@article{BormanndeBritoCharchousietal.2018,
  author    = {Bormann, Helge and de Brito, Mariana Madruga and Charchousi, Despoina and Chatzistratis, Dimitris and David, Amrei and Grosser, Paula Farina and Kebschull, Jenny and Konis, Alexandros and Koutalakis, Paschalis and Korali, Alkistis and Krauzig, Naomi and Meier, Jessica and Meliadou, Varvara and Meinhardt, Markus and Munnelly, Kieran and Stephan, Christiane and de Vos, Leon Frederik and Dietrich, J{\"o}rg and Tzoraki, Ourania},
  title     = {Impact of Hydrological Modellers' Decisions and Attitude on the Performance of a Calibrated Conceptual Catchment Model},
  series = {Hydrology},
  volume    = {5},
  journal   = {Hydrology},
  number    = {4},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2306-5338},
  doi       = {10.3390/hydrology5040064},
  pages     = {13},
  year      = {2018},
  abstract  = {In this study, 17 hydrologists with different experience in hydrological modelling applied the same conceptual catchment model (HBV) to a Greek catchment, using identical data and model code. Calibration was performed manually. Subsequently, the modellers were asked for their experience, their calibration strategy, and whether they enjoyed the exercise. The exercise revealed that there is considerable modellers' uncertainty even among the experienced modellers. It seemed to be equally important whether the modellers followed a good calibration strategy, and whether they enjoyed modelling. The exercise confirmed previous studies about the benefit of model ensembles: Different combinations of the simulation results (median, mean) outperformed the individual model simulations, while filtering the simulations even improved the quality of the model ensembles. Modellers' experience, decisions, and attitude, therefore, have an impact on the hydrological model application and should be considered as part of hydrological modelling uncertainty.},
  language  = {en}
}
@article{deBritoKuhlickeMarx2020,
  author    = {de Brito, Mariana Madruga and Kuhlicke, Christian and Marx, Andreas},
  title     = {Near-real-time drought impact assessment},
  series = {Environmental research letters},
  volume    = {15},
  journal   = {Environmental research letters},
  number    = {10},
  publisher = {IOP Publ.},
  address   = {Bristol},
  issn      = {1748-9326},
  doi       = {10.1088/1748-9326/aba4ca},
  pages     = {11},
  year      = {2020},
  abstract  = {Contemporary drought impact assessments have been constrained due to data availability, leading to an incomplete representation of impact trends. To address this, we present a novel method for the comprehensive and near-real-time monitoring of drought socio-economic impacts based on media reports. We tested its application using the case of the exceptional 2018/19 German drought. By employing text mining techniques, 4839 impact statements were identified, relating to livestock, agriculture, forestry, fires, recreation, energy and transport sectors. An accuracy of 95.6\% was obtained for their automatic classification. Furthermore, high levels of performance in terms of spatial and temporal precision were found when validating our results against independent data (e.g. soil moisture, average precipitation, population interest in droughts, crop yield and forest fire statistics). The findings highlight the applicability of media data for rapidly and accurately monitoring the propagation of drought consequences over time and space. We anticipate our method to be used as a starting point for an impact-based early warning system.},
  language  = {en}
}
@article{MadrugadeBritoOttoKuhlicke2021,
  author    = {Madruga de Brito, Mariana and Otto, Danny and Kuhlicke, Christian},
  title     = {Tracking topics and frames regarding sustainability transformations during the onset of the COVID-19 crisis},
  series = {Sustainability / Multidisciplinary Digital Publishing Institute (MDPI)},
  volume    = {13},
  journal   = {Sustainability / Multidisciplinary Digital Publishing Institute (MDPI)},
  number    = {19},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2071-1050},
  doi       = {10.3390/su131911095},
  pages     = {19},
  year      = {2021},
  abstract  = {Many researchers and politicians believe that the COVID-19 crisis may have opened a "window of opportunity " to spur sustainability transformations. Still, evidence for such a dynamic is currently lacking. Here, we propose the linkage of "big data " and "thick data " methods for monitoring debates on transformation processes by following the COVID-19 discourse on ecological sustainability in Germany. We analysed variations in the topics discussed by applying text mining techniques to a corpus with 84,500 newspaper articles published during the first COVID-19 wave. This allowed us to attain a unique and previously inaccessible "bird's eye view " of how these topics evolved. To deepen our understanding of prominent frames, a qualitative content analysis was undertaken. Furthermore, we investigated public awareness by analysing online search behaviour. The findings show an underrepresentation of sustainability topics in the German news during the early stages of the crisis. Similarly, public awareness regarding climate change was found to be reduced. Nevertheless, by examining the newspaper data in detail, we found that the pandemic is often seen as a chance for sustainability transformations-but not without a set of challenges. Our mixed-methods approach enabled us to bridge knowledge gaps between qualitative and quantitative research by "thickening " and providing context to data-driven analyses. By monitoring whether or not the current crisis is seen as a chance for sustainability transformations, we provide insights for environmental policy in times of crisis.},
  language  = {en}
}