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Sabine Seidel, Dr.

Wissenschaftlicher Mitarbeiter

E-Mail: [Email protection active, please enable JavaScript.]Sabine Seidel
Telefon: +49 (0)228 73 2876
Fax: +49 (0)228 73 2870
Raum: 2.013


CV

since May 2020 Junior Research Group leader (topic: Optimizing crop mixtures for a sustainable and climate-resilient crop production by combining field experiments and crop models) within CP5 of the Excellence Cluster PhenoRob (http://www.phenorob.de/cp-5-new-field-arrangements/)
since 2016 Postdoctorial Scientist at the Institute of Crop Science and Resource Conservation, Crop Science Group, University of Bonn, Germany
2012 – 2015 Postdoctorial Scientist at the Chair of Hydrology, Technische Universität Dresden, Germany
Jan – March 2015 Research stay at the Wyler Department for Dryland Agriculture, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University, Israel
2012 – 2014 Employed in the EU project ”SAPHIR - Saxonian Platform for high Performance Irrigation”, report at http://tu-dresden.de/uw/was/hydrologie/forschung/Projekte/saphir
2012 Parental leave (6 months)
Title of qualification awarded 2012: Ph.D. "Optimal simulation based design of deficit irrigation experiments", final grade: 1.2 (magna cum laude). The dissertation is online available (see below).
March – May 2009 Research stay at CEMAGREF (now IRSTEA) in Montpellier, France since 2008 Scientist at the Chair of Hydrology, Technische Universität Dresden, Germany
Title of qualification awarded 2008: Diploma Diplomagraringenieur, main field of study: Plant Sciences
2007 Semester abroad at the Private University of Antenor Orrego (UPAO, Trujillo, Peru)
2005 Guest student at the University of San José (USJ, San José, Costa Rica)
2003 – 2008 Study of Agricultural Science at the Technische Universität München, Germany


Research interests

•    Modeling the water dynamics from the soil through the plant and stomata into the atmosphere
•    Optimization of crop irrigation under consideration of uncertainties (rainfall, soil)
•    Multi-criterial optimization of irrigation and fertilization for a sustainable and resource efficient crop production
•    Multi-criterial optimization of model parameters based on experimental data
•    Impact of drought and heat stress on crops in different phenological stages
•    Evaluation and improvement of current crop models to better simulate the effects of drought and heat stress on plant growth and development
•    Regionalization of yield and crop water demand predictions based on mechanistic crop growth model simulations
•    How to aground science? From complex modeling approaches to decision support tools for farmers and policy makers


Selected publications

Peer Reviewed Journal Articles:

