Uncertainty propagation analysis of an N2O emission model at the plot and landscape scale

Nol, L.; Heuvelink, G.B.M.; Veldkamp, A.; Vries, Wim de; Kros, J.

doi:10.1016/j.geoderma.2010.06.009

Cited by 46 publications

(24 citation statements)

References 46 publications

(48 reference statements)

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“…This is clearly larger than the uncertainty at the EU27 level from this study (12 %), but also larger than uncertainties from this study at NCU level (26-44 %). The reason for the larger uncertainty might be that Nol et al (2010) also included uncertainty on detailed management information, which is lacking in our study. Due to the different nature and character of the agricultural sources, among regions and countries, as well as by the limited number and uneven spread of the measurements concerning related emission parameters, the uncertainty in local scale estimates of N 2 O emissions can be rather large .…”

Section: Plausibility Of the Uncertainty Quantificationmentioning

confidence: 98%

“…Nol et al (2010) estimated an average N 2 O emission at landscape scale of 20.5 kg N 2 O-N ha −1 yr −1 and a standard deviation of 10.7 kg N 2 O-N ha −1 yr −1 , implying a relative uncertainty of 52 %. This is clearly larger than the uncertainty at the EU27 level from this study (12 %), but also larger than uncertainties from this study at NCU level (26-44 %).…”

Section: Plausibility Of the Uncertainty Quantificationmentioning

confidence: 99%

“…Lehuger et al, 2009), at landscape scale (e.g. Nol et al, 2010) and at national scale (e.g. Del Grosso et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…Del Grosso et al, 2010). Nol et al (2010) performed an uncertainty propagation analysis for a Dutch fen meadow landscape using the INITIATOR model, while including uncertain spatial model inputs. They used a Monte Carlo (MC) analysis combined with a novel method for estimating and simulating continuous-numerical and categorical input variables, handling spatial and crosscorrelations.…”

Section: Introductionmentioning

confidence: 99%

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Uncertainties in model predictions of nitrogen fluxes from agro-ecosystems in Europe

et al. 2012

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Abstract.To assess the responses of nitrogen and greenhouse gas emissions to pan-European changes in land cover, land management and climate, an integrated dynamic model, INTEGRATOR, has been developed. This model includes both simple process-based descriptions and empirical relationships and uses detailed GIS-based environmental and farming data in combination with various downscaling methods. This paper analyses the propagation of uncertainties in model inputs and parameters to outputs of INTEGRA-TOR, using a Monte Carlo analysis. Uncertain model inputs and parameters were represented by probability distributions, while spatial correlation in these uncertainties was taken into account by assigning correlation coefficients at various spatial scales. The uncertainty propagation was analysed for the emissions of NH 3 , N 2 O and NO x , N leaching to groundwater and N runoff to surface water for the entire EU27 and for individual countries. Results show large uncertainties for N leaching and runoff (relative errors of ∼ 19 % for Europe as a whole), and smaller uncertainties for emission of N 2 O, NH 3 and NO x (relative errors of ∼ 12 %). Uncertainties for Europe as a whole were much smaller compared to uncertainties at country level, because errors partly cancelled out due to spatial aggregation.

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Section: Plausibility Of the Uncertainty Quantificationmentioning

confidence: 98%

Section: Plausibility Of the Uncertainty Quantificationmentioning

confidence: 99%

“…Lehuger et al, 2009), at landscape scale (e.g. Nol et al, 2010) and at national scale (e.g. Del Grosso et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Uncertainties in model predictions of nitrogen fluxes from agro-ecosystems in Europe

et al. 2012

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“…Some effects of uncertainty propagation might also play a role in our methodology of terroir delineation. A good example on how this could be done is well explained in Nol, Heuvelink, Veldkamp, de Vries, and Kros (2010). A proper execution of such an uncertainty propagation analysis goes beyond the scope of this thesis.…”

Section: Future Directionsmentioning

confidence: 99%

Smallholder coffee terroirs of Rwanda : linking local to global trade through geographical characterization

Mukashema¹

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Projected Changes in Soil Organic Carbon Stocks Upon Adoption of Recommended Soil and Water Conservation Practices in the Upper Tana River Catchment, Kenya

Batjes

2012

Land Degrad Dev

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Large areas in the Upper Tana river catchment, Kenya, have been over‐exploited, resulting in soil erosion, nutrient depletion and loss of soil organic matter (SOM). This study focuses on sections of the catchment earmarked as being most promising for implementing Green Water Credits, an incentive mechanism to help farmers invest in land and soil management activities that affect all fresh water resources at source. Such management practices can also help restore SOM levels towards their natural level. Opportunities to increase soil organic carbon (SOC) stocks, for two broadly defined land use types (croplands and plantation crops, with moderate input levels), are calculated using a simple empirical model, using three scenarios for the proportion of suitable land that may be treated with these practices (low = 40 per cent, medium = 60 per cent, high = 80 per cent). For the medium scenario, corresponding to implementation on ~348 000 ha in the basin, the eco‐technologically possible SOC gains are estimated at 4·8 to 9·3 × 106 tonnes (Mg) CO2 over the next 20 years. Assuming a conservative price of US$10 per tonne CO2‐equivalent on the carbon offset market, this would correspond to ~US$48–93 million over a 20‐year period of sustained green water management. This would imply a projected (potential) payment of some US$7–13 ha−1 to farmers annually; this sum would be in addition to incentives that are being put in place for implementing green water management practices and also in addition to the benefits that farmers would realize from the impact on production of these practices themselves. Copyright © 2012 John Wiley & Sons, Ltd.

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Uncertainty propagation analysis of an N2O emission model at the plot and landscape scale

Cited by 46 publications

References 46 publications

Uncertainties in model predictions of nitrogen fluxes from agro-ecosystems in Europe

Uncertainties in model predictions of nitrogen fluxes from agro-ecosystems in Europe

Smallholder coffee terroirs of Rwanda : linking local to global trade through geographical characterization

Projected Changes in Soil Organic Carbon Stocks Upon Adoption of Recommended Soil and Water Conservation Practices in the Upper Tana River Catchment, Kenya

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