KIT – University of the State of Baden-Wuerttemberg and
IMK-IFU Garmisch-Partenkirchen Department of biogeochemical processes
LandscapeDNDC
A process based model for biogeochemical simulations from site to the regional scale
E. Haas, R. Kiese, S. Klatt, D. Kraus, S. Molina,
R. Grote, Y. Kim, Klaus Butterbach-Bahl
LandscapeDNDC – History/ background Site validation
Regional applications
Uncertainty quantification (parameter vs. input uncertainty) Scenario applications
Outlook – coupled biogeochemical/ hydrological simulations
Overview
Institute for Meteorology and Climate Research,(IMK-IFU)
3 29.09.2014 TERENO International Conference 2014
LandscapeDNDC history/ background
arable land grassland forest
DNDC model
University of New Hampshire
PnET-N-DNDC
Forest-DNDC model
IMK-IFU Garmisch- Partenkirchen
Landscape-DNDC +regionalisation
UQ/ UA
LandscapeDNDC – Model overview
Forest
Arable
Grass
Haas et al.,2013
Institute for Meteorology and Climate Research,(IMK-IFU)
5 29.09.2014 TERENO International Conference 2014
0 10 20 30 40
soil temperature (°T)
daily precipitation (mm)
precipitation (mm) ST-Measured ST-LandscapeDNDC
0 10 20 30 40 50 60
soil water content at 10 cm depth (%)
SWC-Measured SWC-LandscapeDNDC
0 5 10 15 20 25 30
WIWH WIWH
plant biomass (t DW ha-1)
AGB-Measured AGB-LandscapeDNDC
BEET
0 50 100 150 200
inorganic N at 10 cm depth (kg N ha-1)
NH4-Measured NH4-LandscapeDNDC NO3-Measured NO3-LandscapeDNDC
2006 2007 2008 2009
-80 -40 0 40 80 120 160
nitroux oxide (ug N m-2 d-1)
years Manual-Measured Auto-Measured N2O-LandscapeDNDC
µ µ µ
0 10 20 30 40 50
soil temperature (°T)
daily precipitation (mm)
precipitation (mm) ST-Measured ST-LandscapeDNDC
0 10 20 30 40 50 60 70
soil water content at 10 cm depth (%)
SWC-Measured SWC-LandscapeDNDC
0 5 10 15 20
plant biomass (t DW ha-1)
AGB-Measured AGB-LandscapeDNDC
PERG
0 50 100 150 200
inorganic N from 2-6 cm depth (kg N ha-1 )
NH4-Measured NH4-LandscapeDNDC NO3-Measured NO3-LandscapeDNDC
2002 2003 2004 2005 2006 2007 2008
0 200 400 600 800 1000 1200
nitroux oxide (ug N m-2 d-1)
years
N2O-Measured N2O-LandscapeDNDC
µ µ µ
Arable: Gebesee (D) Grassland: Oensingen (CH)
Molina et al., in preparation
LandscapeDNDC site validation
rice rice
maize rice
LandscapeDNDC site validation
Kraus et al.,2014
Institute for Meteorology and Climate Research,(IMK-IFU)
7 29.09.2014 TERENO International Conference 2014
LandscapeDNDC site validation
Regional N 2 O emission inventory simulations
4400 polygons, BUEK200 soil database, Climate input on 1 x 1 km, 3 crop rotation: w-barley, w-wheat, maize; N-Fertilizer: 111 000 t / yr
Data source: LfULG, Environmental Service, State of Saxony, Germany
IPCC (Tier 1): 1 110 t N 2 O-N / yr NIR (Tier 2): 3 000 t N 2 O-N / yr LandscapeDNDC (Tier 3): 2 693 t N 2 O-N / yr
GIS database
LandscapeDNDC – UNFCCC GHG reporting
Institute for Meteorology and Climate Research,(IMK-IFU)
9 29.09.2014 TERENO International Conference 2014
150 kg N
N2O emissions from rows [ug N m-2 h-1]
0 100 200 300 400
250 kg N
0 100 200 300 400
350 kg N
Month
Dec Apr Aug Dec
0 100 200 300 400
50 kg N
0 100 200 300 400
Simulated Measured
50 kg N
0 200 400 600 800
150 kg N
Nitrate concentrations at 15 cm depth of rows [mg N l-1 d-1]
0 200 400 600 800
250 kg N
0 200 400 600 800
350 kg N
Month
Dec Apr Aug Dec
0 200 400 600 800
Simulated Measured
LandscapeDNDC – Mitigating N losses
Haean catchment S-Korea
Kim et al., in preparation
Kim et al., 2014
LandscapeDNDC – Mitigating N losses
Haean catchment S-Korea
Kim et al., in preparation
50%
50%
Institute for Meteorology and Climate Research,(IMK-IFU)
11 29.09.2014 TERENO International Conference 2014
Sources of Uncertainty in N 2 O & NO 3 inventory simulations
Parameter Uncertainty
Bayesian Calibration technique used to obtain parameter probability distribution
Input Uncertainty of soil properties (LH samp.) bulk density (approx. 20%)
soil carbon content (approx. 100%) pH values (approx. 0.25)
hydraulic properties (approx. 20%)
Nearly 1000 regional inventory simulations
LandscapeDNDC – Uncertainties (regional scale)
LandscapeDNDC – Parameter Uncertainty
(regional scale)
Klatt et al., accepted
Institute for Meteorology and Climate Research,(IMK-IFU)
