@article{KalkuhlWenz2020, author = {Kalkuhl, Matthias and Wenz, Leonie}, title = {The impact of climate conditions on economic production}, series = {Journal of Environmental Economics and Management}, volume = {103}, journal = {Journal of Environmental Economics and Management}, publisher = {Elsevier}, address = {San Diego}, issn = {0095-0696}, doi = {10.1016/j.jeem.2020.102360}, pages = {20}, year = {2020}, abstract = {We present a novel data set of subnational economic output, Gross Regional Product (GRP), for more than 1500 regions in 77 countries that allows us to empirically estimate historic climate impacts at different time scales. Employing annual panel models, long-difference regressions and cross-sectional regressions, we identify effects on productivity levels and productivity growth. We do not find evidence for permanent growth rate impacts but we find robust evidence that temperature affects productivity levels considerably. An increase in global mean surface temperature by about 3.5°C until the end of the century would reduce global output by 7-14\% in 2100, with even higher damages in tropical and poor regions. Updating the DICE damage function with our estimates suggests that the social cost of carbon from temperature-induced productivity losses is on the order of 73-142\$/tCO2 in 2020, rising to 92-181\$/tCO2 in 2030. These numbers exclude non-market damages and damages from extreme weather events or sea-level rise.}, language = {en} } @misc{GeigerFrielerLevermann2017, author = {Geiger, Tobias and Frieler, Katja and Levermann, Anders}, title = {Reply to Comment on: High-income does not protect against hurricane losses (Environmental research letters. - 12 (2017))}, series = {Environmental research letters}, volume = {12}, journal = {Environmental research letters}, publisher = {IOP Publ. Ltd.}, address = {Bristol}, issn = {1748-9326}, doi = {10.1088/1748-9326/aa88d6}, pages = {2}, year = {2017}, abstract = {Recently a multitude of empirically derived damage models have been applied to project future tropical cyclone (TC) losses for the United States. In their study (Geiger et al 2016 Environ. Res. Lett. 11 084012) compared two approaches that differ in the scaling of losses with socio-economic drivers: the commonly-used approach resulting in a sub-linear scaling of historical TC losses with a nation's affected gross domestic product (GDP), and the disentangled approach that shows a sub-linear increase with affected population and a super-linear scaling of relative losses with per capita income. Statistics cannot determine which approach is preferable but since process understanding demands that there is a dependence of the loss on both GDP per capita and population, an approach that accounts for both separately is preferable to one which assumes a specific relation between the two dependencies. In the accompanying comment, Rybski et al argued that there is no rigorous evidence to reach the conclusion that high-income does not protect against hurricane losses. Here we affirm that our conclusion is drawn correctly and reply to further remarks raised in the comment, highlighting the adequateness of our approach but also the potential for future extension of our research.}, language = {en} } @article{CabezaMuellerPereyraetal.2018, author = {Cabeza, Sandra and M{\"u}ller, Bernd R. and Pereyra, Ricio and Fernandez, Ricardo and Gonzalez-Doncel, Gaspar and Bruno, Giovanni}, title = {Evidence of damage evolution during creep of Al-Mg alloy using synchrotron X-ray refraction}, series = {Journal of applied crystallography}, volume = {51}, journal = {Journal of applied crystallography}, publisher = {International Union of Crystallography}, address = {Chester}, issn = {1600-5767}, doi = {10.1107/S1600576718001449}, pages = {420 -- 427}, year = {2018}, abstract = {In order to provide further evidence of damage mechanisms predicted by the recent solid-state transformation creep (SSTC) model, direct observation of damage accumulation during creep of Al-3.85Mg was made using synchrotron X-ray refraction. X-ray refraction techniques detect the internal specific surface (i.e. surface per unit volume) on a length scale comparable to the specimen size, but with microscopic sensitivity. A significant rise in the internal specific surface with increasing creep time was observed, providing evidence for the creation of a fine grain substructure, as predicted by the SSTC model. This substructure was also observed by scanning electron microscopy.}, language = {en} } @misc{SamprognaMohorThiekenKorup2021, author = {Samprogna Mohor, Guilherme and Thieken, Annegret and Korup, Oliver}, title = {Residential flood loss estimated from Bayesian multilevel models}, 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-51774}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-517743}, pages = {1599 -- 1614}, year = {2021}, abstract = {Models for the predictions of monetary losses from floods mainly blend data deemed to represent a single flood type and region. Moreover, these approaches largely ignore indicators of preparedness and how predictors may vary between regions and events, challenging the transferability of flood loss models. We use a flood loss database of 1812 German flood-affected households to explore how Bayesian multilevel models can estimate normalised flood damage stratified by event, region, or flood process type. Multilevel models acknowledge natural groups in the data and allow each group to learn from others. We obtain posterior estimates that differ between flood types, with credibly varying influences of water depth, contamination, duration, implementation of property-level precautionary measures, insurance, and previous flood experience; these influences overlap across most events or regions, however. We infer that the underlying damaging processes of distinct flood types deserve further attention. Each reported flood loss and affected region involved mixed flood types, likely explaining the uncertainty in the coefficients. Our results emphasise the need to consider flood types as an important step towards applying flood loss models elsewhere. We argue that failing to do so may unduly generalise the model and systematically bias loss estimations from empirical data.