Presentation

Modeling wheat yield gaps in European Russia
using the SWAT model
Schierhorn, Florian
Faramarzi, Monireh
Prishchepov, Alexander V.
Koch, Friedrich
Müller, Daniel
SWAT conference 2013 | 17 – 19 July
Rising demand for agricultural products
 Population
o 2.5 billion more by 2070
o Growing affluence
 Diets
guardian.co.uk
o Meat
o Processed food
 Bioenergy
guardian.co.uk
o Traditional (80%)
o Modern (20%)
guardian.co.uk
2
Two options to increase
agricultural production
1. Expansion of agricultural land
o Most fertile land already used
o Further expansion associated with
high environmental tradeoffs
2. Intensification on existing agricultural land
o More inputs per unit of land
o Better technology
3
Low yields due to yield gap?
Objectives
• Simulation of post-Soviet wheat yields using
SWAT [->capturing of inter-anual yield
variations]
• Simulation of wheat yield potentials
• Sensitivity analysis of growing period (& PHU)
and crop parameters on yield
Study area
30°E
40°E
50°E
60°E
70°E
Vologda
Perm
Kirov
Udmurtia
European Russia
MariEl
Nizhny
Chuvash
#
*
Moscow
Ryazan
Tatarstan
Bashkortostan
Ulyanovsk
Mordovia
Samara
Tula
50°N
Penza
Bryansk
Oryol
Lipetsk
Tambov
Saratov
Kursk
#
*
Belgorod
Voronezh
50°N
Volgograd
Ukraine
546 subbasins
-> 30
Kazakhstan
selected for individual calibration
Rostov
Spring wheat
Subbasin
Krasnodar
40°E
Stravropol
Provinces (oblast)
50°E
60°E
Model setup
 Calibration: 1996-2006 / 3yrs warm-up
 Validation: 1991-1994 / 3yrs warm-up
 Study area size: 4 million km² square kilometers
 Hargreaves method for ET-estimation
 Dominant soil and land use property
 Winter wheat & spring wheat dominant
 Assignment of ONE representative subbasin per
province (oblast)
-> 30 regions to be calibrated indi
Data
• Landuse: Binary cropland map (100 ha)
• Soil: Harmonized World Soil Database (10 km)
• Climate: Daily weather data from Schuol and
Abbaspour (2007)
• Wheat yield: ROSSTAT 2012 (provinces)
• Management:
• Growing period – USDA
• N fertilizer – ROSSTAT 2012
Calibration, Validation, and scenarios
analysis
• Wheat yields were calibrated for each
province
• Simulated wheat yields were compared with
anual wheat yield data reported at provincial
level
• After satisfactory calibration/validation, two
scenarios: A) sufficient N fertilizer, B) sufficient
N fertilizer + Water were constructed [to
access yield potentials]
Initial parameter ranges for calibration
Parameter
MIN
MAX
v__ESCO.hru
0.01
1
v__EPCO.hru
0.01
v__OV_N.hru
MIN
MAX
v__USLE_K(1).sol
0
0.65
1
v__USLE_K(2).sol
0
0.65
0.01
0.8
v__SOL_EC(1).sol
0
100
v__LAT_TTIME.hru
0
180
v__SOL_EC(2).sol
0
100
v__LAT_SED.hru
0
5000
v__SHALLST.gw
0
1000
v__CANMX.hru
0
1
v__DEEPST.gw
0
1290
v__SOL_BD(1).sol
1.1
1.7
v__GW_DELAY.gw
0
500
v__SOL_BD(2).sol
1.1
1.7
v__ALPHA_BF.gw
0
1
v__SOL_CBN(1).sol
1
3
v__GWQMN.gw
0
5000
v__SOL_CBN(2).sol
0
2
v__GW_REVAP.gw
0.02
0.2
v__SOL_ALB(1).sol
0
0.25
v__RCHRG_DP.gw
0
1.1
v__SOL_ALB(2).sol
0
0.25
v__GWHT.gw
0
25
0.2
0.8
v__GW_SPYLD.gw
0
0.4
v__SOL_K(1).sol
0
2000
v__SHALLST_N.gw
0
10
v__SOL_K(2).sol
0
2000
v__GWSOLP.gw
0
1000
v__SOL_CRK.sol
0
1
v__HLIFE_NGW.gw
0
365
65
90
r__FRT_KG{x,x}.mgt
-0.3
0.3
v__ANION_EXCL.sol
v__CN2.mgt
Parameter
Crop related parameters were excluded for calibration!
