Peter Reichert: Research Fields

Systems Analysis Methodology

Development of techniques for statistical inference of model states and parameters that account for the need of using prior information and of considering input and model structure uncertainty and intrinsic stochasticity.

5 key contributions to this field:

• Reichert, P., Ammann, L. and Fenicia, F. Potential and Challenges of Investigating Intrinsic Uncertainty of Hydrological Models with Stochastic, Time-Dependent Parameters. Water Resources Research in press, 2021. doi:10.1029/2020WR028400
  
• Kattwinkel, M. and Reichert, P. Bayesian parameter inference for Individual-Based Models using Particle Markov Chain Monte Carlo (PMCMC). Environmental Modelling & Software 87, 110-119, 2017. doi:10.1016/j.envsoft.2016.11.001
  
• Reichert, P. and Schuwirth, N. Linking statistical description of bias to multi-objective model calibration. Water Resources Research, 48, W09543, 2012. doi:10.1029/2011WR011391 (open access)
  
• Rinderknecht, S. L., Borsuk, M. E. and Reichert, P. Bridging Uncertain and Ambiguous Knowledge with Imprecise Probabilities. Environmental Modelling & Software 36, 122-130, 2012. doi:10.1016/j.envsoft.2011.07.022
  
• Rinderknecht, S.L., Borsuk, M.E. and Reichert, P. Eliciting Density Ratio Classes. International Journal of Approximate Reasoning 52, 792-804, 2011. doi:10.1016/j.ijar.2011.02.002 (open access)
  

External Links:

• International Society for Bayesian Analysis
• Society for Imprecise Probability: Theories and Applications
• The R Project for Statistical Computing
• The Julia Programming Language

Hydrological, Biogeochemical and Ecological Modelling

Development and application of hydrological, biogeochemical and ecological models of river and lake systems to quantitatively describe scientific knowledge and predict effects of changes in driving forces and of management measures.

5 key contributions to this field:

• Schuwirth, N. and Reichert, P. Bridging the gap between theoretical ecology and real ecosystems: modeling invertebrate community composition in streams. Ecology 94(2), 368-379, 2013. doi:10.1890/12-0591.1
  
• Reichert, P. and Schuwirth, N. A generic framework for deriving process stoichiometry in environmental models. Environmental Modelling & Software, 25, 1241-1251, 2010. doi:10.1016/j.envsoft.2010.03.002
  
• Reichert, P., Uehlinger, U. and Acuña V. Estimating stream metabolism from oxygen concentrations: The effect of spatial heterogeneity. Journal of Geophysical Research 114, G03016, 2009. doi:10.1029/2008JG000917 (open access)
      R-scripts: calc_np_luteren.r, calc_np.r, smooth.r
      Data: calc_np_luteren_o2.dat, calc_np_luteren_par.dat
• Reichert, P., Borchardt, D., Henze, M., Rauch, W., Shanahan, P., Somlyódy, L. and Vanrolleghem, P. River Water Quality Model no. 1 (RWQM1): II. Biochemical process equations. Water Sci. Tech. 43(5), 11-30, 2001. http://wst.iwaponline.com/content/43/5/11 (open access)
  
• Omlin, M., Reichert, P. and Forster, R. Biogeochemical model of lake Zürich: Model equations and results. Ecological Modelling 141(1-3), 77-103, 2001. doi:10.1016/S0304-3800(01)00256-3

External Links:

• Freshwater Information Platform
• Computational Ecology

Environmental Decision Support

Design and apply decision analytical procedures to quantify societal preferences and apply them jointly with scientific predictions of outcomes of management alternatives in environmental decision support.

5 key contributions to this field:

• Reichert, P. Towards a comprehensive uncertainty assessment in environmental research and decision support. Water Science and Technology 81(8), 1588–1596, 2020. doi:10.2166/wst.2020.032
  
• Kuemmerlen, M., Reichert, P., Siber, R. and Schuwirth, N. Ecological assessment of river networks: From reach to catchment scale. Science of the Total Environment 650, 1613-1627, 2019. doi:10.1016/j.scitotenv.2018.09.019
  
• Haag, F., Lienert, J., Schuwirth, N. and Reichert, P. Identifying non-additive multi-attribute value functions based on uncertain indifference statements. Omega 95, 49-67, 2019. doi:10.1016/j.omega.2018.05.011
  
• Reichert, P., Langhans, S., Lienert, J. and Schuwirth, N. The Conceptual Foundation of Environmental Decision Support. Journal of Environmental Management 154, 316-332, 2015. doi:10.1016/j.jenvman.2015.01.053 (open access)
  
• Reichert, P. and Borsuk, M.E. Does high forecast uncertainty preclude effective decision support? Environmental Modelling and Software 20(8), 991-1001, 2005. doi:10.1016/j.envsoft.2004.10.005
  

External Links:

• Decision Analysis Society