| 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 |
| Quantifying the uncertainty of a conceptual herbicide transport model with time‐dependent, stochastic parameters
Ammann, L., Stamm, C., Fenicia, F., & Reichert, P. (2021). Quantifying the uncertainty of a conceptual herbicide transport model with time‐dependent, stochastic parameters. Water Resources Research, 57(8), e2020WR028311 (27 pp.). https://doi.org/10.1029/2020WR028311 |
| Potential and challenges of investigating intrinsic uncertainty of hydrological models with stochastic, time‐dependent parameters
Reichert, P., Ammann, L., & Fenicia, F. (2021). Potential and challenges of investigating intrinsic uncertainty of hydrological models with stochastic, time‐dependent parameters. Water Resources Research, 57(3), e2020WR028400 (28 pp.). https://doi.org/10.1029/2020WR028400 |
| 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 |
| Effects of site selection and taxonomic resolution on the inference of stream invertebrate responses to environmental conditions
Caradima, B., Reichert, P., & Schuwirth, N. (2020). Effects of site selection and taxonomic resolution on the inference of stream invertebrate responses to environmental conditions. Freshwater Science, 39(3), 415-432. https://doi.org/10.1086/709024 |
| 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 |
| 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, ETH Zurich]. 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 |
| Lake models
Reichert, P., & Mieleitner, J. (2019). Lake models. In B. Fath (Ed.), Vol. 2. Encyclopedia of ecology. Reference module in earth systems and environmental sciences (pp. 116-128). https://doi.org/10.1016/B978-0-12-409548-9.11155-8 |
| 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, 7(3-4), 197-219. 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 |