Seidel, S.J., Gaiser, T., Kautz, T., Bauke, S.L., Amelung, W., Barfus, K., Ewert, F. and Athmann, M. Estimation of the impact of precrops and climate variability on soil depth-differentiated spring wheat growth and water, nitrogen and phosphorus uptake. Soil and Tillage Research. 2019, 195, 104427. doi: 10.1016/j.still.2019.104427
Kumar, A., Shahbaz, M., Koirala, M., Blagodatskaya, E., Seidel, S.J., Kuzyakov, Y. and Pausch, J. Root trait plasticity and plant nutrient acquisition in phosphorus limited soil. J. Plant Nutr. Soil Sci. 2019. doi: 10.1002/jpln.201900322
Koch, M., Guppy, Ch., Amelung, W., Gypser, S., Bol, R., Seidel, S., Siebers, N. Insights into 33phosphorus utilization from Fe- and Al-hydroxides in Luvisol and Ferralsol subsoils. Soil Research 57(5) 447-458. 2019. doi: 10.1071/SR18223
Seidel, S. J., Barfus, K., Gaiser, T., Nguyen, T. H. and Lazarovitch, N. The influence of climate variability, soil conditions and sowing date on simulation-based crop coefficient curves and irrigation water demand. Agricultural Water Management 221:73-83, 2019. doi: 10.1016/j.agwat.2019.02.007
Maharjana, G. R., Prescher, A.-K., Nendel, C., Ewert, F., Mboh, C. M., Gaiser, T. and Seidel, S. J. Approaches to model the impact of tillage implements on soil physical and nutrient properties in different agro-ecosystem models. Soil and Tillage Research 180:210-221, 2018. doi: 10.1016/j.still.2018.03.009
Seidel, S. J., Palosuo, T., Thorburn, P. and D. Wallach. Towards improved calibration of crop models – where are we now and where should we go? European Journal of Agronomy 94:25-35, 2018. doi: 10.1016/j.eja.2018.01.006
A. Hartmann, J. Simunek, M. Kwame Aidoo, S. J. Seidel and N. Lazarovitch. Implementation and Application of a Root Growth Module in HYDRUS. Vadose Zone Journal, 2017. doi: 10.2136/vzj2017.02.0040
Schneider, F. , A. Don, I. Hennings, O. Schmittmann, S. J. Seidel, 2017. The effect of deep tillage on crop yield – What do we really know? Soil and Tillage Research 174:193-204. Doi: 10.1016/j.still.2017.07.005
Seidel, S. J. , S. Werisch, N. Schütze, and H. Laber. Impact of irrigation on plant growth and development of white cabbage. Agricultural Water Management 187:99–111. Doi: 10.1016/j.agwat.2017.03.011.
Seidel, S. J. , S. Rachmilevitch, N. Schütze and N. Lazarovitch, 2016. Modelling the impact of drought and heat stress on common bean with two different photosynthesis model approaches. Environmental Modelling & Software 81:111-121. Doi: 10.1016/j.envsoft.2016.04.001.
Seidel, S. J. , S. Werisch, K. Barfus, M. Wagner, N. Schütze, and H. Laber, 2016. Field evaluation of irrigation scheduling strategies using a mechanistic crop growth model. Irrigation and Drainage. 65(2):214-223. Doi: 10.1002/ird.1942.
Wagner, M. , S. J. Seidel, S. Werisch, K. Barfuss and N. Schütze. Integrierte Modellierung von Wasserdargebot und Wassernachfrage am Beispiel der Bew\”asserungslandwirtschaft in Sachsen. Hydrologie und Wasserbewirtschaftung. 1(60):22-37. Doi: 10.5675/HyWa\_2016,1\_2.
S. J. Seidel, S. Rachmilevitch, N. Schütze and N. Lazarovitch. Modelling the impact of drought and heat stress on common bean with two different photosynthesis model approaches. Environmental Modelling & Software   81:111-121, 2016. doi: 10.1016/j.envsoft.2016.04.001.
S. J. Seidel, S. Werisch, K. Barfus, M. Wagner, N. Schütze, and H. Laber. Field evaluation of irrigation scheduling strategies using a mechanistic crop growth model. Irrigation and Drainage. 65(2):214-223, 2016.doi: 10.1002/ird.1942.
M. Wagner, S. J. Seidel, S. Werisch, K. Barfuss and N. Schütze. Integrierte Modellierung von Wasserdargebot und Wassernachfrage am Beispiel der Bewässerungslandwirtschaft in Sachsen. Hydrologie und Wasserbewirtschaftung. 1(60):22-37, 2016. doi: 10.5675/HyWa_2016,1_2.
M. Wagner, S. J. Seidel and N. Schütze. Irrigation water demand of common bean on field and regional scale under varying climatic conditions. Meteorologische Zeitschrift, 2015. doi: 10.1127/metz/2014/0698.
S. J. Seidel, N. Schütze, M. Fahle, J.-C. Mailhol, and P. Ruelle. Optimal irrigation scheduling, irrigation control and drip line layout to increase water productivity and profit in subsurface drip irrigated agriculture. Irrigation and Drainage, 64:501-518, 2015. doi: 10.1002/ird.1926.
S. Kloss, J. Grundmann, S. J. Seidel, S. Werisch, J. Trümmer, U. Schmidhalter, and N. Schütze. Investigation of deficit irrigation strategies combining SVAT-modeling, optimization and experiments. Environmental Earth Sciences, 72(12):1866-6280, 2014. doi: 10.1007/s12665-014-3463-7.
S. Walser, N. Schütze, M. Guderle, S. Liske, and U. Schmidhalter. Evaluation of the transferability of a SVAT model? Results from field and greenhouse applications. Irrigation and Drainage, 60(S1):59-70, 2011. doi: 10.1002/ird.669.
J.C. Mailhol, P. Ruelle, S. Walser, N. Schütze, and C. Dejean. Analysis of AET and yield predictions under surface and buried drip irrigation systems using the Crop Model PILOTE and Hydrus-2D. Agricultural Water Management, 98(6):1033-1044, 2011. doi: 10.1016/j.agwat.2011.01.014.
PhD Thesis: S. J. Seidel. Optimal simulation based design of deficit irrigation experiments. PhD thesis, Dresdner Schriften zur Hydrologie Heft 12, Technische Universität Dresden,
2012. avaiable at: http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-100254


Current projects


Junior Research Group leader

"Optimizing crop mixtures for a sustainable and climate-resilient crop production by combining field experiments and crop models"

Crop mixtures offer multiple advantages over traditional sole crops, including production of greater yield on a given piece of land, complementary resource use in time and space among different species; reduction of production risk due to complementarity; improved weed suppression; increased N availability for the subsequent crop due to legumes; decreased nitrate leaching by non-legume cover crops; improved soil fertility, soil organic matter content, and carbon sequestration; increased biodiversity, and maintainance and regeneration of ecosystem services. The numerous processes and mechanisms involved in crop mixtures highlight the need to deal with their complexity by combining concepts from diverse disciplines (agronomy, physiology and ecology) and demand for further information on crop species combination, arrangements and proportion as factors that affect mixtures.

Crop simulation models are widely recognized as useful tools that examine cause and effect relationships in crop production. Moreover, they can be used to study the influence of climate variability, soil, or management options, and for real-time simulation based crop management. Today, only a handful of models simulate mixed cropping systems. In several studies, yield and water use, light distribution, nitrogen transport and uptake, or weed supression in mixtures were modeled. Given the complexity of mixed cropping systems, crop models can be especially helpful for testing hypotheses about the key factors driving competition and compensatory growth between species. Hereby, competition for soil water and nutrients and for light play a key role. The authors of a recent review on modeling annual crop mixtures state that modeling of crop mixtures is in its infancy. The competition for below-ground resources taken up by roots is not represented, which remains a main weakness. The majority of the models still ignore spatial heterogeneity of plant mixtures and streamline the system into a single dimension. Although existing models can simulate interactions, the degree of precision is questionable because of the general poor understanding of system dynamics within mixed cropping systems. According to the authors, mathematical equations within modeling of mixtures should be developed alongside theories.

The overall objectives of the Research Group are to i) obtain data using classical and new methods and technologies to gain insights into interactions and mechanisms in crop mixtures, ii) develop new and advanced crop models for crop mixtures, iii) determine optimal field arrangements (e.g. species combination, arrangements and proportion) and management (e.g. sowing, fertilization, harvest) in mixtures for a sustainable and climate-resilient crop production by combining highly monitored experiments and models.

BonaRes (BMBF)

For a more complete listing of my publications and research activities, please visit my personal website:
http://www.sabine-seidel.de/


 

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