139
201
220
221
235
251
279
300
308
379
425
9
1
2
7
15
12
3
13
10
5
4
16
6
17
11
8
20
23
24
14
18
34
32
19
29
33
30
40
31
22
25
37
36
46
43
26
27
35
48
42
41
28
47
44
21
38
39
45
14
8
3
48
21
15
1
4
6
2
5
12
11
23
9
10
7
13
16
43
32
26
28
27
24
22
33
40
25
38
44
29
46
31
18
30
34
20
39
36
42
47
41
35
37
19
45
17
10
26
1
4
9
12
6
3
8
2
5
11
28
7
14
19
13
16
15
35
18
41
17
23
45
30
36
20
47
43
37
24
32
27
40
46
31
21
22
33
39
25
42
38
29
34
44
48
8
1
15
5
6
2
16
14
4
13
19
7
12
3
21
10
11
9
17
18
47
29
27
37
30
31
28
25
24
40
20
33
46
42
43
34
41
45
26
22
35
38
23
39
44
48
36
32
7
8
15
11
9
1
14
4
34
6
12
3
10
18
25
5
2
21
13
40
16
28
23
24
20
42
37
19
38
26
32
30
17
33
36
22
46
31
48
47
29
27
35
39
45
41
43
44
5
6
19
1
2
10
3
16
8
14
4
15
12
7
9
13
18
11
29
17
47
23
24
31
38
26
20
22
39
27
42
44
46
25
40
35
21
32
45
41
43
30
33
34
48
37
28
36
11
12
1
3
8
2
5
41
7
10
4
6
13
14
37
25
15
9
46
28
23
27
32
18
30
16
20
39
42
22
19
17
38
24
40
21
26
45
29
35
47
43
48
31
36
33
34
44
18
1
20
11
27
23
31
2
10
5
24
35
3
47
28
8
25
9
19
6
4
7
12
30
16
41
17
43
26
36
32
46
14
48
15
33
40
38
13
21
45
34
29
39
44
42
22
37
1
6
2
4
3
12
16
23
13
14
43
5
9
8
10
15
7
36
17
21
32
11
22
44
18
19
47
46
20
48
45
29
26
24
38
37
27
30
35
40
28
34
31
42
39
33
25
41
5
12
1
6
13
11
2
3
25
9
8
10
23
7
4
29
17
14
16
21
30
18
19
24
33
40
42
41
31
26
15
45
32
37
43
47
38
35
44
28
22
36
34
20
27
39
48
46
1
9
3
15
11
20
4
2
5
8
6
16
13
17
12
18
19
7
44
36
14
10
43
23
34
27
22
24
26
25
30
21
46
45
29
37
31
38
28
40
35
41
39
33
42
48
47
32
+
Parameter sensitivity
Parameter 129
FRT_KG{12,3}.mgt 8
SOL_CBN(2).sol 7
FRT_KG{9,3}.mgt 20
FRT_KG{6,3}.mgt 9
FRT_KG{11,3}.mgt 5
FRT_KG{14,3}.mgt 10
FRT_KG{8,3}.mgt 29
ESCO.hru 6
FRT_KG{10,3}.mgt 3
CN2.mgt 48
FRT_KG{7,3}.mgt 2
FRT_KG{13,3}.mgt 11
SOL_CBN(1).sol 12
FRT_KG{15,3}.mgt 1
FRT_KG{4,3}.mgt 4
ANION_EXCL.sol 26
EPCO.hru 35
FRT_KG{5,3}.mgt 44
CANMX.hru 15
SOL_BD(1).sol 16
SOL_BD(2).sol 14
SOL_K(1).sol 42
GWSOLP.gw 23
FRT_KG{3,3}.mgt 25
GWQMN.gw 18
SOL_K(2).sol 39
LAT_SED.hru 37
SHALLST_N.gw 13
FRT_KG{1,3}.mgt 28
SOL_EC(1).sol 24
DEEPST.gw 40
GWHT.gw 30
LAT_TTIME.hru 22
FRT_KG{2,3}.mgt 21
SOL_ALB(1).sol 19
SOL_EC(2).sol 36
GW_REVAP.gw 46
HLIFE_NGW.gw 45
OV_N.hru 41
GW_SPYLD.gw 38
SOL_ALB(2).sol 17
USLE_K(1).sol 47
