Model based estimation of nitrogen fertilization recommendations using

agrometeorological data

K. Christian Kersebaum

WMO Expert meeting Geneva 11/2004

Outline

Introduction

Modell description

Examples for applications on farm level

Applications for groundwater protection

Requirements for agrometeorological services

Introduction

• Weather conditions have a strong impact on crop growth and soil

processes and their interactions.

• Nutrient, especially nitrogen management is therefore a challenge

due to the annual variability of nutrient demand by crops on one

side and nitrogen support from the soil on the other.

• The adoption of fertilization considering the supply from the soil and

the demand of crops in their temporal behaviour is important for an

economically effective use of fertilizer and for environmental

protection avoiding leaching of surplus nitrogen to water ressources.

• Measurements of soil and crop nutrient status are only representing

a snapshot with limited temporal validity.

• Process oriented simulation models provide to help in the estimation

of spatial and temporal variability and probable future developments

Methods: Scheme of the nitrogen model HERMES

Kersebaum & Beblik, 2001

predicted N demand covered by subsequent doses

actual weather datasite specific weather scenario

N-uptake

mineral N in root zone

time

net-mineralisation

next development stage for fertilization

N

defi

cie

ncy

1. 2. 3. Fertilizer application

N-deficit occursday of recommendation

Methods: Scheme of model based fertilizer recommendations

Results of 3-year fertilizer trials with different methods (41 field trials from agricultural advisory office Hannover )

Fertilizer efficiency = additional yield per kg N-fertlization compared to Zero plot

Fertilizer efficiency, rel. %yield, rel. %

Winter barley

Winter wheat

Winter rye

Zero model chloroph. model chlorophyll

100% = recommendation based on soil mineral N analysis

Messpunkte Corg [%]

[kg N*ha ]:-1

Grid sampling to get spatial information of soil properties and state variables on field Autobahn/Beckum

Stone content texture organic initial Nmin-content matter (15.9.1999)

Results: Spatial patterns on field Autobahn

Model based nitrogen fertilizer recommendation for winter wheat in 2000 on field Autobahn

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< 3030 - 6060 - 90

90 - 120120 - 150150 - 180

> 180#S sampling points

N- fertilizer recom-mendation [kg N*ha ]:

0 100 m

a) b) c)

-1

Reduction of nitrogen leaching through model based site specific fertilizationcompared to a uniform fertilization of the usual farm level (185 kg N/ha)

Total fertilzer saving for20 ha field: 256 kg N

Variations-koeffizient [%]:

0 50 100 m

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9 - 11

11 - 13

13 - 15

15 - 17

17 - 19

19 - 21

21 - 24

Ertrag [bei 86% TM/ ha]:

90 - 95

30 - 50

50 - 60

60 - 70

70 - 80

80 - 90

0 50 100 m

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Simulated average yields and their variations in a period of 11 years on field Autobahn (average precipitation 800 mm)

Yield[ dt ha-1 ]

Coeff. variation[ %]

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0 50 100 m

max. Duengung [kg N/ ha]:

Stilllegung

< 120

120 - 140

140 - 160

160 - 180

> 180

Restrictions for fertilizer recommendations for winter wheat to matchthe drinking water quality standard of 50 mg nitrate/l in seepage water

Estimation of zones with fertilization restrictions

max fertilization[kg N ha-1]

Set aside

Relief effects on spatial distribution of model inputs

Clay content

Relative irradiation annual average 1998

Corg-content

Topographic wetness index

Digital elevation model

(laser scan 1x1 m grid)

101,8 97,699,5 96,392

94

96

98

100

102

104

TOP BOTTOM

% o

f ra

dia

tion

at

refe

ren

ce s

tati

on measured July 2002 (10 days)

simulated July 2002 (31days)

Reference Weather Station

SRAD-Validation (12d - field)

Observed and simulated yield distribution of spring barley in 1998

Yield spring barley observed

Yield spring barley observed

2000

-1-1-1 -1

Conventional (Soil + crop analysis)HERMES average (135 kg N ha )HERMES average +/- (95 kg N ha )HERMES site specificZero

Conventional (Soil + crop analysis)HERMES average (136 kg N ha )HERMES average +/- (178 kg N ha )HERMES site specificZero

156

192

181

176

187 168

202 150

94 162 141 90 172 172 86 167

158 170 90 165 170 94 158 70

70 165 160 155 172 85 141 158

127 172 139 160 172 172 70 70

1

2

3

4

5

6

7

8

A B C D E F G H

154 174

195 180

194 185

180 168

123 123 125 123 148 149 133 153

146 151 133 150 150 130 149 123

14915015115115315715375

148 148 146 148 149 149 125 80

1

2

3

4

5

6

7

8

A B C D E F G H

2002

0 100 200 Meters

A B C D E F G H

1

2

3

4

5

6

7

8

2001

Experimental design of fertilizer trial 2000 - 2003 on Sportkomplex

Kersebaum et al., 2003

Null Nmin/Sensor HERMES TF HERMES HERMES +30

Düngevarianten

0

20

40

60

80

Ko

rn

ertra

g [

dt T

M/h

a]

Null Nmin/Sensor HERMES TF HERMES HERMES +30

Düngevarianten

0

20

40

60

80

Ko

rn

ertra

g [

dt T

M/h

a]

Fertilizer:0 179 139 136 178 kg N/hayields 2000

yields 2002Fertilizer:0 177 135 136 95 kg N/ha

Comparison of different fertilizer recommendations on Sportkomplex

80

60

40

20

80

60

40

20

Zero Nmin+Sensor HERMES SS HERMES HERMES -30%

Zero Nmin+Sensor HERMES SS HEMES HERMES +30%

Requirements for agrometeorological services

The model requires weather data on a daily basis:• Precipitation• Air temperature (2m)• Humidity (average or 2 p.m. depending on evaporation formula)• Global radiation or sunshine duration• Optional: wind speed

Upto now the model works mostly in conjunction with automatic weather stations because accessability of upto date data with a high spatial resolution is limited.

Longterm site specific data sets are desirable to create specific weather scenarios for predictive simulations.

3-5 day forecast can be used to adopt the fertilization schedule to site specific requirements (e.g to avoid nitrate leaching).

Thank you

for your attention