Calibration and evaluation of a crop model using remote sensing data

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Title:Main Title: Calibration and evaluation of a crop model using remote sensing data
Description:Abstract: Agricultural ecosystems are highly depending on environmental factors, especially weather and soil physical properties. If soil conditions, water and nitrogen availability are consistent within a field, the crop growth of the individual plants differs only in a small range. However, if these conditions vary within a field, it is assumed, that crop growth is strongly affected, causing a spatial variation of biomass, leaf area index (LAI), and yield (Hutchings et al., 2003, Hutchings and John, 2004, Johnen et al. 2014). Since biomass production as well as LAI and yield are directly influenced by assimilation, the fluxes of CO2 and water probably vary accordingly within the field. The effects of varying spatial conditions on crop growth are examined on different spatial scales. Several studies are considering either a global or a regional scale (e.g. Hu and Mo, 2011, Wassenaar et al., 1999), but there is also a large number of studies paying attention to spatial heterogeneity on field level (Diacono et al., 2012; Freckleton et al., 1999; Sudduth et al., 1997). As the mentioned studies showed, spatial heterogeneity within a field is not a scarce phenomenon but widespread. Nevertheless, the spatial variability of biomass and leaf area index of winter wheat and sugar beet and in particular their causes are not yet well examined. Regarding the understanding of soil heterogeneity and its effects on crop growth, crop growth models can help to detect causes leading to spatially varying canopies (Batchelor et al., 2002). However, currently available crop growth models are not programmed to reproduce spatial variability of crop growth within a field; in fact, these models are designed for homogeneous field conditions. Nevertheless, varying yield, for instance, has been examined in modeling studies for winter wheat, maize and soybean with the crop growth models CERES-Maize (Basso et al., 2001, Basso et al., 2007, Batchelor et al., 2002), CERES-Wheat (Duan, 2011), APSIM (Wong and Asseng, 2006), and CROPGRO-Soybean (Basso et al., 2001, Basso et al., 2007, Batchelor et al., 2002). The results showed that soil heterogeneity strongly affected yield patterns on field scale resulting from unequally distributed soil moisture, pests, and weeds. Sugar beet growth was examined under heterogeneous conditions with the models SUCROS (Launay and Guérif, 2003) and GreenLab (de Reffye et al., 2009; Richter et al., 2006). Based on these findings, our main question to be answered here is, which crop physiological processes are the driving mechanisms for heterogeneity of crop growth in sugar beet and winter wheat stands under field conditions. Therefore, our objectives are (I) to identify soil characteristics with EMI measurements and (II) to correlate the EMI measurement patterns with crop measurements (III) to estimate which crop growth processes are mainly influenced by varying soil characteristics.
Responsible Party
Creator:Anja Stadler (Author)
Publisher:CRC/TR32 Database (TR32DB)
Publication Year:2014
Topic
TR32 Topic:Vegetation
Related Subproject:B5
Subject:Keyword: PhD Report
File Details
Filename:Report_ModelingCropGrowthVariability.pdf
Data Type:Text - Text
File Size:269 KB
Date:Available: 07.06.2014
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
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Download Permission:Only Project Members
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Licence:[TR32DB] Data policy agreement
Geographic
Specific Information - Report
Report Date:8th of April, 2013
Report Type:PhD Report
Report City:Bonn, Germany
Report Institution:Institute of Crop Science and Resource Conservation, INRES, University Bonn
Number of Pages:5 (1 - 5)
Further Information:TR32 Student Report Phase II
Metadata Details
Metadata Creator:Anja Stadler
Metadata Created:23.06.2014
Metadata Last Updated:23.06.2014
Subproject:B5
Funding Phase:2
Metadata Language:English
Metadata Version:V50
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