pesticides in Stream
• Endosulfa-α concentrations were high during rainy period (August) and irrigation (October) period. The values exceeded MAL- value of EU 0.1 µg L-1
• Endosulfa-β and 2,4-D in streamflow were not exceeded EU MAL in study period
Residue levels in onion and khat biomass
B) isomer
Raw-onion
Boiled-onion
Khat0
2
4
6
8
10
12
14
A) isomer
Raw-onion
Boiled-onion
Khat
Res
idue
( g.
kg-1
)
0
2
4
6
8
10
12
14
The EU pesticides regulation for α-and β-endosulfanresidue in bulbs and vegetables recommended a tolerance level of 100 µg.kg-1
Key messages for sustainable development
• ILSSI project provided evidence for critical institutional
changes, guidelines and monitoring mechanisms to regulate
agrochemical use and occurance in water bodies
• Increase smallholder awarness on the impact of agrochemicals
on water quality and human health needed
• Target and promote intensified SSI in suitable areas through
evidence-base on agriculture-water-environment-health system
• Reverse degradation and rehabilitate watersheds (river basins)
for improved SSI
• Link watershed management with irrigation
Thank youThis research was supported through Feed the Future Innovation Labs. We are grateful to Sustainably Intensified Production Systems Impact on Nutrition (SIPSIN-IWMI) project and Bahir Dar Institute of Technology for funding the field research. The Innovation Lab for Small Scale Irrigation provided support for institutional engagement and supporting materials.
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