@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{FranckeHeistermannKoehlietal.2022,
  author    = {Francke, Till and Heistermann, Maik and K{\"o}hli, Markus and Budach, Christian and Schr{\"o}n, Martin and Oswald, Sascha},
  title     = {Assessing the feasibility of a directional cosmic-ray neutron sensing sensor for estimating soil moisture},
  series = {Geoscientific Instrumentation, Methods and Data Systems},
  volume    = {11},
  journal   = {Geoscientific Instrumentation, Methods and Data Systems},
  publisher = {Copernicus Publ.},
  address   = {G{\"o}ttingen},
  issn      = {2193-0864},
  doi       = {10.5194/gi-11-75-2022},
  pages     = {75 -- 92},
  year      = {2022},
  abstract  = {Cosmic-ray neutron sensing (CRNS) is a non-invasive tool for measuring hydrogen pools such as soil moisture, snow or vegetation. The intrinsic integration over a radial hectare-scale footprint is a clear advantage for averaging out small-scale heterogeneity, but on the other hand the data may become hard to interpret in complex terrain with patchy land use. This study presents a directional shielding approach to prevent neutrons from certain angles from being counted while counting neutrons entering the detector from other angles and explores its potential to gain a sharper horizontal view on the surrounding soil moisture distribution. Using the Monte Carlo code URANOS (Ultra Rapid Neutron-Only Simulation), we modelled the effect of additional polyethylene shields on the horizontal field of view and assessed its impact on the epithermal count rate, propagated uncertainties and aggregation time. The results demonstrate that directional CRNS measurements are strongly dominated by isotropic neutron transport, which dilutes the signal of the targeted direction especially from the far field. For typical count rates of customary CRNS stations, directional shielding of half-spaces could not lead to acceptable precision at a daily time resolution. However, the mere statistical distinction of two rates should be feasible.},
  language  = {en}
}
@misc{FranckeHeistermannKoehlietal.2022,
  author    = {Francke, Till and Heistermann, Maik and K{\"o}hli, Markus and Budach, Christian and Schr{\"o}n, Martin and Oswald, Sascha},
  title     = {Assessing the feasibility of a directional cosmic-ray neutron sensing sensor for estimating soil moisture},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-54422},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-544229},
  pages     = {75 -- 92},
  year      = {2022},
  abstract  = {Cosmic-ray neutron sensing (CRNS) is a non-invasive tool for measuring hydrogen pools such as soil moisture, snow or vegetation. The intrinsic integration over a radial hectare-scale footprint is a clear advantage for averaging out small-scale heterogeneity, but on the other hand the data may become hard to interpret in complex terrain with patchy land use. This study presents a directional shielding approach to prevent neutrons from certain angles from being counted while counting neutrons entering the detector from other angles and explores its potential to gain a sharper horizontal view on the surrounding soil moisture distribution. Using the Monte Carlo code URANOS (Ultra Rapid Neutron-Only Simulation), we modelled the effect of additional polyethylene shields on the horizontal field of view and assessed its impact on the epithermal count rate, propagated uncertainties and aggregation time. The results demonstrate that directional CRNS measurements are strongly dominated by isotropic neutron transport, which dilutes the signal of the targeted direction especially from the far field. For typical count rates of customary CRNS stations, directional shielding of half-spaces could not lead to acceptable precision at a daily time resolution. However, the mere statistical distinction of two rates should be feasible.},
  language  = {en}
}
@article{MesterWillnerFrieleretal.2021,
  author    = {Mester, Benedikt and Willner, Sven N. and Frieler, Katja and Schewe, Jacob},
  title     = {Evaluation of river flood extent simulated with multiple global hydrological models and climate forcings},
  series = {Environmental research letters : ERL / Institute of Physics},
  volume    = {16},
  journal   = {Environmental research letters : ERL / Institute of Physics},
  number    = {9},
  publisher = {IOP Publ. Ltd.},
  address   = {Bristol},
  issn      = {1748-9326},
  doi       = {10.1088/1748-9326/ac188d},
  pages     = {15},
  year      = {2021},
  abstract  = {Global flood models (GFMs) are increasingly being used to estimate global-scale societal and economic risks of river flooding. Recent validation studies have highlighted substantial differences in performance between GFMs and between validation sites. However, it has not been systematically quantified to what extent the choice of the underlying climate forcing and global hydrological model (GHM) influence flood model performance. Here, we investigate this sensitivity by comparing simulated flood extent to satellite imagery of past flood events, for an ensemble of three climate reanalyses and 11 GHMs. We study eight historical flood events spread over four continents and various climate zones. For most regions, the simulated inundation extent is relatively insensitive to the choice of GHM. For some events, however, individual GHMs lead to much lower agreement with observations than the others, mostly resulting from an overestimation of inundated areas. Two of the climate forcings show very similar results, while with the third, differences between GHMs become more pronounced. We further show that when flood protection standards are accounted for, many models underestimate flood extent, pointing to deficiencies in their flood frequency distribution. Our study guides future applications of these models, and highlights regions and models where targeted improvements might yield the largest performance gains.},
  language  = {en}
}
@article{WagenerReineckePianosi2022,
  author    = {Wagener, Thorsten and Reinecke, Robert and Pianosi, Francesca},
  title     = {On the evaluation of climate change impact models},
  series = {Wiley interdisciplinary reviews : Climate change},
  volume    = {13},
  journal   = {Wiley interdisciplinary reviews : Climate change},
  number    = {3},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {1757-7780},
  doi       = {10.1002/wcc.772},
  pages     = {13},
  year      = {2022},
  abstract  = {In-depth understanding of the potential implications of climate change is required to guide decision- and policy-makers when developing adaptation strategies and designing infrastructure suitable for future conditions. Impact models that translate potential future climate conditions into variables of interest are needed to create the causal connection between a changing climate and its impact for different sectors. Recent surveys suggest that the primary strategy for validating such models (and hence for justifying their use) heavily relies on assessing the accuracy of model simulations by comparing them against historical observations. We argue that such a comparison is necessary and valuable, but not sufficient to achieve a comprehensive evaluation of climate change impact models. We believe that a complementary, largely observation-independent, step of model evaluation is needed to ensure more transparency of model behavior and greater robustness of scenario-based analyses. This step should address the following four questions: (1) Do modeled dominant process controls match our system perception? (2) Is my model's sensitivity to changing forcing as expected? (3) Do modeled decision levers show adequate influence? (4) Can we attribute uncertainty sources throughout the projection horizon? We believe that global sensitivity analysis, with its ability to investigate a model's response to joint variations of multiple inputs in a structured way, offers a coherent approach to address all four questions comprehensively. Such additional model evaluation would strengthen stakeholder confidence in model projections and, therefore, into the adaptation strategies derived with the help of impact models. This article is categorized under: Climate Models and Modeling > Knowledge Generation with Models Assessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change},
  language  = {en}
}