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

被引：150

作者：

Coucheney, Elsa ^{[1
,7
]}

Buis, Samuel ^{[2
]}

Launay, Marie ^{[3
]}

Constantin, Julie ^{[4
]}

Mary, Bruno ^{[1
]}

de Cortazar-Atauri, Itiaki Garcia ^{[3
]}

Ripoche, Dominique ^{[3
]}

Beaudoin, Nicolas ^{[1
]}

Ruget, Francoise ^{[2
]}

Andrianarisoa, Kasaina Sitraka ^{[1
,5
]}

Le Bas, Christine ^{[6
]}

Justes, Eric ^{[4
]}

Leonard, Joel ^{[1
]}

机构：

[1] INRA, UR 1158 Agroimpact, F-02000 Barenton Bugny, France

[2] UAPV, INRA, UMR EMMAH 1114, F-84914 Avignon, France

[3] INRA, AgroClim US1116, F-84914 Avignon, France

[4] INRA INP ENSAT, UMR AGIR 1248, F-31326 Castanet Tolosan, France

[5] ISA Grp HEI ISA ISEN, Lab Biotechnol & Gest Agents Pathogenes Agr BioGA, F-59046 Lille, France

[6] INRA, InfoSol US1106, F-45075 Orleans, France

[7] Swedish Univ Agr Sci, Dept Soil & Environm, S-75007 Uppsala, Sweden

来源：

ENVIRONMENTAL MODELLING & SOFTWARE | 2015年 / 64卷

关键词：

Soil-crop model; STICS; Model performances; Plant biomass; Soil nitrogen; Soil water; REMOTE-SENSING DATA; HYDROLOGICAL MODEL; SOLAR-RADIATION; GENERIC MODEL; VALIDATION; WHEAT; SIMULATION; GROWTH; CALIBRATION; DYNAMICS;

D O I：

10.1016/j.envsoft.2014.11.024

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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.

引用

页码：177 / 190

页数：14

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