Thea Roksvåg

Thea Julie Thømt Roksvåg; Silius Mortensønn Vandeskog; C. Ole Wulff; Kamilla Klock Wergeland; An LSTM network for joint modeling of streamflow and hydropower generation for run-of-river plants Journal of Hydrology, vol. 667, (ISSN 0022-1694 1879-2707 ), doi: https://doi.org/10.1016/j.jhydrol.2025.134890 , 2026. Scientific article

Celine Marie Løken Cunen; Thea Julie Thømt Roksvåg; Claudio Constantin Heinrich-Mertsching; Frank Alexander Lenkoski; Combining predictive distributions for time-to-event outcomes in meteorology International Journal of Forecasting, vol. 42, pp. 673 690 , (ISSN 0169-2070 1872-8200 ), doi: https://doi.org/10.1016/j.ijforecast.2025.10.004 , 2026. Scientific article

Michael Scheuerer; Emilie Byermoen; Julia Ribeiro De Oliveira; Thea Julie Thømt Roksvåg; Dagrun Vikhamar-Schuler; Multi-decadal streamflow projections for catchments in Brazil based on CMIP6 multi-model simulations and neural network embeddings for linear regression models Hydrology and Earth System Sciences (HESS), vol. 29, pp. 5099 5119 , (ISSN 1027-5606 1607-7938 ), doi: https://doi.org/10.5194/hess-29-5099-2025 , 2025. Scientific article

Silius Mortensønn Vandeskog; Kamilla Wergeland; Thea Julie Thømt Roksvåg; C. Ole Wulff; Predicting streamflow and hydropower production with Long Short Term Memory models doi: https://www.hydrologiraadet.no/wp-content/uploads/2025/05/9-Kamilla-W-og-Silius-V.pptx , 2025. Lecture

Julia Lutz; Thea Julie Thømt Roksvåg; Anita Verpe Dyrrdal; Cristian Lussana; Thordis Linda Thorarinsdottir; Areal reduction factors from gridded data products Journal of Hydrology, vol. 635, pp. 1 12 , (ISSN 0022-1694 1879-2707 ), doi: https://doi.org/10.1016/j.jhydrol.2024.131177 , 2024. Scientific article

Henrik Nordtorp; Thea Julie Thømt Roksvåg; Thordis Linda Thorarinsdottir; Widespread Risk of Extreme Precipitation and Flooding , 2024. Report

Thea Julie Thømt Roksvåg; Julia Lutz; Anita Verpe Dyrrdal; Cristian Lussana; Thordis Thorarinsdottir; Estimating extreme areal precipitation from gridded data products 2023. Poster

Thea Roksvåg; Ingelin Steinsland; Kolbjørn Engeland; A geostatistical spatially varying coefficient model for mean annual runoff that incorporates process-based simulations and short records Hydrology and Earth System Sciences (HESS), vol. 26, pp. 5391 5410 , (ISSN 1027-5606 1607-7938 ), doi: https://doi.org/10.5194/hess-26-5391-2022 , 2022. Scientific article

Irene Brox Nilsen; Anita Verpe Dyrrdal; Thea Roksvåg; Julia Lutz; Kolbjørn Engeland; Styrtregn og styrtflom: Hvordan kan vi unngå skader? Naturen, (ISSN 0028-0887 1504-3118 ), doi: https://doi.org/10.18261/naturen.146.1.6 , 2022. Science for the public article

Thordis Linda Thorarinsdottir; Thea Julie Thømt Roksvåg; Line Eikvil; Birdcam: Automatic monitoring of birds near wind parks 2022. Report

Thea Roksvåg; Ingelin Steinsland; Kolbjørn Engeland; A geostatistical spatially varying coefficient model for mean annual runoff that incorporates process-based simulations and short records Hydrology and Earth System Sciences (HESS), vol. 26, pp. 5391 5410 , (ISSN 1027-5606 1607-7938 ), doi: https://doi.org/10.5194/hess-26-5391-2022 , 2022. Scientific article

