| Records |
| Author |
Hoffmann, H.; Zhao, G.; Van Bussel, L.G.J.; Enders, A.; Specka, X.; Sosa, C.; Yeluripati, J.; Tao, F.; Constantin, J.; Teixeira, E.; Grosz, B.; Doro, L.; Zhao, Z.; Nendel, C.; Kiese, R.; Raynal, H.; Eckersten, H.; Haas, E.; Wang, E.; Kuhnert, M.; Lewan, E.; Bach, M.; Kersebaum, K.-C.; Rötter, R.; Roggero, P.P.; Wallach, D.; Krauss, G.; Siebert, S.; Gaiser, T.; Cammarano, D.; Asseng, S.; Ewert, F. |
| Title |
Influence of climate input data aggregation on simulated yield |
Type |
Conference Article |
| Year |
2014 |
Publication |
|
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
|
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
ESA Congress |
Series Volume  |
13 Debrecen, |
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
ESA Congress, 2014-08-25 to 2014-08-29, Debrecen, 13: |
| Notes |
|
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5039 |
| Permanent link to this record |
| |
|
| |
| Author |
Zhao, G.; Hoffmann, H.; Van Bussel, L.G.J.; Enders, A.; Specka, X.; Sosa, C.; Yeluripati, J.; Tao, F.; Constantin, J.; Teixeira, E.; Grosz, B.; Luca, D.; Zhao, Z.; Nendel, C.; Ralf, K.; Raynal, H.; Eckersten, H.; Haas, E.; Wang, E.; Kuhnert, M.; Lewan, E.; Bach, M.; Kersebaum, K.-C.; Rötter, R.; Roggero, P.P.; Wallach, D.; Krauss, G.; Siebert, S.; Gaiser, T.; Cammarano, D.; Asseng, S.; Ewert, F. |
| Title |
Weather data aggregation’s effect on simulation of cropping systems: a model, production system and crop comparison |
Type |
Conference Article |
| Year |
2014 |
Publication |
|
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
|
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
ESA Congress |
| Series Volume |
13 Debrecen, |
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
ESA Congress, 2014-08-25 to 2014-08-29, Debrecen, 13: |
| Notes |
|
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5040 |
| Permanent link to this record |
| |
|
| |
| Author |
Ewert, F.; van Bussel, L.G.J.; Zhao, G.; Hoffmann, H.; Gaiser, T.; Specka, X.; Nendel, C.; Kersebaum, K.-C.; Sosa, C.; Lewan, E.; Yeluripati, J.; Kuhnert, M.; Tao, F.; Rötter, R.P.; Constantin, J.; Raynal, H.; Wallach, D.; Teixeira, E.; Grosz, B.; Bach, M.; Doro, L.; Roggero, P.P.; Zhao, Z.; Wang, E.; Kiese, R.; Haas, E.; Eckersten, H.; Trombi, G.; Bindi, M.; Klein, C.; Biernath, C.; Heinlein, F.; Priesack, E.; Cammarano, D.; Asseng, S.; Elliott, J.; Glotter, M.; Basso, B.; Baigorria, G.A.; Romero, C.C.; Moriondo, M. |
| Title |
Uncertainties in Scaling up Crop Models for Large Area Climate-change Impact Assessments |
Type |
Book Chapter |
| Year |
2015 |
Publication |
|
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
261-277 |
| Keywords |
CropM; |
| Abstract |
|
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Imperial College Press |
Place of Publication |
London |
Editor |
Rosenzweig, C.; Hillel, D. |
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
Handbook of Climate Change and Agroecosystems: The Agricultural Model Intercomparison and Improvement Project (AgMIP) Integrated Crop and Economic Assessments — Joint Publication with American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America (In 2 Parts) |
Abbreviated Series Title |
|
| Series Volume |
ICP Series on Climate Change Impacts, Adaptation, |
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
|
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
2427 |
| Permanent link to this record |
| |
|
| |
| Author |
Hoffmann, H.; Zhao, G.; Van Bussel, L.; Enders, A.; Specka, X.; Sosa, C.; Yeluripati, J.; Tao, F.; Constantin, J.; Teixeira, E.; Grosz, B.; Doro, L.; Nendel, C.; Kiese, R.; Raynal, H.; Eckersten, H.; Haas, E.; Kuhnert, M.; Lewan, E.; Bach, M.; Kersebaum, K.-C.; Roggero, P.P.; Rötter, R.; Wallach, D.; Krauss, G.; Siebert, S.; Gaiser, T.; Wang, E.; Zhao, Z.; Ewert, F. |
| Title |
Effects of climate input data aggregation on modelling regional crop yields |
Type |
Conference Article |
| Year |
2014 |
Publication |
|
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
