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Exploring a copula-based alternative to additive error models—for non-negative and autocorrelated time series in hydrology
Wani, O., Scheidegger, A., Cecinati, F., Espadas, G., & Rieckermann, J. (2019). Exploring a copula-based alternative to additive error models—for non-negative and autocorrelated time series in hydrology. Journal of Hydrology, 575, 1031-1040. https://doi.org/10.1016/j.jhydrol.2019.06.006
SPUX: scalable particle Markov Chain Monte Carlo for uncertainty quantification in stochastic ecological models
Šukys, J., & Kattwinkel, M. (2018). SPUX: scalable particle Markov Chain Monte Carlo for uncertainty quantification in stochastic ecological models. In S. Bassini, M. Danelutto, P. Dazzi, G. R. Joubert, & F. Peters (Eds.), Advances in parallel computing: Vol. 32. Parallel computing is everywhere (pp. 159-168). https://doi.org/10.3233/978-1-61499-843-3-159
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 ecological theories and traits in process-based modeling of macroinvertebrate community dynamics in streams
Mondy, C. P., & Schuwirth, N. (2017). Integrating ecological theories and traits in process-based modeling of macroinvertebrate community dynamics in streams. Ecological Applications, 27(4), 1365-1377. https://doi.org/10.1002/eap.1530
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