| A comparison of machine learning and statistical species distribution models: Quantifying overfitting supports model interpretation
Chollet Ramampiandra, E., Scheidegger, A., Wydler, J., & Schuwirth, N. (2023). A comparison of machine learning and statistical species distribution models: Quantifying overfitting supports model interpretation. Ecological Modelling, 481, 110353 (11 pp.). https://doi.org/10.1016/j.ecolmodel.2023.110353 |
| Wastewater-based estimation of the effective reproductive number of SARS-CoV-2
Huisman, J. S., Scire, J., Caduff, L., Fernandez-Cassi, X., Ganesanandamoorthy, P., Kull, A., … Julian, T. R. (2022). Wastewater-based estimation of the effective reproductive number of SARS-CoV-2. Environmental Health Perspectives, 130(5), 057011 (12 pp.). https://doi.org/10.1289/EHP10050 |
| Improving hydrologic models for predictions and process understanding using neural ODEs
Höge, M., Scheidegger, A., Baity-Jesi, M., Albert, C., & Fenicia, F. (2022). Improving hydrologic models for predictions and process understanding using neural ODEs. Hydrology and Earth System Sciences, 26(19), 5085-5102. https://doi.org/10.5194/hess-26-5085-2022 |
| An exploration of Bayesian identification of dominant hydrological mechanisms in ungauged catchments
Prieto, C., Le Vine, N., Kavetski, D., Fenicia, F., Scheidegger, A., & Vitolo, C. (2022). An exploration of Bayesian identification of dominant hydrological mechanisms in ungauged catchments. Water Resources Research, 58(3), e2021WR030705 (28 pp.). https://doi.org/10.1029/2021WR030705 |
| Umwelteinflüsse auf häufige Fischgattungen. Auswertung von Fisch-Monitoring-Programmen
Schuwirth, N., Brodersen, J., Caradima, B., & Scheidegger, A. (2022). Umwelteinflüsse auf häufige Fischgattungen. Auswertung von Fisch-Monitoring-Programmen. Aqua & Gas, 102(6), 66-71. |
| Bayesian multi-level calibration of a process-based maize phenology model
Viswanathan, M., Scheidegger, A., Streck, T., Gayler, S., & Weber, T. K. D. (2022). Bayesian multi-level calibration of a process-based maize phenology model. Ecological Modelling, 474, 110154 (16 pp.). https://doi.org/10.1016/j.ecolmodel.2022.110154 |
| Bridging mechanistic conceptual models and statistical species distribution models of riverine fish
Caradima, B., Scheidegger, A., Brodersen, J., & Schuwirth, N. (2021). Bridging mechanistic conceptual models and statistical species distribution models of riverine fish. Ecological Modelling, 457, 109680 (15 pp.). https://doi.org/10.1016/j.ecolmodel.2021.109680 |
| Wastewater monitoring outperforms case numbers as a tool to track COVID-19 incidence dynamics when test positivity rates are high
Fernandez-Cassi, X., Scheidegger, A., Bänziger, C., Cariti, F., Tuñas Corzon, A., Ganesanandamoorthy, P., … Kohn, T. (2021). Wastewater monitoring outperforms case numbers as a tool to track COVID-19 incidence dynamics when test positivity rates are high. Water Research, 200, 117252 (9 pp.). https://doi.org/10.1016/j.watres.2021.117252 |
| Metabolomic profiling and toxicokinetics modeling to assess the effects of the pharmaceutical diclofenac in the aquatic invertebrate <em>Hyalella azteca</em>
Fu, Q., Scheidegger, A., Laczko, E., & Hollender, J. (2021). Metabolomic profiling and toxicokinetics modeling to assess the effects of the pharmaceutical diclofenac in the aquatic invertebrate Hyalella azteca. Environmental Science and Technology, 55(12), 7920-7929. https://doi.org/10.1021/acs.est.0c07887 |
| A framework for untangling transient groundwater mixing and travel times
Popp, A. L., Pardo-Álvarez, Á., Schilling, O. S., Scheidegger, A., Musy, S., Peel, M., … Kipfer, R. (2021). A framework for untangling transient groundwater mixing and travel times. Water Resources Research, 57(4), e2020WR028362 (16 pp.). https://doi.org/10.1029/2020WR028362 |
| Evaluation of an in vitro assay to screen for the immunotoxic potential of chemicals to fish
Rehberger, K., Escher, B. I., Scheidegger, A., Werner, I., & Segner, H. (2021). Evaluation of an in vitro assay to screen for the immunotoxic potential of chemicals to fish. Scientific Reports, 11(1), 3167 (16 pp.). https://doi.org/10.1038/s41598-021-82711-5 |
| Ex-ante quantification of nutrient, total solids, and water flows in sanitation systems
Spuhler, D., Scheidegger, A., & Maurer, M. (2021). Ex-ante quantification of nutrient, total solids, and water flows in sanitation systems. Journal of Environmental Management, 280, 111785 (17 pp.). https://doi.org/10.1016/j.jenvman.2020.111785 |
| Estimating quantities and qualities (Q&Q) of faecal sludge at community to city‐wide scales
Strande, L., Englund, M., Andriessen, N., Carbajal, J. P., & Scheidegger, A. (2021). Estimating quantities and qualities (Q&Q) of faecal sludge at community to city‐wide scales. In K. Velkushanova, L. Strande, M. Ronteltap, T. Koottatep, D. Brdjanovic, & C. Buckley (Eds.), Methods for faecal sludge analysis (pp. 115-144). IWA Publishing. |
| Predictive models using "cheap and easy" field measurements: can they fill a gap in planning, monitoring, and implementing fecal sludge management solutions?
