کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8959387 | 1646312 | 2018 | 19 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
The response of process-based agro-ecosystem models to within-field variability in site conditions
ترجمه فارسی عنوان
پاسخ مدل های اکوسیستم مبتنی بر فرایند به تغییرات درون محدوده در شرایط سایت
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کلمات کلیدی
تنوع فضایی، خاک مدل محصول، حساسیت مدل،
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
علوم زراعت و اصلاح نباتات
چکیده انگلیسی
Process-oriented agro-ecosystem models are increasingly applied to assess crop management options or impacts of climate change on agricultural production, food security and ecosystem services. Thereby, the aggregation of initial soil and climate information is a widely used approach for performing simulations at larger scales such as regions, nations or even globally. In this context, the ability of models to respond to different site conditions is essential for high quality impact assessment through the use of modelling tools. As part of a model inter-comparison the present study investigated models' yield response on variable site conditions using data sets from two well-documented fields, one located in Germany and one in Italy. The fields were sampled at 60 and 100 grid points, respectively, and soil and crop variables were recorded at varying intensity for the entire simulation period covering three growing seasons. The data was provided successively to the participating modelling groups in three calibration steps (a, b, and c) and the first growing season was considered for calibration. Model validation was based on these steps and each growing season as well as on the entire simulation period considering the soil state variables mineral nitrogen and water content (N, WC) as well as crop yield, biomass, and leaf area index (LAI). The WC was best depicted by the models, resulting in high correlation coefficients (r) up to 0.81 between simulated and observed values. The root mean square error (RMSE) of simulated N ranged from 20âkg haâ1 to 1072âkg haâ1 regarding all steps and growing seasons. The annual within-field variability of yields was better simulated by the models when observed subsoil information was provided. However, the RMSE ranged from 0.5ât haâ1 to 3.5ât haâ1 at the German field, and from 0.6ât haâ1 to 5.9ât haâ1 at the Italian field, respectively. It was found that intensified calibration did not necessarily lead to improved model output. Furthermore, single models showed specific inconsistencies in their algorithms when, for example, underestimated WC was associated with overestimated yields. In total, the sensitivity of models to spatially variable site conditions differed considerably. The importance of quality-assured soil and yield information for model improvement was highlighted.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Field Crops Research - Volume 228, 1 November 2018, Pages 1-19
Journal: Field Crops Research - Volume 228, 1 November 2018, Pages 1-19
نویسندگان
Evelyn Wallor, Kurt-Christian Kersebaum, Domenico Ventrella, Marco Bindi, Davide Cammarano, Elsa Coucheney, Thomas Gaiser, Pasquale Garofalo, Luisa Giglio, Pietro Giola, Munir P. Hoffmann, Ileana Iocola, Marcos Lana, Elisabet Lewan, Ganga Ram Maharjan,