Modeling wheat yield gaps in European Russia

using the SWAT model

SWAT conference 2013 | 17 – 19 July

Schierhorn, Florian Faramarzi, Monireh Prishchepov, Alexander V. Koch, Friedrich Müller, Daniel

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Rising demand for agricultural products

Population o 2.5 billion more by 2070

o Growing affluence

Diets o Meat

o Processed food

Bioenergy o Traditional (80%)

o Modern (20%)

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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?

• 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

Objectives

#*

#* Kazakhstan

Kirov

Rostov

Saratov

Perm

Volgograd

Nizhny

Bashkortostan

Vologda

Tatarstan

Penza

Samara

KrasnodarStravropol

Tula

Moscow

Ryazan

Voronezh

Kursk

Oryol

Udmurtia

TambovBryansk

Ulyanovsk

MariEl

Lipetsk

Belgorod

Mordovia

Chuvash

70°E

60°E

60°E

50°E

50°E

40°E

40°E30°E

50°N

50°N

Ukraine

European Russia

Spring wheat

Subbasin

Provinces (oblast)

Study area

546 subbasins -> 30 selected for individual calibration

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 Parameter MIN MAX

v__ESCO.hru 0.01 1 v__USLE_K(1).sol 0 0.65

v__EPCO.hru 0.01 1 v__USLE_K(2).sol 0 0.65

v__OV_N.hru 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

v__ANION_EXCL.sol 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

v__CN2.mgt 65 90 r__FRT_KG{x,x}.mgt -0.3 0.3

Crop related parameters were excluded for calibration!

