| Records |
Author  |
Crout, N.M.J.; Craigon, J.; Cox, G.M.; Jao, Y.; Tarsitano, D.; Wood, A.T.A.; Semenov, M. |
| Title |
An objective approach to model reduction: Application to the Sirius wheat model |
Type |
Journal Article |
| Year |
2014 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
| Volume |
189-190 |
Issue |
100 |
Pages |
211-219 |
| Keywords |
Complexity; Crop model; Evaluation; Model reduction; Parsimony; Wheat |
| Abstract |
An existing simulation model of wheat growth and development, Sirius, was evaluated through a systematic model reduction procedure. The model was automatically manipulated under software control to replace variables within the model structure with constants, individually and in combination. Predictions of the resultant models were compared to growth analysis observations of total biomass, grain yield, and canopy leaf area derived from 9 trials conducted in the UK and New Zealand under optimal, nitrogen limiting and drought conditions. Model performance in predicting these observations was compared in order to evaluate whether individual model variables contributed positively to the overall prediction. Of the 1 1 1 model variables considered 16 were identified as potentially redundant. Areas of the model where there was evidence of redundancy were: (a) translocation of biomass carbon to grain; (b) nitrogen physiology; (c) adjustment of air temperature for various modelled processes; (d) allowance for diurnal variation in temperature; (e) vernalisation (f) soil nitrogen mineralisation (g) soil surface evaporation. It is not suggested that these are not important processes in real crops, rather, that their representation in the model cannot be justified in the context of the analysis. The approach described is analogous to a detailed model inter-comparison although it would be better described as a model intra-comparison as it is based on the comparison of many simplified forms of the same model. The approach provides automation to increase the efficiency of the evaluation and a systematic means of increasing the rigour of the evaluation. |
| Address |
2016-10-31 |
| Corporate Author |
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Thesis |
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Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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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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Medium |
Article |
| Area |
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Expedition |
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Conference |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4788 |
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| Author |
Coucheney, E.; Buis, S.; Launay, M.; Constantin, J.; Mary, B.; García de Cortázar-Atauri, I.; Ripoche, D.; Beaudoin, N.; Ruget, F.; &rianarisoa, K.S.; Le Bas, C.; Justes, E.; Léonard, J. |
| Title |
Accuracy, robustness and behavior of the STICS soil–crop model for plant, water and nitrogen outputs: Evaluation over a wide range of agro-environmental conditions in France |
Type |
Journal Article |
| Year |
2015 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
| Volume |
64 |
Issue |
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Pages |
177-190 |
| Keywords |
soil-crop model; stics; model performances; plant biomass; soil nitrogen; soil water; remote-sensing data; goodness-of-fit; hydrological model; simulation-models; solar-radiation; regional-scale; climate-change; generic model; data set; validation |
| Abstract |
Soil-crop models are increasingly used as predictive tools to assess yield and environmental impacts of agriculture in a growing diversity of contexts. They are however seldom evaluated at a given time over a wide domain of use. We tested here the performances of the STICS model (v8.2.2) with its standard set of parameters over a dataset covering 15 crops and a wide range of agropedoclimatic conditions in France. Model results showed a good overall accuracy, with little bias. Relative RMSE was larger for soil nitrate (49%) than for plant biomass (35%) and nitrogen (33%) and smallest for soil water (10%). Trends induced by contrasted environmental conditions and management practices were well reproduced. Finally, limited dependency of model errors on crops or environments indicated a satisfactory robustness. Such performances make STICS a valuable tool for studying the effects of changes in agro-ecosystems over the domain explored. (C) 2014 Elsevier Ltd. All rights reserved. |
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Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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Edition |
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| ISSN |
1364-8152 |
ISBN |
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Article |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4554 |
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| Author |
Conradt, T.; Koch, H.; Hattermann, F.F.; Wechsung, F.; Hartje, V.; Kaden, S.; Venohr, M.; Hansjürgens, B.; Gräfe, P. |
| Title |
Validierung von Lokalkorrekturen der Verdunstung bei den Simulationen des Wasserabflusses |
Type |
Book Chapter |
| Year |
2013 |
Publication |
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Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
211-231 |
| Keywords |
CropM |
| Abstract |
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Thesis |
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| Publisher |
Weißensee Verl. |
Place of Publication |
Berlin |
Editor |
Wechsung, F.; Hartje, V.; Kaden, S.; Venohr, M.; Hansjürgens, B.; Gräfe, P. |
| Language |
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Summary Language |
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Original Title |
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Series Title |
Die Elbe im globalen Wandel |
Abbreviated Series Title |
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Approved |
no |
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MA @ admin @ |
Serial |
2367 |
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| Author |
Conradt, T.; Hattermann, F.F.; Koch, H.; Wechsung, F. |
| Title |
Klima- und Landnutzungsszenarien in ihren Wirkungen auf den Wasserabfluss |
Type |
Book Chapter |
| Year |
2013 |
Publication |
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Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
177-209 |
| Keywords |
CropM |
| Abstract |
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| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Weißensee Verl. |
Place of Publication |
Berlin |
Editor |
Wechsung, F.; Hartje, V.; Kaden, S.; Venohr, M.; Hansjürgens, B.; Gräfe, P. |
| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
Die Elbe im globalen Wandel |
Abbreviated Series Title |
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Series Issue |
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Edition |
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ISBN |
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Medium |
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Expedition |
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Conference |
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| Notes |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
2365 |
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| 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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Thesis |
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Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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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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Medium |
Article |
| Area |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4709 |
| Permanent link to this record |