RCHRG_DP.gw 31
ALPHA_BF.gw 43
USLE_K(2).sol 27
SHALLST.gw 32
SOL_CRK.sol 34
GW_DELAY.gw 33
-
Calibration and Validation results
Calibration
Validation
2
10 kg N
No
irrigation
Rainfed
1.5
3500
4
3000
3.5
2500
3
2000
1
1500
1000
0.5
500
0
0
1
10
19
28
37
46
55
PHU: 2009
64
73
82
91 100 109
2.5
2.5
1.5
3000
1
2000
0.5
1000
0
0
1
16000
4
14000
3.5
12000
3
10000
2.5
2
1.5
6000
1.5
1
4000
1
0.5
2000
0.5
0
0
21
31
PHU: 2009
41
51
61
71
81
91
YLD = 4.7 t/ha
5000
4000
8000
11
6000
2
2
1
7000
11
21
31
41
51
61
PHU: 2009
300 kg N
Irrigation
3
300 kg N
No
irrigation
Rainfed
YLD = 0.7 t/ha
4
3.5
8000
101 111
71
81
91
101
111
YLD = 1.2 t/ha
12000
300 kg N
Irrigation
10000
8000
6000
4000
2000
0
0
1
11
21
PHU: 1409
31
41
51
61
71
YLD = 3.4 t/ha
Yield gap for sufficient N & Water supply
Bashkortostan
Belgorod
Bryansk
Chuvash
Kirov
Krasnodar
Kursk
Lipetsk
MariEl
Mordovia
Moscow
Nizhny
Oryol
Penza
Perm
Rostov
Ryazan
Samara
Saratov
Stravropol
Tambov
Tatarstan
Tula
Udmurtia
8
6
4
2
0
8
6
4
2
0
8
6
4
2
0
8
6
4
2
0
1995
Ulyanovsk
Volgograd
Vologda
8
6
4
2
0
Voronezh
2000
2005
1995
2000
2005
7
1995
2000
2005
1995
2000
2005
1995
2000
Wheat yield (t/ha)
6
2005
5
1995
2000
2005
4
3
Yield potential for sufficient N & WATER supply
2
Yield potential for sufficient N supply
1
Reported
0
YGN&Water
YGN
Average wheat yields, 2001-2006
30°E
40°E
50°E
60°E
70°E
Vologda
Spring wheat
Perm
Kirov
Udmurtia
European Russia
MariEl
Nizhny
Chuvash
#
*
Moscow
Ryazan
Tatarstan
Bashkortostan
Ulyanovsk
Mordovia
Samara
Tula
50°N
Penza
Bryansk
Oryol
Lipetsk
Tambov
Saratov
Kursk
#
*
Belgorod
Average wheat yields
reported 2001-2006
Voronezh
50°N
Volgograd
t/ha
Ukraine
Rostov
Krasnodar
40°E
2.17 - 2.43
1.10 - 1.18
2.44 - 2.53
1.19 - 1.35
2.54 - 2.94
1.36 - 1.48
2.95 - 3.15
1.49 - 1.87
3.16 - 4.31
1.88 - 2.16
Stravropol
50°E
60°E
Yield gap for sufficent N supply
30°E
40°E
50°E
60°E
70°E
Vologda
Spring wheat
Perm
Kirov
Udmurtia
European Russia
MariEl
Nizhny
Chuvash
#
*
Moscow
Ryazan
Tatarstan
Bashkortostan
Ulyanovsk
Mordovia
Samara
Tula
50°N
Penza
Bryansk
Oryol
Lipetsk
Tambov
Saratov
Kursk
#
*
Belgorod
Average yield gap for sufficient
N supply, 2001-2006
Voronezh
50°N
Volgograd
t/ha
Ukraine
Rostov
Krasnodar
40°E
2.18 - 2.31
1.16 - 1.43
2.32 - 2.37
1.44 - 1.75
2.38 - 2.52
1.76 - 1.80
