@article{BuergerHeistermannBronstert2014,
  author    = {B{\"u}rger, Gerd and Heistermann, Maik and Bronstert, Axel},
  title     = {Towards subdaily rainfall disaggregation via Clausius-Clapeyron},
  series = {Journal of hydrometeorology},
  volume    = {15},
  journal   = {Journal of hydrometeorology},
  number    = {3},
  publisher = {American Meteorological Soc.},
  address   = {Boston},
  issn      = {1525-755X},
  doi       = {10.1175/JHM-D-13-0161.1},
  pages     = {1303 -- 1311},
  year      = {2014},
  abstract  = {Two lines of research are combined in this study: first, the development of tools for the temporal disaggregation of precipitation, and second, some newer results on the exponential scaling of heavy short-term precipitation with temperature, roughly following the Clausius-Clapeyron (CC) relation. Having no extra temperature dependence, the traditional disaggregation schemes are shown to lack the crucial CC-type temperature dependence. The authors introduce a proof-of-concept adjustment of an existing disaggregation tool, the multiplicative cascade model of Olsson, and show that, in principal, it is possible to include temperature dependence in the disaggregation step, resulting in a fairly realistic temperature dependence of the CC type. They conclude by outlining the main calibration steps necessary to develop a full-fledged CC disaggregation scheme and discuss possible applications.},
  language  = {en}
}
@article{BronstertCreutzfeldtGraeffetal.2012,
  author    = {Bronstert, Axel and Creutzfeldt, Benjamin and Gr{\"a}ff, Thomas and Hajnsek, Irena and Heistermann, Maik and Itzerott, Sibylle and Jagdhuber, Thomas and Kneis, David and Lueck, Erika and Reusser, Dominik and Zehe, Erwin},
  title     = {Potentials and constraints of different types of soil moisture observations for flood simulations in headwater catchments},
  series = {Natural hazards : journal of the International Society for the Prevention and Mitigation of Natural Hazards},
  volume    = {60},
  journal   = {Natural hazards : journal of the International Society for the Prevention and Mitigation of Natural Hazards},
  number    = {3},
  publisher = {Springer},
  address   = {New York},
  issn      = {0921-030X},
  doi       = {10.1007/s11069-011-9874-9},
  pages     = {879 -- 914},
  year      = {2012},
  abstract  = {Flood generation in mountainous headwater catchments is governed by rainfall intensities, by the spatial distribution of rainfall and by the state of the catchment prior to the rainfall, e. g. by the spatial pattern of the soil moisture, groundwater conditions and possibly snow. The work presented here explores the limits and potentials of measuring soil moisture with different methods and in different scales and their potential use for flood simulation. These measurements were obtained in 2007 and 2008 within a comprehensive multi-scale experiment in the Weisseritz headwater catchment in the Ore-Mountains, Germany. The following technologies have been applied jointly thermogravimetric method, frequency domain reflectometry (FDR) sensors, spatial time domain reflectometry (STDR) cluster, ground-penetrating radar (GPR), airborne polarimetric synthetic aperture radar (polarimetric SAR) and advanced synthetic aperture radar (ASAR) based on the satellite Envisat. We present exemplary soil measurement results, with spatial scales ranging from point scale, via hillslope and field scale, to the catchment scale. Only the spatial TDR cluster was able to record continuous data. The other methods are limited to the date of over-flights (airplane and satellite) or measurement campaigns on the ground. For possible use in flood simulation, the observation of soil moisture at multiple scales has to be combined with suitable hydrological modelling, using the hydrological model WaSiM-ETH. Therefore, several simulation experiments have been conducted in order to test both the usability of the recorded soil moisture data and the suitability of a distributed hydrological model to make use of this information. The measurement results show that airborne-based and satellite-based systems in particular provide information on the near-surface spatial distribution. However, there are still a variety of limitations, such as the need for parallel ground measurements (Envisat ASAR), uncertainties in polarimetric decomposition techniques (polarimetric SAR), very limited information from remote sensing methods about vegetated surfaces and the non-availability of continuous measurements. The model experiments showed the importance of soil moisture as an initial condition for physically based flood modelling. However, the observed moisture data reflect the surface or near-surface soil moisture only. Hence, only saturated overland flow might be related to these data. Other flood generation processes influenced by catchment wetness in the subsurface such as subsurface storm flow or quick groundwater drainage cannot be assessed by these data. One has to acknowledge that, in spite of innovative measuring techniques on all spatial scales, soil moisture data for entire vegetated catchments are still today not operationally available. Therefore, observations of soil moisture should primarily be used to improve the quality of continuous, distributed hydrological catchment models that simulate the spatial distribution of moisture internally. Thus, when and where soil moisture data are available, they should be compared with their simulated equivalents in order to improve the parameter estimates and possibly the structure of the hydrological model.},