Parameter 129 139 201 220 221 235 251 279 300 308 379 425

FRT_KG{12,3}.mgt 8 9 14 10 8 7 5 11 18 1 5 1

SOL_CBN(2).sol 7 1 8 26 1 8 6 12 1 6 12 9

FRT_KG{9,3}.mgt 20 2 3 1 15 15 19 1 20 2 1 3

FRT_KG{6,3}.mgt 9 7 48 4 5 11 1 3 11 4 6 15

FRT_KG{11,3}.mgt 5 15 21 9 6 9 2 8 27 3 13 11

FRT_KG{14,3}.mgt 10 12 15 12 2 1 10 2 23 12 11 20

FRT_KG{8,3}.mgt 29 3 1 6 16 14 3 5 31 16 2 4

ESCO.hru 6 13 4 3 14 4 16 41 2 23 3 2

FRT_KG{10,3}.mgt 3 10 6 8 4 34 8 7 10 13 25 5

CN2.mgt 48 5 2 2 13 6 14 10 5 14 9 8

FRT_KG{7,3}.mgt 2 4 5 5 19 12 4 4 24 43 8 6

FRT_KG{13,3}.mgt 11 16 12 11 7 3 15 6 35 5 10 16

SOL_CBN(1).sol 12 6 11 28 12 10 12 13 3 9 23 13

FRT_KG{15,3}.mgt 1 17 23 7 3 18 7 14 47 8 7 17

FRT_KG{4,3}.mgt 4 11 9 14 21 25 9 37 28 10 4 12

ANION_EXCL.sol 26 8 10 19 10 5 13 25 8 15 29 18

EPCO.hru 35 20 7 13 11 2 18 15 25 7 17 19

FRT_KG{5,3}.mgt 44 23 13 16 9 21 11 9 9 36 14 7

CANMX.hru 15 24 16 15 17 13 29 46 19 17 16 44

SOL_BD(1).sol 16 14 43 35 18 40 17 28 6 21 21 36

SOL_BD(2).sol 14 18 32 18 47 16 47 23 4 32 30 14

SOL_K(1).sol 42 34 26 41 29 28 23 27 7 11 18 10

GWSOLP.gw 23 32 28 17 27 23 24 32 12 22 19 43

FRT_KG{3,3}.mgt 25 19 27 23 37 24 31 18 30 44 24 23

GWQMN.gw 18 29 24 45 30 20 38 30 16 18 33 34

SOL_K(2).sol 39 33 22 30 31 42 26 16 41 19 40 27

LAT_SED.hru 37 30 33 36 28 37 20 20 17 47 42 22

SHALLST_N.gw 13 40 40 20 25 19 22 39 43 46 41 24

FRT_KG{1,3}.mgt 28 31 25 47 24 38 39 42 26 20 31 26

SOL_EC(1).sol 24 22 38 43 40 26 27 22 36 48 26 25

DEEPST.gw 40 25 44 37 20 32 42 19 32 45 15 30

GWHT.gw 30 37 29 24 33 30 44 17 46 29 45 21

LAT_TTIME.hru 22 36 46 32 46 17 46 38 14 26 32 46

FRT_KG{2,3}.mgt 21 46 31 27 42 33 25 24 48 24 37 45

SOL_ALB(1).sol 19 43 18 40 43 36 40 40 15 38 43 29

SOL_EC(2).sol 36 26 30 46 34 22 35 21 33 37 47 37

GW_REVAP.gw 46 27 34 31 41 46 21 26 40 27 38 31

HLIFE_NGW.gw 45 35 20 21 45 31 32 45 38 30 35 38

OV_N.hru 41 48 39 22 26 48 45 29 13 35 44 28

GW_SPYLD.gw 38 42 36 33 22 47 41 35 21 40 28 40

SOL_ALB(2).sol 17 41 42 39 35 29 43 47 45 28 22 35

USLE_K(1).sol 47 28 47 25 38 27 30 43 34 34 36 41

RCHRG_DP.gw 31 47 41 42 23 35 33 48 29 31 34 39

ALPHA_BF.gw 43 44 35 38 39 39 34 31 39 42 20 33

USLE_K(2).sol 27 21 37 29 44 45 48 36 44 39 27 42

SHALLST.gw 32 38 19 34 48 41 37 33 42 33 39 48

SOL_CRK.sol 34 39 45 44 36 43 28 34 22 25 48 47

GW_DELAY.gw 33 45 17 48 32 44 36 44 37 41 46 32

Param

eter se

nsitivity

+

-

Calibration and Validation results

Calibration Validation

0

500

1000

1500

2000

2500

3000

3500

0

0.5

1

1.5

2

1 10 19 28 37 46 55 64 73 82 91 100 109

10 kg NNo irrigation

PHU: 2009 YLD = 0.7 t/ha

0

1000

2000

3000

4000

5000

6000

7000

8000

0

0.5

1

1.5

2

2.5

3

3.5

4

1 11 21 31 41 51 61 71 81 91 101 111

PHU: 2009 YLD = 1.2 t/ha

300 kg NNo irrigation

0

2000

4000

6000

8000

10000

12000

14000

16000

0

0.5

1

1.5

2

2.5

3

3.5

4

1 11 21 31 41 51 61 71 81 91 101 111

PHU: 2009 YLD = 4.7 t/ha

300 kg NIrrigation

0

2000

4000

6000

8000

10000

12000

0

0.5

1

1.5

2

2.5

3

3.5

4

1 11 21 31 41 51 61 71

300 kg NIrrigation

PHU: 1409 YLD = 3.4 t/ha

Rainfed Rainfed

02468

02468

02468

02468

02468

1995 2000 2005 1995 2000 2005

1995 2000 2005 1995 2000 2005 1995 2000 2005 1995 2000 2005

Bashkortostan Belgorod Bryansk Chuvash Kirov Krasnodar

Kursk Lipetsk MariEl Mordovia Moscow Nizhny

Oryol Penza Perm Rostov Ryazan Samara

Saratov Stravropol Tambov Tatarstan Tula Udmurtia

Ulyanovsk Volgograd Vologda Voronezh

Yield potential for sufficient N & WATER supply

Yield potential for sufficient N supply

Reported

Wh

eat

yiel

d (

t/h

a)

0

1

2

3

4

5

6

7

Wh

eat

yie

ld (

t/h

a)