2.53 - 2.82
1.81 - 1.97
2.83 - 3.03
1.98 - 2.17
Stravropol
50°E
60°E
Yield gap for sufficent N supply & water supply
30°E
40°E
50°E
60°E
70°E
Vologda
Spring wheat
Perm
Kirov
Udmurtia
European Russia
MariEl
Nizhny
Chuvash
#
*
Moscow
Ryazan
Tatarstan
Bashkortostan
Ulyanovsk
Mordovia
Samara
Tula
50°N
Penza
Bryansk
Oryol
Lipetsk
Tambov
Saratov
Kursk
#
*
Belgorod
Average yield gap for sufficient
N & Water supply, 2001-2006
Voronezh
50°N
Volgograd
t/ha
Ukraine
Rostov
Krasnodar
40°E
3.21 - 3.38
1.79 - 2.57
3.39 - 3.44
2.58 - 2.74
3.45 - 3.72
2.75 - 2.89
3.73 - 3.80
2.90 - 3.11
3.81 - 4.56
3.12 - 3.20
Stravropol
50°E
60°E
Yield gap for entire European Russia:
2.1 t/ha -> under sufficient N supply
3.2 t/ha -> under sufficient N & Water supply
Yield sensitivity to growing period
Bashkortostan
Chuvash
Kirov
MariEl
Mordovia
Nizhny
Penza
Perm
Samara
Saratov
Tatarstan
Udmurtia
7
6
5
4
3
7
6
5
4
3
7
6
5
4
3
1995
Vologda
Volgograd
Ulyanovsk
7
6
5
4
3
1995
2000
2005
1995
2000
2005
1995
2000
2005
95PPU of simulated yield, average growing period
95PPU of simulated yield, short growing period
95PPU of simulated yield, long growing period
2000
2005
Yield sensitivity to crop parameter
Mordovia
Nizhny
Penza
Samara
Saratov
Tatarstan
8
6
4
2
0
8
6
4
2
0
1995
Ulyanovsk
2000
2005
Volgograd
8
6
4
2
0
1995
2000
2005
1995
2000
2005
95PPU of simulated yield for sufficient N & Water supply, Variation of crop parameters
95PPU of simulated yield for sufficient N & Water supply, SWAT default crop parameters
Reported
Conclusion
• Russia has large potential to increase crop yields
• SWAT crop growth module reproduces accurate
yields despite the large scale & data scarcity
• Yield gaps are heterogeneously distributed
• Information on crop characteristics (PHU in
particular) are essential for accurate yield gap
estimations
20
Thank you
very much.
Contact:
Florian Schierhorn
([email protected])
www.iamo.de
Foto: J. Stahl
Calibration and Validation results
Bashkortostan
Chuvash
Kirov
MariEl
Mordovia
Nizhny
Penza
Perm
Samara
Saratov
Tatarstan
Udmurtia
Calibration
Validation
Calibration
Validation
Calibration
Validation
-.5
Volgograd
Vologda
.5
1
1.5
2
P factor
R factor
Calibration
Validation
-.5
0
R2
0
.5
1
1.5
2
-.5
0
.5
1
1.5
2
Nash Sutclif
-.5
0
.5
1
1.5
2