  language  = {en}
}
@article{HeistermannFranckeGeorgietal.2014,
  author    = {Heistermann, Maik and Francke, Till and Georgi, Christof and Bronstert, Axel},
  title     = {Increasing life expectancy of water resources literature},
  series = {Water resources research},
  volume    = {50},
  journal   = {Water resources research},
  number    = {6},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {0043-1397},
  doi       = {10.1002/2014WR015674},
  pages     = {5019 -- 5028},
  year      = {2014},
  abstract  = {In a study from 2008, Lariviere and colleagues showed, for the field of natural sciences and engineering, that the median age of cited references is increasing over time. This result was considered counterintuitive: with the advent of electronic search engines, online journal issues and open access publications, one could have expected that cited literature is becoming younger. That study has motivated us to take a closer look at the changes in the age distribution of references that have been cited in water resources journals since 1965. Not only could we confirm the findings of Lariviere and colleagues. We were also able to show that the aging is mainly happening in the oldest 10-25\% of an average reference list. This is consistent with our analysis of top-cited papers in the field of water resources. Rankings based on total citations since 1965 consistently show the dominance of old literature, including text books and research papers in equal shares. For most top-cited old-timers, citations are still growing exponentially. There is strong evidence that most citations are attracted by publications that introduced methods which meanwhile belong to the standard toolset of researchers and practitioners in the field of water resources. Although we think that this trend should not be overinterpreted as a sign of stagnancy, there might be cause for concern regarding how authors select their references. We question the increasing citation of textbook knowledge as it holds the risk that reference lists become overcrowded, and that the readability of papers deteriorates.},
  language  = {en}
}
@misc{VormoorHeistermannBronstertetal.2018,
  author    = {Vormoor, Klaus Josef and Heistermann, Maik and Bronstert, Axel and Lawrence, Deborah},
  title     = {Hydrological model parameter (in)stability},
  series = {Hydrological Sciences Journal},
  journal   = {Hydrological Sciences Journal},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-413008},
  pages     = {18},
  year      = {2018},
  abstract  = {This paper investigates the transferability of calibrated HBV model parameters under stable and contrasting conditions in terms of flood seasonality and flood generating processes (FGP) in five Norwegian catchments with mixed snowmelt/rainfall regimes. We apply a series of generalized (differential) split-sample tests using a 6-year moving window over (i) the entire runoff observation periods, and (ii) two subsets of runoff observations distinguished by the seasonal occurrence of annual maximum floods during either spring or autumn. The results indicate a general model performance loss due to the transfer of calibrated parameters to independent validation periods of -5 to -17\%, on average. However, there is no indication that contrasting flood seasonality exacerbates performance losses, which contradicts the assumption that optimized parameter sets for snowmelt-dominated floods (during spring) perform particularly poorly on validation periods with rainfall-dominated floods (during autumn) and vice versa.},
  language  = {en}
}
@misc{VormoorLawrenceHeistermannetal.2015,
  author    = {Vormoor, Klaus Josef and Lawrence, D. and Heistermann, Maik and Bronstert, Axel},
  title     = {Climate change impacts on the seasonality and generation processes of floods},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-84366},
  year      = {2015},
  abstract  = {Climate change is likely to impact the seasonality and generation processes of floods in the Nordic countries, which has direct implications for flood risk assessment, design flood estimation, and hydropower production management. Using a multi-model/multi-parameter approach to simulate daily discharge for a reference (1961-1990) and a future (2071-2099) period, we analysed the projected changes in flood seasonality and generation processes in six catchments with mixed snowmelt/rainfall regimes under the current climate in Norway. The multi-model/multi-parameter ensemble consists of (i) eight combinations of global and regional climate models, (ii) two methods for adjusting the climate model output to the catchment scale, and (iii) one conceptual hydrological model with 25 calibrated parameter sets. Results indicate that autumn/winter events become more frequent in all catchments considered, which leads to an intensification of the current autumn/winter flood regime for the coastal catchments, a reduction of the dominance of spring/summer flood regimes in a high-mountain catchment, and a possible systematic shift in the current flood regimes from spring/summer to autumn/winter in the two catchments located in northern