Crop models can be sensitive to climate input data aggregation and this response may differ among models. This should be considered when applying field-scale models for assessment of climate change impacts on larger spatial scales or when coupling models across scales. In order to evaluate these effects systematically, an ensemble of ten crop models was run with climate input data on different spatial aggregations ranging from 1, 10, 25, 50 and 100 km horizontal resolution for the state of North Rhine-Westphalia, Germany. Models were minimally calibrated to typical sowing and harvest dates, and crop yields observed in the region, subsequently simulating potential, water-limited and nitrogen-limited production of winter wheat and silage maize for 1982-2011. Outputs were analysed for 19 variables (yield, evapotranspiration, soil organic carbon, etc.). In this study the sensitivity of the individual models and the model ensemble in response to input data aggregation is assessed for crop yield. Results show that the mean yield of the region calculated from climate time series of 1 km horizontal resolution changes only little when using climate input data of higher aggregation levels for most models. However, yield frequency distributions change with aggregation, resembling observed data better with increasing resolution. With few exceptions, these results apply to the two crops and three production situations (potential, water-, nitrogen-limited) and across models including the model ensemble, regardless of differences among models in simulated yield levels and spatial yield patterns. Results of this study improve the confidence of using crop models at varying scales. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
| Series Volume |
3(S) Sassari, Italy |
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
| Notes |
|
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5077 |
| Permanent link to this record |
| |
|
| |
| Author |
Haas, E.; Klatt, S.; Kiese, R.; Santa Barbara Ruiz, I.; Kraus, D. |
| Title |
Parameter-induced uncertainty quantification of a regional N2O and NO3 inventory using the biogeochemical model LandscapeDNDC |
Type |
Conference Article |
| Year |
2014 |
Publication |
|
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
In this study we quantify regional parameter-induced model uncertainty on nitrous oxide (N2O) emissions and nitrate (NO3) leaching from arable soils of Saxony (Germany) using the biogeochemical model LandscapeDNDC. For this we calculate a regional inventory using a joint parameter distribution for key parameters describing microbial C and N turnover processes as obtained by a Bayesian calibration study. We representatively sampled 400 different parameter vectors from the discrete joint parameter distribution comprising approximately 400,000 parameter combinations and used these to calculate 400 individual realizations of the regional inventory. The spatial domain (represented by 4042 polygons) is set up with spatially explicit soil and climate information and a region-typical 3-year crop rotation consisting of winter wheat, rape- seed, and winter barley. Average N2O emission from arable soils in the state of Saxony across all 400 realizations was 1.43 ± 1.25 [kg N / ha] with a median value of 1.05 [kg N / ha]. Using the default IPCC emission factor approach (Tier 1) for direct emissions reveal a higher average N2O emission of 1.51 [kg N / ha] due to fertilizer use. In the regional uncertainty quantification the 20% likelihood range for N2O emissions is 0.79 – 1.37 [kg N / ha] (50% likelihood: 0.46 – 2.05 [kg N / ha]; 90% likelihood: 0.11 – 4.03 [kg N / ha]). Respective quantities were calculated for nitrate leaching. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
| Series Volume |
3(S) Sassari, Italy |
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
| Notes |
|
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5111 |
| Permanent link to this record |
