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A likelihood framework for deterministic hydrological models and the importance of non-stationary autocorrelation
Ammann, L., Fenicia, F., & Reichert, P. (2019). A likelihood framework for deterministic hydrological models and the importance of non-stationary autocorrelation. Hydrology and Earth System Sciences, 23(4), 2147-2172. https://doi.org/10.5194/hess-23-2147-2019
From individual to joint species distribution models: a comparison of model complexity and predictive performance
Caradima, B., Schuwirth, N., & Reichert, P. (2019). From individual to joint species distribution models: a comparison of model complexity and predictive performance. Journal of Biogeography, 46(10), 2260-2274. https://doi.org/10.1111/jbi.13668
Advancing decision analysis methods for environmental management. Including stakeholder values in wastewater infrastructure planning and river assessment
Haag, F. (2019). Advancing decision analysis methods for environmental management. Including stakeholder values in wastewater infrastructure planning and river assessment (Doctoral dissertation). https://doi.org/10.3929/ethz-b-000378014
Identifying non-additive multi-attribute value functions based on uncertain indifference statements
Haag, F., Lienert, J., Schuwirth, N., & Reichert, P. (2019). Identifying non-additive multi-attribute value functions based on uncertain indifference statements. Omega: the international journal of management science, 85, 49-67. https://doi.org/10.1016/j.omega.2018.05.011
Integrating uncertainty of preferences and predictions in decision models: an application to regional wastewater planning
Haag, F., Reichert, P., Maurer, M., & Lienert, J. (2019). Integrating uncertainty of preferences and predictions in decision models: an application to regional wastewater planning. Journal of Environmental Management, 252, 109652 (16 pp.). https://doi.org/10.1016/j.jenvman.2019.109652
Ecological assessment of river networks: from reach to catchment scale
Kuemmerlen, M., Reichert, P., Siber, R., & Schuwirth, N. (2019). Ecological assessment of river networks: from reach to catchment scale. Science of the Total Environment, 650, 1613-1627. https://doi.org/10.1016/j.scitotenv.2018.09.019
Introducing the H2020 AQUACROSS project: knowledge, assessment, and management for AQUAtic biodiversity and ecosystem services aCROSS EU policies
Lago, M., Boteler, B., Rouillard, J., Abhold, K., Jähnig, S. C., Iglesias-Campos, A., … Hugh, M. D. (2019). Introducing the H2020 AQUACROSS project: knowledge, assessment, and management for AQUAtic biodiversity and ecosystem services aCROSS EU policies. Science of the Total Environment, 652, 320-329. https://doi.org/10.1016/j.scitotenv.2018.10.076
The need for unconventional value aggregation techniques: experiences from eliciting stakeholder preferences in environmental management
Reichert, P., Niederberger, K., Rey, P., Helg, U., & Haertel-Borer, S. (2019). The need for unconventional value aggregation techniques: experiences from eliciting stakeholder preferences in environmental management. EURO Journal on Decision Processes. https://doi.org/10.1007/s40070-019-00101-9
Signature-domain calibration of hydrological models using Approximate Bayesian Computation: empirical analysis of fundamental properties
Fenicia, F., Kavetski, D., Reichert, P., & Albert, C. (2018). Signature-domain calibration of hydrological models using Approximate Bayesian Computation: empirical analysis of fundamental properties. Water Resources Research, 54(6), 3958-3987. https://doi.org/10.1002/2017WR021616
Signature-domain calibration of hydrological models using Approximate Bayesian Computation: theory and comparison to existing applications
Kavetski, D., Fenicia, F., Reichert, P., & Albert, C. (2018). Signature-domain calibration of hydrological models using Approximate Bayesian Computation: theory and comparison to existing applications. Water Resources Research, 54(6), 4059-4083. https://doi.org/10.1002/2017WR020528
Methoden zur Untersuchung und Beurteilung der Fliessgewässer. Makrophyten - Stufe F (flächendeckend) und Stufe S (systembezogen). <em>Entwurf zur Vernehmlassung</em>
Känel, B., Michel, C., & Reichert, P. (2018). Methoden zur Untersuchung und Beurteilung der Fliessgewässer. Makrophyten - Stufe F (flächendeckend) und Stufe S (systembezogen). Entwurf zur Vernehmlassung. Umwelt-Vollzug. Bern: Bundesamt für Umwelt, BAFU.
Accelerating Bayesian inference in hydrological modeling with a mechanistic emulator
Machac, D., Reichert, P., Rieckermann, J., Del Giudice, D., & Albert, C. (2018). Accelerating Bayesian inference in hydrological modeling with a mechanistic emulator. Environmental Modelling and Software, 109, 66-79. https://doi.org/10.1016/j.envsoft.2018.07.016
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
Integrating and extending ecological river assessment: concept and test with two restoration projects
Paillex, A., Schuwirth, N., Lorenz, A. W., Januschke, K., Peter, A., & Reichert, P. (2017). Integrating and extending ecological river assessment: concept and test with two restoration projects. Ecological Indicators, 72, 131-141. https://doi.org/10.1016/j.ecolind.2016.07.048
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
Describing the catchment-averaged precipitation as a stochastic process improves parameter and input estimation
Del Giudice, D., Albert, C., Rieckermann, J., & Reichert, P. (2016). Describing the catchment-averaged precipitation as a stochastic process improves parameter and input estimation. Water Resources Research, 52(4), 3162-3186. https://doi.org/10.1002/2015WR017871
Modeling macroinvertebrate community dynamics in stream mesocosms contaminated with a pesticide
Kattwinkel, M., Reichert, P., Rüegg, J., Liess, M., & Schuwirth, N. (2016). Modeling macroinvertebrate community dynamics in stream mesocosms contaminated with a pesticide. Environmental Science and Technology, 50(6), 3165-3173. https://doi.org/10.1021/acs.est.5b04068
Emulation of dynamic simulators with application to hydrology
Machac, D., Reichert, P., & Albert, C. (2016). Emulation of dynamic simulators with application to hydrology. Journal of Computational Physics, 313(May), 352-366. https://doi.org/10.1016/j.jcp.2016.02.046
Fast mechanism-based emulator of a slow urban hydrodynamic drainage simulator
Machac, D., Reichert, P., Rieckermann, J., & Albert, C. (2016). Fast mechanism-based emulator of a slow urban hydrodynamic drainage simulator. Environmental Modelling and Software, 78, 54-67. https://doi.org/10.1016/j.envsoft.2015.12.007
Methoden zur Untersuchung und Beurteilung der Seen. <i>Modul: Ökomorphologie Seeufer</i>
Niederberger, K., Rey, P., Reichert, P., Schlosser, J., Helg, U., Haertel-Borer, S., & Binderheim, E. (2016). Methoden zur Untersuchung und Beurteilung der Seen. Modul: Ökomorphologie Seeufer. Umwelt-Vollzug: Vol. 1632. Bern: Bundesamt für Umwelt (BAFU).
 

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