publication . Article . 2016

Spatial sampling of weather data for regional crop yield simulations

Lenny G.J. van Bussel; Frank Ewert; Gang Zhao; Holger Hoffmann; Andreas Enders; Daniel Wallach; Senthold Asseng; Guillermo A. Baigorria; Bruno Basso; Christian Biernath; ...
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  • Published: 23 Jan 2016 Journal: Agricultural and Forest Meteorology, volume 220, pages 101-115 (issn: 0168-1923, Copyright policy)
  • Publisher: Elsevier BV
Abstract
Abstract Field-scale crop models are increasingly applied at spatio-temporal scales that range from regions to the globe and from decades up to 100 years. Sufficiently detailed data to capture the prevailing spatio-temporal heterogeneity in weather, soil, and management conditions as needed by crop models are rarely available. Effective sampling may overcome the problem of missing data but has rarely been investigated. In this study the effect of sampling weather data has been evaluated for simulating yields of winter wheat in a region in Germany over a 30-year period (1982–2011) using 12 process-based crop models. A stratified sampling was applied to compare th...
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Subjects
free text keywords: Agronomy and Crop Science, Forestry, Atmospheric Science, Global and Planetary Change, Stratified sampling, Soil water, Statistics, Crop yield, Missing data, Stratification (seeds), Sample size determination, Weather data, Hydrology, Environmental science, Sampling (statistics)
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