Irene Brox Nilsen; Anita Verpe Dyrrdal; Thea Roksvåg; Julia Lutz; Kolbjørn Engeland; Styrtregn og styrtflom: Hvordan kan vi unngå skader? Naturen, vol. 146, pp. 48 55 , (ISSN 0028-0887 1504-3118 ), doi: https://doi.org/10.18261/naturen.146.1.6 , 2022. Scientific article

Julia Lutz; Lars Grinde; Anita Verpe Dyrrdal; Thea Roksvåg; Thordis Linda Thorarinsdottir; Estimating consistent rainfall design values for Norway using Bayesian inference and post-processing of posterior quantiles 2022. Scientific lecture

Thordis Linda Thorarinsdottir; Danielle Marie Barna; Thea Roksvåg; Kolbjørn Engeland; Chong-Yu Xu; Julia Lutz; Anita Verpe Dyrrdal; Lars Grinde; Consistent estimation of extreme precipitation and flooding across multiple durations 2022. Scientific lecture

Thordis Linda Thorarinsdottir; Thea Roksvåg; Julia Lutz; Lars Grinde; Anita Verpe Dyrrdal; A Bayesian framework to derive consistent intensity-duration-frequency curves from multiple data sources 2022. Scientific lecture

Thordis Linda Thorarinsdottir; Thea Roksvåg; Kolbjørn Engeland; Danielle Marie Barna; Chong-Yu Xu; Julia Lutz; Anita Verpe Dyrrdal; Lars Grinde; Consistent estimation of extreme precipitation and flooding across multiple durations 2022. Scientific lecture

Thordis Linda Thorarinsdottir; Rune Solberg; Alex Lenkoski; Thea Roksvåg; Potensialet i data 2022. Lecture

Thea Roksvåg; Alex Lenkoski; Michael Scheuerer; Claudio Constantin Heinrich; Thordis Linda Thorarinsdottir; Probabilistic prediction of the time to hard freeze using seasonal weather forecasts and survival time methods Quarterly Journal of the Royal Meteorological Society, (ISSN 0035-9009 1477-870X ), doi: https://doi.org/10.1002/qj.4403 , 2022. Scientific article

Thea Roksvåg; Michael Scheuerer; Claudio Constantin Heinrich; Thordis Linda Thorarinsdottir; Alex Lenkoski; Probabilistic prediction of the time to hard freeze using seasonal weather forecasts and survival time methods 2022. Lecture

Manuel Hempel; Ellen-Margrethe Hovland; Kristoffer Herland Hellton; Thea Roksvåg; Vær- og klimaprognoser for framtidas grøntproduksjon 2022. Scientific lecture

Thea Roksvåg; Ola Haug; Presentasjon av Climate Futures 2022. Scientific lecture

Thea Roksvåg; Alex Lenkoski; Michael Scheuerer; Claudio Constantin Heinrich; Thordis Linda Thorarinsdottir; Probabilistic prediction of the time to hard freeze using seasonal weather forecasts and survival time methods 2022. Scientific lecture

Thea Roksvåg; Michael Scheuerer; Alex Lenkoski; Claudio Constantin Heinrich; Thordis Linda Thorarinsdottir; Prediction of the time to hard freeze using seasonal weather forecasts and survival time methods 2022. Lecture

Thea Roksvåg; Ingelin Steinsland; Kolbjørn Engeland; A Two-Field Geostatistical Model Combining Point and Areal Observations—A Case Study of Annual Runoff Predictions in the Voss Area Journal of the Royal Statistical Society, Series C (Applied Statistics), vol. 70, pp. 934 960 , (ISSN 0035-9254 1467-9876 ), doi: https://doi.org/10.1111/rssc.12492 , 2021. Scientific article

Thea Roksvåg; Julia Lutz; Lars Grinde; Anita Verpe Dyrrdal; Thordis Linda Thorarinsdottir; Consistent Intensity-Duration-Frequency curves by post-processing of estimated Bayesian posterior quantiles 2021. Scientific lecture

Thea Roksvåg; Ingelin Steinsland; Kolbjørn Engeland; Estimating mean annual runoff by using a geostatistical spatially varying coefficient model that incorporates process-based simulations and short records 2021. Scientific lecture