YGN

YGN&Water

Yield gap for sufficient N & Water supply

#*

#*

Kirov

Rostov

Saratov

Perm

Volgograd

Nizhny

Bashkortostan

Vologda

Tatarstan

Penza

Samara

KrasnodarStravropol

Tula

Moscow

Ryazan

Voronezh

Kursk

Oryol

Udmurtia

TambovBryansk

Ulyanovsk

MariEl

Lipetsk

Belgorod

Mordovia

Chuvash

70°E

60°E

60°E

50°E

50°E

40°E

40°E30°E

50°N

50°N

Ukraine

European Russia

t/ha

1.10 - 1.18

1.19 - 1.35

1.36 - 1.48

1.49 - 1.87

1.88 - 2.16

2.17 - 2.43

2.44 - 2.53

2.54 - 2.94

2.95 - 3.15

3.16 - 4.31

Average wheat yieldsreported 2001-2006

Spring wheat

Average wheat yields, 2001-2006

#*

#*

Kirov

Rostov

Saratov

Perm

Volgograd

Nizhny

Bashkortostan

Vologda

Tatarstan

Penza

Samara

KrasnodarStravropol

Tula

Moscow

Ryazan

Voronezh

Kursk

Oryol

Udmurtia

TambovBryansk

Ulyanovsk

MariEl

Lipetsk

Belgorod

Mordovia

Chuvash

70°E

60°E

60°E

50°E

50°E

40°E

40°E30°E

50°N

50°N

Ukraine

European Russia

t/ha

1.16 - 1.43

1.44 - 1.75

1.76 - 1.80

1.81 - 1.97

1.98 - 2.17

2.18 - 2.31

2.32 - 2.37

2.38 - 2.52

2.53 - 2.82

2.83 - 3.03

Average yield gap for sufficient N supply, 2001-2006

Spring wheat

Yield gap for sufficent N supply

Yield gap for sufficent N supply & water supply

#*

#*

Kirov

Rostov

Saratov

Perm

Volgograd

Nizhny

Bashkortostan

Vologda

Tatarstan

Penza

Samara

KrasnodarStravropol

Tula

Moscow

Ryazan

Voronezh

Kursk

Oryol

Udmurtia

TambovBryansk

Ulyanovsk

MariEl

Lipetsk

Belgorod

Mordovia

Chuvash

70°E

60°E

60°E

50°E

50°E

40°E

40°E30°E

50°N

50°N

Ukraine

European Russia

t/ha

1.79 - 2.57

2.58 - 2.74

2.75 - 2.89

2.90 - 3.11

3.12 - 3.20

3.21 - 3.38

3.39 - 3.44

3.45 - 3.72

3.73 - 3.80

3.81 - 4.56

Average yield gap for sufficient N & Water supply, 2001-2006

Spring wheat

Yield gap for entire European Russia: 2.1 t/ha -> under sufficient N supply 3.2 t/ha -> under sufficient N & Water supply

34567

34567

34567

34567

1995 2000 2005

1995 2000 2005 1995 2000 2005 1995 2000 2005

Bashkortostan Chuvash Kirov MariEl

Mordovia Nizhny Penza Perm

Samara Saratov Tatarstan Udmurtia

Ulyanovsk Volgograd Vologda

95PPU of simulated yield, average growing period

95PPU of simulated yield, short growing period

95PPU of simulated yield, long growing period

Spri

ng

wh

eat

yiel

d (

t/h

a)

Yield sensitivity to growing period

02468

02468

02468

1995 2000 2005

1995 2000 2005 1995 2000 2005

Mordovia Nizhny Penza

Samara Saratov Tatarstan

Ulyanovsk Volgograd

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

Spri

ng

wh

eat

yiel

d (

t/h

a)

Yield sensitivity to crop parameter

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

(schierhorn@iamo.de)

www.iamo.de

Foto: J. Stahl

-.5 0 .5 1 1.5 2 -.5 0 .5 1 1.5 2

-.5 0 .5 1 1.5 2 -.5 0 .5 1 1.5 2

Validation

Calibration

Validation

Calibration

Validation

Calibration

Validation

Calibration

Bashkortostan Chuvash Kirov MariEl

Mordovia Nizhny Penza Perm

Samara Saratov Tatarstan Udmurtia

Volgograd Vologda P factor

R factor

R2

Nash Sutclif

Calibration and Validation results