13 29.09.2014 TERENO International Conference 2014
Parameter induced Input Data induced
Klatt et al., accepted
N 2 O Emission
LandscapeDNDC – Parameter/ Input Uncertainty
(regional scale)
NO 3 Leaching
0 1 2
kg N ha yr-1
0 10 20 30 40 50
0 1 2
kg N ha-1 yr-1
0 10 20 30 40 50
Nitrate seepage flux during a ~120 yr rotation time (Climate baseline 1990 to 2010)
Clearcut (high N loss)
Understorey reinitiation (efficient N uptake, increasing N retention)
Old growth (increasing N loss with forest age)
Nitrate-N conc. [mg/l]
Forest thinnings
Dirnböck et al. in preparation
LandscapeDNDC scenario application
Institute for Meteorology and Climate Research,(IMK-IFU)
15 29.09.2014 TERENO International Conference 2014
1. Increased peak flows of nitrate
2. Summer drought causes retarded tree regeneration
Less N-uptake and more water percolation in winter causes higher seepage nitrate concentrations during understorey reinitiation
3. Mature forests have a higher growth rate under climate change and therefore retain nitrate more efficiently
Clearcut understorey reinitiation old growth
LandscapeDNDC scenario application
ECHAM5-A2 2090 Baseline 1990 to 2010
1
2 3
Dirnböck et al. in preparation
Coupled biogeochemical-hydrological model
LandscapeDNDC Unit
CMF Unit
meteorology phenology
soil hydrology N turnover
NO3conc
regional water fluxes Biogeochemistry Hyrdology
NO3leaching
Institute for Meteorology and Climate Research,(IMK-IFU)
17 29.09.2014 TERENO International Conference 2014
ralf.kiese@kit.edu
Biomass productivity gradient Indirect N
2O emissions
Coupled LandscapeDNDC – CMF simulation
Extensive g rassland
Arable land Fertiliz ation:
300 kg N/ha
Lateral nitrate transport
Total biomass production
Accumulated N
2O emissions
Legend
Soil NO
3concentrations high
low Soil nitra te conce
ntrations
LandscapeDNDC coupled to reg. hydrological model
Thank you
for your attention!
Ralf.kiese@kit.edu
Institute for Meteorology and Climate Research,(IMK-IFU)
19 29.09.2014 TERENO International Conference 2014
Parameter Uncertainty
Sampling of 400 joint parameter distributions out of 400 0000
400 regional inventories
Input Uncertainty
Latin hypercube sampling for bulk density, soil carbon content, pH values, hydraulic properties
525 regional inventories
Nearly 1000 regional inventory simulations
LandscapeDNDC – Uncertainties (regional scale)
LandscapeDNDC – Model overview
Biogeochemical processes Vertical layering
Institute for Meteorology and Climate Research,(IMK-IFU)
21 29.09.2014 TERENO International Conference 2014
Parameter induced Input Data induced
Klatt et al., accepted
N 2 O
LandscapeDNDC – Parameter Uncertainty
(regional scale)
NO 3
Molina et al., in preparation
Above ground biomass
measured mean (t DM ha-1)
0 2 4 6 8 10 12
s im u la ted m e an ( t D M ha- 1 )
0 2 4 6 8 10 12
y= 1.04x r
2=0.98 p < 0.001
UK-EsB (n= 32) CH-Oen (n= 24)
FR-Aur (n= 43) FR-Gri (n= 35) FR-Lam (n= 41) DE-Geb (n= 16)
IT-BCio (n= 64)
DE-Pau (n= 3)
N 2 O emissions
measured mean ( µ g N2O-N m-2 h-1) 0 40 80 120 160 200 s imu la te d mea n ( µ g N 2 O- N m -2 h -1 )
0 40 80 120 160 200
y= 1.01x r
2=0.99 p < 0.001 UK-EsB (n= 182)
DE-Pau (n= 44)
DE-Geb_aut (n= 514) DE-Geb_man (n= 86)
CH-Oen (n= 1012) FR-Gri (n= 444)
IT-BCio (n= 64)
LandscapeDNDC site validation
Institute for Meteorology and Climate Research,(IMK-IFU)
23 29.09.2014 TERENO International Conference 2014
LandscapeDNDC Processes Uncertainties Pathways Outlook
Establishing regional modelling for UNFCC Tier III reporting Coupling LandscapeDNDC to Hydrology & Air Quality models
“Dynamic Farmer” / agent based modelling to replace static agricultural management prescribed via input data
…
LandscapeDNDC Processes Uncertainties Pathways Outlook
Comparing Parameter vs Input Data Uncertainty in N2O & NO3 inventory simulations
N 2 O emissions [t N/yr] Parameter induced Input Data induced
Mean 1 166 644
Q 0.25 379 400
Median (Q 0.5 ) 858 656
Q 0.75 1 686 878
NO 3 leaching [t N/yr]
Mean 22 845 32 310
Q 0.25 19 174 27 990
Median (Q 0.5 ) 24 000 31 230
Q 0.75 28 060 35 990
Klatt et al., in preparation
State of Saxony: area 18 416 km
2, arable cropland: 7 190 km
2Institute for Meteorology and Climate Research,(IMK-IFU)
25 29.09.2014 TERENO International Conference 2014