}, language = {en} } @article{SamprognaMohorThiekenKorup2021, author = {Samprogna Mohor, Guilherme and Thieken, Annegret and Korup, Oliver}, title = {Residential flood loss estimated from Bayesian multilevel models}, series = {Natural Hazards and Earth System Sciences}, volume = {21}, journal = {Natural Hazards and Earth System Sciences}, publisher = {European Geophysical Society}, address = {Katlenburg-Lindau}, issn = {2195-9269}, doi = {10.5194/nhess-21-1599-2021}, pages = {1599 -- 1614}, year = {2021}, abstract = {Models for the predictions of monetary losses from floods mainly blend data deemed to represent a single flood type and region. Moreover, these approaches largely ignore indicators of preparedness and how predictors may vary between regions and events, challenging the transferability of flood loss models. We use a flood loss database of 1812 German flood-affected households to explore how Bayesian multilevel models can estimate normalised flood damage stratified by event, region, or flood process type. Multilevel models acknowledge natural groups in the data and allow each group to learn from others. We obtain posterior estimates that differ between flood types, with credibly varying influences of water depth, contamination, duration, implementation of property-level precautionary measures, insurance, and previous flood experience; these influences overlap across most events or regions, however. We infer that the underlying damaging processes of distinct flood types deserve further attention. Each reported flood loss and affected region involved mixed flood types, likely explaining the uncertainty in the coefficients. Our results emphasise the need to consider flood types as an important step towards applying flood loss models elsewhere. We argue that failing to do so may unduly generalise the model and systematically bias loss estimations from empirical data.}, language = {en} } @misc{LaudanZoellerThieken2020, author = {Laudan, Jonas and Z{\"o}ller, Gert and Thieken, Annegret}, title = {Flash floods versus river floods}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {968}, issn = {1866-8372}, doi = {10.25932/publishup-47397}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-473974}, pages = {999 -- 1023}, year = {2020}, abstract = {River floods are among the most damaging natural hazards that frequently occur in Germany. Flooding causes high economic losses and impacts many residents. In 2016, several southern German municipalities were hit by flash floods after unexpectedly severe heavy rainfall, while in 2013 widespread river flooding had occurred. This study investigates and compares the psychological impacts of river floods and flash floods and potential consequences for precautionary behaviour. Data were collected using computer-aided telephone interviews that were conducted among flood-affected households around 9 months after each damaging event. This study applies Bayesian statistics and negative binomial regressions to test the suitability of psychological indicators to predict the precaution motivation of individuals. The results show that it is not the particular flood type but rather the severity and local impacts of the event that are crucial for the different, and potentially negative, impacts on mental health. According to the used data, however, predictions of the individual precaution motivation should not be based on the derived psychological indicators - i.e. coping appraisal, threat appraisal, burden and evasion - since their explanatory power was generally low and results are, for the most part, non-significant. Only burden reveals a significant positive relation to planned precaution regarding weak flash floods. In contrast to weak flash floods and river floods, the perceived threat of strong flash floods is significantly lower although feelings of burden and lower coping appraisals are more pronounced. Further research is needed to better include psychological assessment procedures and to focus on alternative data sources regarding floods and the connected precaution motivation of affected residents.}, language = {en} } @article{LaudanZoellerThieken2020, author = {Laudan, Jonas and Z{\"o}ller, Gert and Thieken, Annegret}, title = {Flash floods versus river floods}, series = {Natural Hazards and Earth System Sciences}, volume = {20}, journal = {Natural Hazards and Earth System Sciences}, publisher = {European Geophysical Society}, address = {Katlenburg-Lindau}, issn = {1684-9981}, doi = {10.5194/nhess-20-999-2020}, pages = {999 -- 1023}, year = {2020}, abstract = {River floods are among the most damaging natural hazards that frequently occur in Germany. Flooding causes high economic losses and impacts many residents. In 2016, several southern German municipalities were hit by flash floods after unexpectedly severe heavy rainfall, while in 2013 widespread river flooding had occurred. This study investigates and compares the psychological impacts of river floods and flash floods and potential consequences for precautionary behaviour. Data were collected using computer-aided telephone interviews that were conducted among flood-affected households around 9 months after each damaging event. This study applies Bayesian statistics and negative binomial regressions to test the suitability of psychological indicators to predict the precaution motivation of individuals. The results show that it is not the particular flood type but rather the severity and local impacts of the event that are crucial for the different, and potentially negative, impacts on mental health. According to the used data, however, predictions of the individual precaution motivation should not be based on the derived psychological indicators - i.e. coping appraisal, threat appraisal, burden and evasion - since their explanatory power was generally low and results are, for the most part, non-significant. Only burden reveals a significant positive relation to planned precaution regarding weak flash floods. In contrast to weak flash floods and river floods, the perceived threat of strong flash floods is significantly lower although feelings of burden and lower coping appraisals are more pronounced. Further research is needed to better include psychological assessment procedures and to focus on alternative data sources regarding floods and the connected precaution motivation of affected residents.