Thea Roksvåg; Julia Lutz; Lars Grinde; Anita Verpe Dyrrdal; Thordis Linda Thorarinsdottir; Consistent intensity-duration-frequency curves by post-processing of estimated Bayesian posterior quantiles Journal of Hydrology, vol. 603, pp. 1 15 , (ISSN 0022-1694 1879-2707 ), doi: https://doi.org/10.1016/j.jhydrol.2021.127000 , 2021. Scientific article

Thea Roksvåg; Julia Lutz; Lars Grinde; Anita Verpe Dyrrdal; Thordis Linda Thorarinsdottir; New methods for making consistent IDF curves for Norway 2021. Lecture

Thea Roksvåg; Thordis Linda Thorarinsdottir; Prediksjon av lavvann ved Åbjøra 2021. Report

Thea Roksvåg; Ingelin Steinsland; Kolbjørn Engeland; Journal of the Royal Statistical Society: Series C (Applied Statistics) Journal of the Royal Statistical Society: Series C (Applied Statistics) ORIGINAL ARTICLE Open Access A two-field geostatistical model combining point and areal observations—A case study of annual runoff predictions in the Voss area The Journal of the Royal Statistical Society, Series C (Applied Statistics), pp. 27 , doi: https://doi.org/10.1111/rssc.12492 , 2021. Scientific article

Thea Roksvåg; Ingelin Steinsland; Kolbjørn Engeland; Estimation of annual runoff by exploiting long-term spatial patterns and short records within a geostatistical framework Hydrology and Earth System Sciences (HESS), pp. 4109 4133 , doi: https://doi.org/10.5194/hess-24-4109-2020 , 2020. Scientific article

Thea Roksvåg; Ingelin Steinsland; Kolbjørn Engeland; Estimation of annual runoff by exploiting long-term spatial patterns and short records within a geostatistical framework Hydrology and Earth System Sciences (HESS), vol. 24, pp. 4109 4133 , (ISSN 1027-5606 1607-7938 ), doi: https://doi.org/10.5194/hess-24-4109-2020 , 2020. Scientific article

Thea Roksvåg; Bayesian geostatistical two field models for combining data sources and exploiting short records: Applied to annual runoff interpolation in Norway 2020. Doctor dissertat

Ingelin Steinsland; Thea Roksvåg; Kolbjørn Engeland; A new Bayesian hierarchical geostatistical model based on two spatial fields with case studies with short records of annual runoff in Norway 2020. Scientific lecture

Thea Roksvåg; Ingelin Steinsland; Kolbjørn Engeland; Using Bayesian geostatistical models to correct gridded hydrological products relative to the actually observed streamflow 2020. Poster

Thea Roksvåg; Ingelin Steinsland; Kolbjørn Engeland; Prediction of annual runoff by using a Bayesian geostatistical model for combining precipitation gauge observations and runoff observations 2018. Scientific lecture

Thea Roksvåg; Ingelin Steinsland; Kolbjørn Engeland; Prediction of annual runoff by using a Bayesian geostatistical model for combining precipitation gauge observations and runoff observations 2018. Poster

Jingyi Guo; Thea Roksvåg; Ingelin Steinsland; On combining point and area measurements for a non-stationary spatial model 2017. Poster

Thea Roksvåg; Ingelin Steinsland; Kolbjørn Engeland; A Bayesian spatial model for utilising precipitation gauge observations and runoff observations for annual runoff predictions 2017. Lecture

Thea Roksvåg; Kolbjørn Engeland; Ingelin Steinsland; A Bayesian spatial model for utilising precipitation gauge observations and runoff observations for annual runoff predictions 2017. Lecture

Jingyi Guo; Thea Roksvåg; Ingelin Steinsland; On combining point and area measurements for annual runoff predictions - A non-stationary model 2017. Scientific lecture

Thea Roksvåg; Ingelin Steinsland; A Bayesian latent Gaussian spatial model for area and point observations and predictions. 2016. Poster