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  • (-) Eawag Departments = Systems Analysis, Integrated Assessment and Modelling SIAM
  • (-) Eawag Authors = Reichert, Peter
  • (-) Keywords = Bayesian inference
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A comparison of numerical approaches for statistical inference with stochastic models
Bacci, M., Sukys, J., Reichert, P., Ulzega, S., & Albert, C. (2023). A comparison of numerical approaches for statistical inference with stochastic models. Stochastic Environmental Research and Risk Assessment, 37(8), 3041-3061. https://doi.org/10.1007/s00477-023-02434-z
Reducing sample size requirements by extending discrete choice experiments to indifference elicitation
Sriwastava, A., & Reichert, P. (2023). Reducing sample size requirements by extending discrete choice experiments to indifference elicitation. Journal of Choice Modelling, 48, 100426 (18 pp.). https://doi.org/10.1016/j.jocm.2023.100426
Application of stochastic time dependent parameters to improve the characterization of uncertainty in conceptual hydrological models
Bacci, M., Dal Molin, M., Fenicia, F., Reichert, P., & Šukys, J. (2022). Application of stochastic time dependent parameters to improve the characterization of uncertainty in conceptual hydrological models. Journal of Hydrology, 612, 128057 (19 pp.). https://doi.org/10.1016/j.jhydrol.2022.128057
Investigating the effect of pesticides on Daphnia population dynamics by inferring structure and parameters of a stochastic model
Palamara, G. M., Dennis, S. R., Haenggi, C., Schuwirth, N., & Reichert, P. (2022). Investigating the effect of pesticides on Daphnia population dynamics by inferring structure and parameters of a stochastic model. Ecological Modelling, 472, 110076 (13 pp.). https://doi.org/10.1016/j.ecolmodel.2022.110076
Confronting existing knowledge on ecological preferences of stream macroinvertebrates with independent monitoring data using a Bayesian multi-species distribution model
Vermeiren, P., Reichert, P., Graf, W., Leitner, P., Schmidt-Kloiber, A., & Schuwirth, N. (2021). Confronting existing knowledge on ecological preferences of stream macroinvertebrates with independent monitoring data using a Bayesian multi-species distribution model. Freshwater Science, 40(1), 202-220. https://doi.org/10.1086/713175
Characterizing fast herbicide transport in a small agricultural catchment with conceptual models
Ammann, L., Doppler, T., Stamm, C., Reichert, P., & Fenicia, F. (2020). Characterizing fast herbicide transport in a small agricultural catchment with conceptual models. Journal of Hydrology, 586, 124812 (15 pp.). https://doi.org/10.1016/j.jhydrol.2020.124812
Towards a comprehensive uncertainty assessment in environmental research and decision support
Reichert, P. (2020). Towards a comprehensive uncertainty assessment in environmental research and decision support. Water Science and Technology, 81(8), 1588-1596. https://doi.org/10.2166/wst.2020.032
Integrating uncertain prior knowledge regarding ecological preferences into multi-species distribution models: effects of model complexity on predictive performance
Vermeiren, P., Reichert, P., & Schuwirth, N. (2020). Integrating uncertain prior knowledge regarding ecological preferences into multi-species distribution models: effects of model complexity on predictive performance. Ecological Modelling, 420, 108956 (15 pp.). https://doi.org/10.1016/j.ecolmodel.2020.108956
Bayesian parameter inference for individual-based models using a Particle Markov Chain Monte Carlo method
Kattwinkel, M., & Reichert, P. (2017). Bayesian parameter inference for individual-based models using a Particle Markov Chain Monte Carlo method. Environmental Modelling and Software, 87, 110-119. https://doi.org/10.1016/j.envsoft.2016.11.001
Mechanistic modelling for predicting the effects of restoration, invasion and pollution on benthic macroinvertebrate communities in rivers
Paillex, A., Reichert, P., Lorenz, A. W., & Schuwirth, N. (2017). Mechanistic modelling for predicting the effects of restoration, invasion and pollution on benthic macroinvertebrate communities in rivers. Freshwater Biology, 62(6), 1083-1093. https://doi.org/10.1111/fwb.12927
The effect of ambiguous prior knowledge on Bayesian model parameter inference and prediction
Rinderknecht, S. L., Albert, C., Borsuk, M. E., Schuwirth, N., Künsch, H. R., & Reichert, P. (2014). The effect of ambiguous prior knowledge on Bayesian model parameter inference and prediction. Environmental Modelling and Software, 62, 300-315. https://doi.org/10.1016/j.envsoft.2014.08.020
Sewer deterioration modeling with condition data lacking historical records
Egger, C., Scheidegger, A., Reichert, P., & Maurer, M. (2013). Sewer deterioration modeling with condition data lacking historical records. Water Research, 47(17), 6762-6779. https://doi.org/10.1016/j.watres.2013.09.010
Combining expert knowledge and local data for improved service life modeling of water supply networks
Scholten, L., Scheidegger, A., Reichert, P., & Maurer, M. (2013). Combining expert knowledge and local data for improved service life modeling of water supply networks. Environmental Modelling and Software, 42, 1-16. https://doi.org/10.1016/j.envsoft.2012.11.013
Bridging the gap between theoretical ecology and real ecosystems: modeling invertebrate community composition in streams
Schuwirth, N., & Reichert, P. (2013). Bridging the gap between theoretical ecology and real ecosystems: modeling invertebrate community composition in streams. Ecology, 94(2), 368-379. https://doi.org/10.1890/12-0591.1
Development of a mechanistic model (ERIMO-I) for analyzing the temporal dynamics of the benthic community of an intermittent Mediterranean stream
Schuwirth, N., Acuña, V., & Reichert, P. (2011). Development of a mechanistic model (ERIMO-I) for analyzing the temporal dynamics of the benthic community of an intermittent Mediterranean stream. Ecological Modelling, 222(1), 91-104. https://doi.org/10.1016/j.ecolmodel.2010.09.013
A mechanistic model of benthos community dynamics in the River Sihl, Switzerland
Schuwirth, N., Kühni, M., Schweizer, S., Uehlinger, U., & Reichert, P. (2008). A mechanistic model of benthos community dynamics in the River Sihl, Switzerland. Freshwater Biology, 53(7), 1372-1392. https://doi.org/10.1111/j.1365-2427.2008.01970.x
Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China
Yang, J., Reichert, P., Abbaspour, K. C., Xia, J., & Yang, H. (2008). Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China. Journal of Hydrology, 358(1–2), 1-23. https://doi.org/10.1016/j.jhydrol.2008.05.012
Hydrological modelling of the chaohe basin in china: statistical model formulation and Bayesian inference
Yang, J., Reichert, P., Abbaspour, K. C., & Yang, H. (2007). Hydrological modelling of the chaohe basin in china: statistical model formulation and Bayesian inference. Journal of Hydrology, 340(3-4), 167-182. https://doi.org/10.1016/j.jhydrol.2007.04.006