| Records |
| Author |
Conradt, T.; Gornott, C.; Wechsung, F. |
| Title |
Extending and improving regionalized winter wheat and silage maize yield regression models for Germany: Enhancing the predictive skill by panel definition through cluster analysis |
Type |
Journal Article |
| Year |
2016 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
| Volume |
216 |
Issue |
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Pages |
68-81 |
| Keywords |
cluster analysis; crop yield estimation; germany; multivariate regression; silage maize; winter wheat; climate-change; canadian prairies; crop yield; temperature; responses; environments; variability; cultivar; china |
| Abstract |
Regional agricultural yield assessments allowing for weather effect quantifications are a valuable basis for deriving scenarios of climate change effects and developing adaptation strategies. Assessing weather effects by statistical methods is a classical approach, but for obtaining robust results many details deserve attention and require individual decisions as is demonstrated in this paper. We evaluated regression models for annual yield changes of winter wheat and silage maize in more than 300 German counties and revised them to increase their predictive power. A major effort of this study was, however, aggregating separately estimated time series models (STSM) into panel data models (PDM) based on cluster analyses. The cluster analyses were based on the per-county estimates of STSM parameters. The original STSM formulations (adopted from a parallel study) contained also the non-meteorological input variables acreage and fertilizer price. The models were revised to use only weather variables as estimation basis. These consisted of time aggregates of radiation, precipitation, temperature, and potential evapotranspiration. Altering the input variables generally increased the predictive power of the models as did their clustering into PDM. For each crop, five alternative clusterings were produced by three different methods, and similarities between their spatial structures seem to confirm the existence of objective clusters about common model parameters. Observed smooth transitions of STSM parameter values in space suggest, however, spatial autocorrelation effects that could also be modeled explicitly. Both clustering and autocorrelation approaches can effectively reduce the noise in parameter estimation through targeted aggregation of input data. (C) 2015 Elsevier B.V. All rights reserved. |
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| Language |
English |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0168-1923 |
ISBN |
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Article |
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Conference |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4709 |
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| Author |
Conradt, T.; Wechsung, F.; Bronstert, A. |
| Title |
Three perceptions of the evapotranspiration landscape: comparing spatial patterns from a distributed hydrological model, remotely sensed surface temperatures, and sub-basin water balances |
Type |
Journal Article |
| Year |
2013 |
Publication |
Hydrology and Earth System Sciences |
Abbreviated Journal |
Hydrol. Earth System Sci. |
| Volume |
17 |
Issue |
7 |
Pages |
2947-2966 |
| Keywords |
senegal river-basin; data assimilation; sensing data; regional evapotranspiration; intercomparison project; environmental-models; oklahoma experiments; solar-radiation; satellite data; scale |
| Abstract |
A problem encountered by many distributed hydrological modelling studies is high simulation errors at interior gauges when the model is only globally calibrated at the outlet. We simulated river runoff in the Elbe River basin in central Europe (148 268 km(2)) with the semi-distributed eco-hydrological model SWIM (Soil and Water Integrated Model). While global parameter optimisation led to Nash-Sutcliffe efficiencies of 0.9 at the main outlet gauge, comparisons with measured runoff series at interior points revealed large deviations. Therefore, we compared three different strategies for deriving sub-basin evapotranspiration: (1) modelled by SWIM without any spatial calibration, (2) derived from remotely sensed surface temperatures, and (3) calculated from long-term precipitation and discharge data. The results show certain consistencies between the modelled and the remote sensing based evapotranspiration rates, but there seems to be no correlation between remote sensing and water balance based estimations. Subsequent analyses for single sub-basins identify amongst others input weather data and systematic error amplification in inter-gauge discharge calculations as sources of uncertainty. The results encourage careful utilisation of different data sources for enhancements in distributed hydrological modelling. |
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English |
Summary Language |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
1607-7938 |
ISBN |
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Article |
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Conference |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4485 |
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| Author |
Kersebaum, K.C.; Kollas, C.; Bindi, M.; Palosuo, T.; Wu, L.; Sharif, B.; Öztürk, I.; Trnka, M.; Hlavinka, P.; Nendel, C.; Müller, C.; Waha, K.; Armas-Herrera, C.; Olesen, J.E.; Eitzinger, J.; Roggero, P.P.; Conradt, T.; Martre, P.; Ferrise, R.; Moriondo, M.; Ruiz-Ramos, M.; Ventrella, D.; Rötter, R.P.; Wegehenkel, M.; Eckersten, H.; Lorite Torres, I.J.; Hernandez, C.G.; Launay, M.; De Wit, A.; Hoffmann, H.; Weigel, H.-J.; Manderscheid, R.; Beaudoin, N.; Constantin, J.; Garcia de Cortazar-Atauri, I.; Mary, B.; Ripoche, D.; Ruget, F. |
| Title |
Model inter-comparison on crop rotation effects – an intermediate report |
Type |
Conference Article |
| Year |
2014 |
Publication |
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Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Abstract |
Data of diverse crop rotations from five locations across Europe were distributed to modelers to investigate the capability of models to handle complex crop rotations and management interactions. Crop rotations comprise various main crops (winter/spring wheat, winter/spring barley, rye, oat, maize, sugar beet, oil seed rape and potatoes) plus several catch crops. The experimental setup of the datasets included treatments such as modified soils, crops exchanged within the rotations, irrigation/rainfed, nitrogen fertilization, residue management, tillage and atmospheric CO2 concentration. 19 modeling teams registered to model either the whole rotation or single crops. Models which are capable to run the whole rotation should provide transient as well as single year simulations with a reset of initial conditions. In the first step only initial soil conditions (water and soil mineral N) of the first year and key phenological stages were provided to the modelers. For calibration, crop yields and biomass were provided for selected years but not for all seasons. In total the combination of treatments and seasons results in 301 years of simulation. Results were analyzed to evaluate the effect of transient simulation versus single-year simulation regarding crop yield, biomass, water and nitrogen balance components. Model results will be evaluated crop-specifically to identify crops with highest uncertainty and potential for model improvement. Full data will be provided to modelers for model-improvement and results will provide insights into model capabilities to reproduce treatments and crops. Further, the question of error propagation along the transient simulation of crop rotations will be addressed. |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
| Series Volume |
3(S) Sassari, Italy |
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Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
| Notes |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5104 |
| Permanent link to this record |
