Dario Del Giudice

SmitomB/Internal_Phosphorus_Loading_Model: Characterizing and Projecting Internal Phosphorus Loading through Bayesian Mass-balance Modeling. (2023, December 23). Zenodo. https://doi.org/10.5281/zenodo.10428197

SmitomB/Internal_Phosphorus_Loading_Model: Characterizing and Projecting Internal Phosphorus Loading through Bayesian Mass-balance Modeling. (2023, December 23). Zenodo. https://doi.org/10.5281/zenodo.10428198

Katin, A., Del Giudice, D., & Obenour, D. R. (2022). Temporally resolved coastal hypoxia forecasting and uncertainty assessment via Bayesian mechanistic modeling. HYDROLOGY AND EARTH SYSTEM SCIENCES, 26(4), 1131–1143. https://doi.org/10.5194/hess-26-1131-2022

Del Giudice, D., Fang, S., Scavia, D., Davis, T. W., Evans, M. A., & Obenour, D. R. (2021). Elucidating controls on cyanobacteria bloom timing and intensity via Bayesian mechanistic modeling. SCIENCE OF THE TOTAL ENVIRONMENT, 755. https://doi.org/10.1016/j.scitotenv.2020.142487

Han, Y., Aziz, T. N., Del Giudice, D., Hall, N. S., & Obenour, D. R. (2021). Exploring nutrient and light limitation of algal production in a shallow turbid reservoir. ENVIRONMENTAL POLLUTION, 269. https://doi.org/10.1016/j.envpol.2020.116210

Katin, A., Del Giudice, D., Hall, N. S., Paerl, H. W., & Obenour, D. R. (2021). Simulating algal dynamics within a Bayesian framework to evaluate controls on estuary productivity. ECOLOGICAL MODELLING, 447. https://doi.org/10.1016/j.ecolmodel.2021.109497

Villez, K., Del Giudice, D., Neumann, M. B., & Rieckermann, J. (2020). Accounting for erroneous model structures in biokinetic process models. RELIABILITY ENGINEERING & SYSTEM SAFETY, 203. https://doi.org/10.1016/j.ress.2020.107075

Del Giudice, D., Matli, V. R. R., & Obenour, D. R. (2020). Bayesian mechanistic modeling characterizes Gulf of Mexico hypoxia: 1968-2016 and future scenarios. ECOLOGICAL APPLICATIONS, 30(2). https://doi.org/10.1002/eap.2032

Fang, S., Giudice, D. D., Scavia, D., Binding, C. E., Bridgeman, T. B., Chaffin, J. D., … Obenour, D. R. (2019). A space-time geostatistical model for probabilistic estimation of harmful algal bloom biomass and areal extent. Science of The Total Environment, 8, 133776. https://doi.org/10.1016/j.scitotenv.2019.133776

Katin, A., Giudice, D. D., & Obenour, D. R. (2019). Modeling biophysical controls on hypoxia in a shallow estuary using a Bayesian mechanistic approach. Environmental Modelling & Software, 7. https://doi.org/10.1016/j.envsoft.2019.07.016

Machac, D., Reichert, P., Rieckermann, J., Giudice, D. D., & Albert, C. (2018). Accelerating Bayesian inference in hydrological modeling with a mechanistic emulator. Environmental Modelling & Software, 7. https://doi.org/10.1016/j.envsoft.2018.07.016

Giudice, D. D., Zhou, Y., Sinha, E., & Michalak, A. M. (2018). Long-term phosphorus loading and springtime temperatures explain interannual variability of hypoxia in a large temperate lake. Environmental Science & Technology, 1. https://doi.org/10.1021/acs.est.7b04730

Del Giudice, D., Muenich, R. L., Kalcic, M. M., Bosch, N. S., Scavia, D., & Michalak, A. M. (2018). On the practical usefulness of least squares for assessing uncertainty in hydrologic and water quality predictions. ENVIRONMENTAL MODELLING & SOFTWARE, 105, 286–295. https://doi.org/10.1016/j.envsoft.2018.03.009

Del Giudice, D., & Davies, A. B. (2017). Communication: A few words can make a big impact. Nature, 541(7635). https://doi.org/10.1038/541030e

Giudice, D. D., Albert, C., Rieckermann, J., & Reichert, P. (2016). Describing the catchment-averaged precipitation as a stochastic process improves parameter and input estimation. Water Resour. Res., 3, n/a-n/a. https://doi.org/10.1002/2015wr017871

Del Giudice, D. (2016). Health. Science, 354(6308). https://doi.org/10.1126/science.354.6308.46

Giudice, D. D., Löwe, R., Madsen, H., Mikkelsen, P. S., & Rieckermann, J. (2015). Comparison of two stochastic techniques for reliable urban runoff prediction by modeling systematic errors. Water Resour. Res., 5, n/a-n/a. https://doi.org/10.1002/2014wr016678

Giudice, D. D., Reichert, P., Bareš, V., Albert, C., & Rieckermann, J. (2015). Model bias and complexity – Understanding the effects of structural deficits and input errors on runoff predictions. Environmental Modelling & Software, 64(1), 205–214. https://doi.org/10.1016/j.envsoft.2014.11.006

Sikorska, A. E., Giudice, D. D., Banasik, K., & Rieckermann, J. (2015). The value of streamflow data in improving TSS predictions - Bayesian multi-objective calibration. Journal of Hydrology, 9, 241–254. https://doi.org/10.1016/j.jhydrol.2015.09.051

Dürrenmatt, D. J., Del Giudice, D., & Rieckermann, J. (2013). Dynamic time warping improves sewer flow monitoring. Water Research, 47(11), 3803–3816. https://doi.org/10.1016/j.watres.2013.03.051

Del Giudice, D., Honti, M., Scheidegger, A., Albert, C., Reichert, P., & Rieckermann, J. (2013). Improving uncertainty estimation in urban hydrological modeling by statistically describing bias. Hydrology and Earth System Sciences, 17(10), 4209–4225. https://doi.org/10.5194/hess-17-4209-2013

Coutu, S., Del Giudice, D., Rossi, L., & Barry, D. A. (2012). Modeling of facade leaching in urban catchments. Water Resources Research, 48(12). https://doi.org/10.1029/2012WR012359

Coutu, S., Del Giudice, D., Rossi, L., & Barry, D. A. (2012). Parsimonious hydrological modeling of urban sewer and river catchments. Journal of Hydrology, 464-465, 477–484. https://doi.org/10.1016/j.jhydrol.2012.07.039