TR32-Database: Database of Transregio 32

[1483] - Use of geophysical data to improve conceptualization and parameterization in soil-vegetation-atmosphere models

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Features
Citation
Brogi, C., 2016. Use of geophysical data to improve conceptualization and parameterization in soil-vegetation-atmosphere models. PhD Report, Forshungszentrum Jülich IBG-3, Jülich. Accessed from http://www.tr32db.uni-koeln.de/data.php?dataID=1483 at 2017-06-25.
Identification
Title(s):Main Title: Use of geophysical data to improve conceptualization and parameterization in soil-vegetation-atmosphere models
Subtitle: PhD Report n.01
Description(s):Abstract: In the last decades the use of geophysics has developed as fast as the technology associated to the measurement techniques. Geophysics has demonstrated an increasing efficiency of data collection methodologies combined with a better reliability of the quantitative data collected. Nevertheless, the non-invasive nature of this technology still plays the main role when looking at the feasibility of contexts where a direct geognostic survey is not adequate or feasible. Despite this promising potential, the use of hydrogeophysics in large scale study is increasing slowly (Vereecken et al. 2015). At any rate, the potential of hydrogeophysics at the catchment scale has been widely recognized (Robinson et al. 2008). Looking at larger scale, techniques like electromagnetic induction (EMI) have shown a great potential for soil hydrologists (Vereecken et al. 2015). New generation EMI measurements are showing their wide potential thanks to the possibility to obtain quantitative information regarding the dominant features of the subsurface up to the depth of 2 m (von Hebel et al. 2014). Moreover, the technique is proven to be fast, non-invasive and feasible for areas up to several hectares. Also, the interaction between the subsurface and the vegetation can now be investigated more effectively. In the recent study, apparent electrical conductivity measured with EMI sensors has been used to investigate the origin of observed leaf area index (LAI) patterns in crop performance. Thanks to a moderate to excellent spatial consistency of LAI and ECa patterns, subsoil water content and water storage capacity have been related to the improved crop performance during water stress periods (Rudolph et al. 2015). It is now possible to collect a large amount of data with a reasonable degree of accuracy and in a large area. Those measurements can be used as input data for selected model platforms where the subsurface parameterization is playing an active role. The main purpose of my project is to investigate the influence of the subsurface structure, represented by layering and texture, in soil water content and in soil-vegetation-atmosphere interactions at the field-scale. Data collected with different geophysical devices will be fused to develop a high spatial resolution model of the subsurface out of which I will be able to define soil properties and layering for an extended area. This subsurface model will be used as input data in three different soil-vegetation-atmosphere model platforms to improve the output of models. Reliability of the subsurface model will be tested to evaluate the importance of an accurate representation of the subsurface structure. The added value of geophysical surveying methods as a source of data will be evaluated as well. Time lapse geophysical data are successfully merged with models using coupled inversion strategies. Such coupled inversion frameworks have been developed for ERT (Huisman et al. 2012) and GPR (Busch et al. 2013). Despite availability of this methodology, it is not used in this project as a main source of data. Indeed, time-lapse measurements with a good temporal resolution are not always available and feasible at larger scale (B6 Research Plan 2015). Considering the extent of the study area it is necessary to rely on different geophysical methodologies (e.g. EMI measurements). EMI data can be used to develop a subsurface model and provide a valuable contribution to model-data fusion. This project consists of three phases dealing with model-data fusion for point-, field- and catchment-scale models which are already used in other sub-projects within the TR32.
Responsible Party
Creator(s):Author: Cosimo Brogi
Publisher:CRC/TR32 Database (TR32DB)
Topic
TR32 Topic:Other
Related Sub-project(s):B6
Subject(s):CRC/TR32 Keywords: Geophysics, PhD Report, EMI, Vegetation-Hyrology interactions, Geomorphology
File Details
File Name:C_Brogi_PhD_Report_n1.pdf
Data Type:Text
File Size:1413 kB (1.38 MB)
Date(s):Available: 2016-05-02
Mime Type:application/pdf
Language:English
Status:Completed
Constraints
Download Permission:OnlyTR32
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Geographic
North:50.8723265
East:6.4577801
South:50.8614925
West:6.4406139
Measurement Region:Ellebach
Measurement Location:Selhausen
Specific Informations - Report
Report Date:2nd of May, 2016
Report Type:PhD Report
Report City:Jülich
Report Institution:Forshungszentrum Jülich IBG-3
Metadata Details
Metadata Creator:Cosimo Brogi
Metadata Created:2017-02-07
Metadata Last Updated:2017-02-07
Subproject:B6
Funding Phase:3
Metadata Language:English
Metadata Version:V41
Dataset Metrics
Page Visits:73
Metadata Downloads:0
Dataset Downloads:1
Dataset Activity
Features