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Hidy, D.; Balogh, J.; Churkina, G.; Haszpra, L.; Horváth, F.; Ittzés, P.; Ittzés, D.; Ma, S.; Nagy, Z.; Pintér, K.; Barcza, Z. |
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Structural development and web service based sensitivity analysis of the Biome-BGC MuSo model |
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2014 |
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LiveM |
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European GeoSciences Union (EGU), General Assembly 2014, 2014-04-28 to 2014-05-02 |
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MA @ admin @ |
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2475 |
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Lellei-Kovács, E.; Barcza, Z.; Hidy, D.; Horváth, F.; Ittzés, D.; Ittzés, P.; Ma, S.; Bellocchi, G. |
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Title |
Application of Biome-BGC MuSo in managed grassland ecosystems in the Euro-Mediteranean region |
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Conference Article |
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2014 |
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Simulation of the biogeochemical cycles of extensively and intensively managed grasslands and croplands are of particular interest due to the strong connection between ecosystem production, animal husbandry and food security. In the frame of MACSUR LiveM activities, we conducted a series of „blind tests” (i.e. uncalibrated model simulations with previously optimized model) on differently managed grasslands within Europe and Israel. We used the latest version of Biome-BGC MuSo model, the modified version of the widely used biogeochemical Biome-BGC model. Biome-BGC MuSo contains structural improvements, development of management modules, and the extension of the model to simulate herbaceouos ecosystem carbon and water cycles more faithfully. The studied ecosystems were meadows and pastures located in a variety of climate zones from the Atlantic sector to Central Europe, including Mediterranean sites. Managements were intensive and extensive grazing or mowing with or without different kind of fertilizers. Under similar options we simulated ecosystem variables, e.g. Gross Primary Production (GPP) and Net Ecosystem Exchange (NEE). Our experiences show that different sites have different sensitivity to the parameters (maximum root depth, soil parameters, etc.), but overall the model provided realistic fluxes. Experiences gained during the blind tests led us to further improve the model. Biome-BGC MuSo is available as a standalone model in personal computers, but also through virtual laboratory environment and Biome-BGC Projects database (http://ecos.okologia.mta.hu/bbgcdb) developed within the BioVeL project (http://www.biovel.eu). Scientific workflow management, web service and desktop grid technology can support model optimization in the so-called „calibrated runs” within MACSUR. |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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no |
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MA @ admin @ |
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5054 |
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Ma, S.; Acutis, M.; Barcza, Z.; Ben, T., H.; Doro, L.; Hidy, D.; Köchy, M.; Minet, J.; Lellei-Kovács, E.; Perego, A.; Rolinski, S.; Ruget, F.; Seddaiu, G.; Wu, L.; Bellocchi, G. |
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The grassland model intercomparison of the MACSUR (Modelling European Agriculture with Climate Change for Food Security) European knowledge hub |
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Conference Article |
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2014 |
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LiveM |
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7th International Congress on Environmental Modelling and Software, 2014-06-15 to 2014-06-19 |
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no |
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Call Number |
MA @ admin @ |
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2618 |
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Ma, S.; Ben, T., H.; Lellei-Kovács, E.; Barcza, Z.; Hidy, D.; Bellocchi, G. |
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Title |
Grassland model intercomparison of the knowledge hub MACSUR: illustrative results from the models PaSim and Biome-BGC MuSo |
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Conference Article |
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2014 |
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LiveM |
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XIII ESA congress, Debrecen, Hungary, 2014-08-25 to 2014-08-29 |
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no |
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MA @ admin @ |
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2617 |
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Ma, S.; Lardy, R.; Graux, A.-I.; Ben Touhami, H.; Klumpp, K.; Martin, R.; Bellocchi, G. |
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Title |
Regional-scale analysis of carbon and water cycles on managed grassland systems |
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Journal Article |
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2015 |
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Environmental Modelling & Software |
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Env. Model. Softw. |
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72 |
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356-371 |
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carbon flux; eddy flux measurements; model evaluation; pasture simulation model (pasim); water balance; pasture simulation-model; nitrous-oxide emissions; primary productivity npp; comparing global-models; net ecosystem exchange; greenhouse-gas balance; climate-change; agricultural systems; co2 exchange; european grasslands |
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Predicting regional and global carbon (C) and water dynamics on grasslands has become of major interest, as grasslands are one of the most widespread vegetation types worldwide, providing a number of ecosystem services (such as forage production and C storage). The present study is a contribution to a regional-scale analysis of the C and water cycles on managed grasslands. The mechanistic biogeochemical model PaSim (Pasture Simulation model) was evaluated at 12 grassland sites in Europe. A new parameterization was obtained on a common set of eco-physiological parameters, which represented an improvement of previous parameterization schemes (essentially obtained via calibration at specific sites). We found that C and water fluxes estimated with the parameter set are in good agreement with observations. The model with the new parameters estimated that European grassland are a sink of C with 213 g C m(-2) yr(-1), which is close to the observed net ecosystem exchange (NEE) flux of the studied sites (185 g C m(-2) yr(-1) on average). The estimated yearly average gross primary productivity (GPP) and ecosystem respiration (RECO) for all of the study sites are 1220 and 1006 g C m(-2) yr(-1), respectively, in agreement with observed average GPP (1230 g C m(-2) yr(-1)) and RECO (1046 g C m(-2) yr(-1)). For both variables aggregated on a weekly basis, the root mean square error (RMSE) was similar to 5-16 g C week(-1) across the study sites, while the goodness of fit (R-2) was similar to 0.4-0.9. For evapotranspiration (ET), the average value of simulated ET (415 mmyr(-1)) for all sites and years is close to the average value of the observed ET (451 mm yr(-1)) by flux towers (on a weekly basis, RMSE similar to 2-8 mm week(-1); R-2 = 0.3-0.9). However, further model development is needed to better represent soil water dynamics under dry conditions and soil temperature in winter. A quantification of the uncertainties introduced by spatially generalized parameter values in C and water exchange estimates is also necessary. In addition, some uncertainties in the input management data call for the need to improve the quality of the observational system. |
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2015-10-09 |
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English |
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1364-8152 |
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Notes |
CropM, LiveM, ft_macsur |
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MA @ admin @ |
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4695 |
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