Ward, B. J., Andriessen, N., Tembo, J. M., Kabika, J., Grau, M., Scheidegger, A., … Strande, L. (2021). Predictive models using "cheap and easy" field measurements: can they fill a gap in planning, monitoring, and implementing fecal sludge management solutions? Water Research, 196, 116997 (12 pp.). https://doi.org/10.1016/j.watres.2021.116997 |
| Estimating black soldier fly larvae biowaste conversion performance by simulation of midgut digestion
Gold, M., Egger, J., Scheidegger, A., Zurbrügg, C., Bruno, D., Bonelli, M., … Mathys, A. (2020). Estimating black soldier fly larvae biowaste conversion performance by simulation of midgut digestion. Waste Management, 112, 40-51. https://doi.org/10.1016/j.wasman.2020.05.026 |
| Modeling the water-energy nexus in households
Hadengue, B., Scheidegger, A., Morgenroth, E., & Larsen, T. A. (2020). Modeling the water-energy nexus in households. Energy and Buildings, 225, 110262 (10 pp.). https://doi.org/10.1016/j.enbuild.2020.110262 |
| Comparative analysis of sanitation systems for resource recovery: influence of configurations and single technology components
Spuhler, D., Scheidegger, A., & Maurer, M. (2020). Comparative analysis of sanitation systems for resource recovery: influence of configurations and single technology components. Water Research, 186, 116281 (18 pp.). https://doi.org/10.1016/j.watres.2020.116281 |
| Synchrotron hard X-ray chemical imaging of trace element speciation in heterogeneous samples: development of criteria for uncertainty analysis
Wielinski, J., Marafatto, F. F., Gogos, A., Scheidegger, A., Voegelin, A., Müller, C. R., … Kaegi, R. (2020). Synchrotron hard X-ray chemical imaging of trace element speciation in heterogeneous samples: development of criteria for uncertainty analysis. Journal of Analytical Atomic Spectrometry, 35, 567-579. https://doi.org/10.1039/C9JA00394K |
| How urban storm- and wastewater management prepares for emerging opportunities and threats: digital transformation, ubiquitous sensing, new data sources, and beyond – a horizon scan
Blumensaat, F., Leitão, J. P., Ort, C., Rieckermann, J., Scheidegger, A., Vanrolleghem, P. A., & Villez, K. (2019). How urban storm- and wastewater management prepares for emerging opportunities and threats: digital transformation, ubiquitous sensing, new data sources, and beyond – a horizon scan. Environmental Science and Technology, 53(15), 8488-8498. https://doi.org/10.1021/acs.est.8b06481 |
| Impact of different sources of precipitation data on urban rainfall-runoff predictions: a comparison of rain gauges, commercial microwave links and radar
Disch, A., Scheidegger, A., Wani, O., & Rieckermann, J. (2019). Impact of different sources of precipitation data on urban rainfall-runoff predictions: a comparison of rain gauges, commercial microwave links and radar. In N. Peleg & P. Molnar (Eds.), Rainfall monitoring, modelling and forecasting in urban environments. Conference Proceedings UrbanRain18 (pp. 27-32). ETH Zurich. |
