Effects of data aggregation on simulations of crop phenology

被引:55
作者
van Bussel, L. G. J. [1 ,3 ]
Ewert, F. [1 ,2 ]
Leffelaar, P. A. [1 ]
机构
[1] Wageningen Univ, Plant Prod Syst Grp, NL-6700 AK Wageningen, Netherlands
[2] Univ Bonn, Inst Crop Sci & Resource Conservat INRES, D-53115 Bonn, Germany
[3] Netherlands Environm Assessment Agcy PBL, NL-3720 AH Bilthoven, Netherlands
关键词
Scaling; Spatial scales; Crop phenology model; Winter wheat; Emergence; ear emergence and harvest dates; AFRCWHEAT2; DIFFERENT SOWING DATES; PROCESS-BASED MODEL; WINTER-WHEAT CROPS; CLIMATE-CHANGE; SCALING-UP; LARGE-AREA; VARIABILITY; IMPACTS; PRODUCTIVITY; EUROPE;
D O I
10.1016/j.agee.2010.03.019
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Policy decisions are often taken at the regional scale, while crop models, supporting these decisions, have been developed for individual locations, expecting location-specific, spatially homogeneous input data. Crop models are able to account for the variation in climatic conditions and management activities and their effects on crop productivity. However, regional applications require consideration of spatial variability in these factors. Several studies have analyzed effects of using spatially aggregated climate data on model outcomes. The effects of spatially aggregated sowing dates on simulations of crop phenological development have not been studied, however. We investigated the impact of spatial aggregation of sowing dates and temperatures on the simulated occurrence of ear emergence and physiological maturity of winter wheat in Germany, using the phenological model of AFRCWHEAT2. We observed time ranges for crop emergence exceeding 90d, whereas for harvesting this was more than 75 d. Spatial aggregation to 100 km x 100 km reduced this range to less than 30 and 20 d for emergence and harvest, respectively. Differences among selected regions were relatively small, suggesting that non-climatic factors largely determined the spatial variability in sowing dates and consecutive phenological stages. Application of the AFRCWHEAT2 phenology model using location-specific weather data and emergence dates, and an identical crop parameter set across Germany gave similar deviations in all studied regions, suggesting that varietal differences were less important among regions than within regions. Importantly, bias in model outcomes as a result of using aggregated input data was small. Increase in resolution from 100 km to 50 km resulted in slight improvements in the simulations. We conclude that using spatially aggregated weather data and emergence dates to simulate the length of the growing season for winter wheat in Germany is justified for grid cells with a maximum area of 100 km x 100 km and for the model considered here. As spatial variability of sowing dates within a region or country can be large, it is important to obtain information about the representative sowing date for the region. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:75 / 84
页数:10
相关论文
共 39 条
[11]  
Dennett M. D., 1999, Wheat: ecology and physiology of yield determination., P123
[12]   Spatial scales of climate information for simulating wheat and maize productivity: the case of the US Great Plains [J].
Easterling, WE ;
Weiss, A ;
Hays, CJ ;
Mearns, LO .
AGRICULTURAL AND FOREST METEOROLOGY, 1998, 90 (1-2) :51-63
[13]   Comparison of agricultural impacts of climate change calculated from high and low resolution climate change scenarios:: Part II.: Accounting for adaptation and CO2 direct effects [J].
Easterling, WE ;
Mearns, LO ;
Hays, CJ ;
Marx, D .
CLIMATIC CHANGE, 2001, 51 (02) :173-197
[14]   Trends and temperature response in the phenology of crops in Germany [J].
Estrella, Nicole ;
Sparks, Tim H. ;
Menzel, Annette .
GLOBAL CHANGE BIOLOGY, 2007, 13 (08) :1737-1747
[15]   Simulation of growth and development processes of spring wheat in response to CO2 and ozone for different sites and years in Europe using mechanistic crop simulation models [J].
Ewert, F ;
van Oijen, M ;
Porter, JR .
EUROPEAN JOURNAL OF AGRONOMY, 1999, 10 (3-4) :231-247
[16]   Use of AFRCWHEAT2 to predict the development of main stem and tillers in winter triticale and winter wheat in North East Germany [J].
Ewert, F ;
Porter, J ;
Honermeier, B .
EUROPEAN JOURNAL OF AGRONOMY, 1996, 5 (1-2) :89-103
[17]   EFFECT OF SOWING TIME ON YIELD AND AGRONOMIC CHARACTERISTICS OF WHEAT IN SOUTH-EASTERN AUSTRALIA [J].
GOMEZMACPHERSON, H ;
RICHARDS, RA .
AUSTRALIAN JOURNAL OF AGRICULTURAL RESEARCH, 1995, 46 (07) :1381-1399
[18]   Scaling-up crop models for climate variability applications [J].
Hansen, JW ;
Jones, JW .
AGRICULTURAL SYSTEMS, 2000, 65 (01) :43-72
[19]   Scaling-up the AFRCWHEAT2 model to assess phenological development for wheat in Europe [J].
Harrison, PA ;
Porter, JR ;
Downing, TE .
AGRICULTURAL AND FOREST METEOROLOGY, 2000, 101 (2-3) :167-186
[20]   Reconciling alternative models of phenological development in winter wheat [J].
Jamieson, P. D. ;
Brooking, I. R. ;
Semenov, M. A. ;
MeMaster, G. S. ;
White, J. W. ;
Porter, J. R. .
FIELD CROPS RESEARCH, 2007, 103 (01) :36-41