}, language = {en} } @misc{TrietDungMerzetal.2018, author = {Triet, Nguyen Van Khanh and Dung, Nguyen Viet and Merz, Bruno and Apel, Heiko}, title = {Towards risk-based flood management in highly productive paddy rice cultivation}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {931}, issn = {1866-8372}, doi = {10.25932/publishup-44603}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-446032}, pages = {2859 -- 2876}, year = {2018}, abstract = {Flooding is an imminent natural hazard threatening most river deltas, e.g. the Mekong Delta. An appropriate flood management is thus required for a sustainable development of the often densely populated regions. Recently, the traditional event-based hazard control shifted towards a risk management approach in many regions, driven by intensive research leading to new legal regulation on flood management. However, a large-scale flood risk assessment does not exist for the Mekong Delta. Particularly, flood risk to paddy rice cultivation, the most important economic activity in the delta, has not been performed yet. Therefore, the present study was developed to provide the very first insight into delta-scale flood damages and risks to rice cultivation. The flood hazard was quantified by probabilistic flood hazard maps of the whole delta using a bivariate extreme value statistics, synthetic flood hydrographs, and a large-scale hydraulic model. The flood risk to paddy rice was then quantified considering cropping calendars, rice phenology, and harvest times based on a time series of enhanced vegetation index (EVI) derived from MODIS satellite data, and a published rice flood damage function. The proposed concept provided flood risk maps to paddy rice for the Mekong Delta in terms of expected annual damage. The presented concept can be used as a blueprint for regions facing similar problems due to its generic approach. Furthermore, the changes in flood risk to paddy rice caused by changes in land use currently under discussion in the Mekong Delta were estimated. Two land-use scenarios either intensifying or reducing rice cropping were considered, and the changes in risk were presented in spatially explicit flood risk maps. The basic risk maps could serve as guidance for the authorities to develop spatially explicit flood management and mitigation plans for the delta. The land-use change risk maps could further be used for adaptive risk management plans and as a basis for a cost-benefit of the discussed land-use change scenarios. Additionally, the damage and risks maps may support the recently initiated agricultural insurance programme in Vietnam.}, language = {en} } @article{RoezerMuellerBubecketal.2016, author = {R{\"o}zer, Viktor and M{\"u}ller, Meike and Bubeck, Philip and Kienzler, Sarah and Thieken, Annegret and Pech, Ina and Schr{\"o}ter, Kai and Buchholz, Oliver and Kreibich, Heidi}, title = {Coping with Pluvial Floods by Private Households}, series = {Water}, volume = {8}, journal = {Water}, publisher = {MDPI}, address = {Basel}, issn = {2073-4441}, doi = {10.3390/w8070304}, pages = {24}, year = {2016}, abstract = {Pluvial floods have caused severe damage to urban areas in recent years. With a projected increase in extreme precipitation as well as an ongoing urbanization, pluvial flood damage is expected to increase in the future. Therefore, further insights, especially on the adverse consequences of pluvial floods and their mitigation, are needed. To gain more knowledge, empirical damage data from three different pluvial flood events in Germany were collected through computer-aided telephone interviews. Pluvial flood awareness as well as flood experience were found to be low before the respective flood events. The level of private precaution increased considerably after all events, but is mainly focused on measures that are easy to implement. Lower inundation depths, smaller potential losses as compared with fluvial floods, as well as the fact that pluvial flooding may occur everywhere, are expected to cause a shift in damage mitigation from precaution to emergency response. However, an effective implementation of emergency measures was constrained by a low dissemination of early warnings in the study areas. Further improvements of early warning systems including dissemination as well as a rise in pluvial flood preparedness are important to reduce future pluvial flood damage.}, language = {en} } @article{GeigerFrielerLevermann2016, author = {Geiger, Tobias and Frieler, Katja and Levermann, Anders}, title = {High-income does not protect against hurricane losses}, series = {Environmental research letters}, volume = {11}, journal = {Environmental research letters}, publisher = {IOP Publ. Ltd.}, address = {Bristol}, issn = {1748-9326}, doi = {10.1088/1748-9326/11/8/084012}, pages = {10}, year = {2016}, abstract = {Damage due to tropical cyclones accounts for more than 50\% of all meteorologically-induced economic losses worldwide. Their nominal impact is projected to increase substantially as the exposed population grows, per capita income increases, and anthropogenic climate change manifests. So far, historical losses due to tropical cyclones have been found to increase less than linearly with a nation's affected gross domestic product (GDP). Here we show that for the United States this scaling is caused by a sub-linear increase with affected population while relative losses scale super-linearly with per capita income. The finding is robust across a multitude of empirically derived damage models that link the storm's wind speed, exposed population, and per capita GDP to reported losses. The separation of both socio-economic predictors strongly affects the projection of potential future hurricane losses. Separating the effects of growth in population and per-capita income, per hurricane losses with respect to national GDP are projected to triple by the end of the century under unmitigated climate change, while they are estimated to decrease slightly without the separation.}, language = {en} }