Characteristic 'fingerprints' of crop model responses data at different spatial resolutions to weather input

被引:49
作者
Angulo, Carlos [1 ]
Roetter, Reimund [2 ]
Trnka, Mirek [3 ,4 ]
Pirttioja, Nina [5 ]
Gaiser, Thomas [1 ]
Hlavinka, Petr [3 ,4 ]
Ewert, Frank [1 ]
机构
[1] Univ Bonn, Inst Crop Sci & Resource Conservat INRES, D-53115 Bonn, Germany
[2] MTT Agrifood Res Finland, FI-50100 Mikkeli, Finland
[3] Mendel Univ Brno, Inst Agrosyst & Bioclimatol, Brno 61300, Czech Republic
[4] Global Change Res Ctr AS CR, Vvi, Brno 60300, Czech Republic
[5] Finnish Environm Inst SYKE, FI-00251 Helsinki, Finland
基金
芬兰科学院;
关键词
Crop model; Weather data resolution; Aggregation; Yield distribution; CLIMATE-CHANGE; WINTER-WHEAT; SIMULATION; IMPACTS; YIELD; PRODUCTIVITY; AGGREGATION; INFORMATION; TEMPERATURE; ENVIRONMENT;
D O I
10.1016/j.eja.2013.04.003
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Crop growth simulation models are increasingly used for regionally assessing the effects of climate change and variability on crop yields. These models require spatially and temporally detailed, location-specific, environmental (weather and soil) and management data as inputs, which are often difficult to obtain consistently for larger regions. Aggregating the resolution of input data for crop model applications may increase the uncertainty of simulations to an extent that is not well understood. The present study aims to systematically analyse the effect of changes in the spatial resolution of weather input data on yields simulated by four crop models (LINTUL-SLIM, DSSAT-CSM, EPIC and WOFOST) which were utilized to test possible interactions between weather input data resolution and specific modelling approaches representing different degrees of complexity. The models were applied to simulate grain yield of spring barley in Finland for 12 years between 1994 and 2005 considering five spatial resolutions of daily weather data: weather station (point) and grid-based interpolated data at resolutions of 10 km x 10 km; 20 km x 20 km; 50 km x 50 km and 100 km x 100 km. Our results show that the differences between models were larger than the effect of the chosen spatial resolution of weather data for the considered years and region. When displaying model results graphically, each model exhibits a characteristic 'fingerprint' of simulated yield frequency distributions. These characteristic distributions in response to the inter-annual weather variability were independent of the spatial resolution of weather input data. Using one model (LINTUL-SLIM), we analysed how the aggregation strategy, i.e. aggregating model input versus model output data, influences the simulated yield frequency distribution. Results show that aggregating weather data has a smaller effect on the yield distribution than aggregating simulated yields which causes a deformation of the model fingerprint. We conclude that changes in the spatial resolution of weather input data introduce less uncertainty to the simulations than the use of different crop models but that more evaluation is required for other regions with a higher spatial heterogeneity in weather conditions, and for other input data related to soil and crop management to substantiate our findings. Our results provide further evidence to support other studies stressing the importance of using not just one, but different crop models in climate assessment studies. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:104 / 114
页数:11
相关论文
共 63 条
[1]   Effects of modelling detail on simulated potential crop yields under a wide range of climatic conditions [J].
Adam, M. ;
Van Bussel, L. G. J. ;
Leffelaar, P. A. ;
Van Keulen, H. ;
Ewert, F. .
ECOLOGICAL MODELLING, 2011, 222 (01) :131-143
[2]   SIMULATION OF SOLUTE LEACHING IN SOILS OF DIFFERING PERMEABILITIES [J].
ADDISCOTT, TM ;
WHITMORE, AP .
SOIL USE AND MANAGEMENT, 1991, 7 (02) :94-102
[3]  
Allen R. G., 1998, FAO Irrigation and Drainage Paper
[4]   Implication of crop model calibration strategies for assessing regional impacts of climate change in Europe [J].
Angulo, Carlos ;
Rotter, Reimund ;
Lock, Reiner ;
Enders, Andreas ;
Fronzek, Stefan ;
Ewert, Frank .
AGRICULTURAL AND FOREST METEOROLOGY, 2013, 170 :32-46
[5]  
[Anonymous], 2008, Journal of Statistical Software, Code Snippets, DOI [10.18637/jss.v028.c01, DOI 10.18637/JSS.V028.C01]
[6]  
Boogaard H.E.A., 1998, WOFOST 7 1 USERS GUI
[7]  
Boons-Prins E.R., 1993, Crop specific simulation parameters for yield forecasting across the European Community
[8]   STICS: a generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parameterization applied to wheat and corn [J].
Brisson, N ;
Mary, B ;
Ripoche, D ;
Jeuffroy, MH ;
Ruget, F ;
Nicoullaud, B ;
Gate, P ;
Devienne-Barret, F ;
Antonioletti, R ;
Durr, C ;
Richard, G ;
Beaudoin, N ;
Recous, S ;
Tayot, X ;
Plenet, D ;
Cellier, P ;
Machet, JM ;
Meynard, JM ;
Delecolle, R .
AGRONOMIE, 1998, 18 (5-6) :311-346
[9]   METHODS AND RESOURCES FOR CLIMATE IMPACTS RESEARCH Achieving Synergy [J].
Challinor, Andrew Juan ;
Osborne, Tom ;
Morse, Andy ;
Shaffrey, Len ;
Wheeler, Tim ;
Weller, Hilary ;
Vidale, Pier Luigi .
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 2009, 90 (06) :836-+
[10]   The modifiable areal unit problem (MAUP) in physical geography [J].
Dark, Shawna J. ;
Bram, Danielle .
PROGRESS IN PHYSICAL GEOGRAPHY, 2007, 31 (05) :471-479