and south-eastern Norway. The changes in flood regimes result from increasing event magnitudes or frequencies, or a combination of both during autumn and winter. Changes towards more dominant autumn/winter events correspond to an increasing relevance of rainfall as a flood generating process (FGP) which is most pronounced in those catchments with the largest shifts in flood seasonality. Here, rainfall replaces snowmelt as the dominant FGP primarily due to increasing temperature.We further analysed the ensemble components in contributing to overall uncertainty in the projected changes and found that the climate projections and the methods for downscaling or bias correction tend to be the largest contributors. The relative role of hydrological parameter uncertainty, however, is highest for those catchments showing the largest changes in flood seasonality, which confirms the lack of robustness in hydrological model parameterization for simulations under transient hydrometeorological conditions.},
  language  = {en}
}
@article{VormoorLawrenceHeistermannetal.2015,
  author    = {Vormoor, Klaus Josef and Lawrence, D. and Heistermann, Maik and Bronstert, Axel},
  title     = {Climate change impacts on the seasonality and generation processes of floods},
  series = {Hydrology and earth system sciences : HESS},
  volume    = {19},
  journal   = {Hydrology and earth system sciences : HESS},
  number    = {2},
  publisher = {Copernicus Publications},
  address   = {G{\"o}ttingen},
  issn      = {1027-5606},
  doi       = {10.5194/hess-19-913-2015},
  pages     = {913 -- 931},
  year      = {2015},
  abstract  = {Climate change is likely to impact the seasonality and generation processes of floods in the Nordic countries, which has direct implications for flood risk assessment, design flood estimation, and hydropower production management. Using a multi-model/multi-parameter approach to simulate daily discharge for a reference (1961-1990) and a future (2071-2099) period, we analysed the projected changes in flood seasonality and generation processes in six catchments with mixed snowmelt/rainfall regimes under the current climate in Norway. The multi-model/multi-parameter ensemble consists of (i) eight combinations of global and regional climate models, (ii) two methods for adjusting the climate model output to the catchment scale, and (iii) one conceptual hydrological model with 25 calibrated parameter sets. Results indicate that autumn/winter events become more frequent in all catchments considered, which leads to an intensification of the current autumn/winter flood regime for the coastal catchments, a reduction of the dominance of spring/summer flood regimes in a high-mountain catchment, and a possible systematic shift in the current flood regimes from spring/summer to autumn/winter in the two catchments located in northern and south-eastern Norway. The changes in flood regimes result from increasing event magnitudes or frequencies, or a combination of both during autumn and winter. Changes towards more dominant autumn/winter events correspond to an increasing relevance of rainfall as a flood generating process (FGP) which is most pronounced in those catchments with the largest shifts in flood seasonality. Here, rainfall replaces snowmelt as the dominant FGP primarily due to increasing temperature.We further analysed the ensemble components in contributing to overall uncertainty in the projected changes and found that the climate projections and the methods for downscaling or bias correction tend to be the largest contributors. The relative role of hydrological parameter uncertainty, however, is highest for those catchments showing the largest changes in flood seasonality, which confirms the lack of robustness in hydrological model parameterization for simulations under transient hydrometeorological conditions.},
  language  = {en}
}
@misc{SeleemAyzelCostaTomazdeSouzaetal.2022,
  author    = {Seleem, Omar and Ayzel, Georgy and Costa Tomaz de Souza, Arthur and Bronstert, Axel and Heistermann, Maik},
  title     = {Towards urban flood susceptibility mapping using data-driven models in Berlin, Germany},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {1297},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-57680},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-576806},
  pages     = {1640 -- 1662},
  year      = {2022},
  abstract  = {Identifying urban pluvial flood-prone areas is necessary but the application of two-dimensional hydrodynamic models is limited to small areas. Data-driven models have been showing their ability to map flood susceptibility but their application in urban pluvial flooding is still rare. A flood inventory (4333 flooded locations) and 11 factors which potentially indicate an increased hazard for pluvial flooding were used to implement convolutional neural network (CNN), artificial neural network (ANN), random forest (RF) and support vector machine (SVM) to: (1) Map flood susceptibility in Berlin at 30, 10, 5, and 2 m spatial resolutions. (2) Evaluate the trained models' transferability in space. (3) Estimate the most useful factors for flood susceptibility mapping. The models' performance was validated using the Kappa, and the area under the receiver operating characteristic curve (AUC). The results indicated that all models perform very well (minimum AUC = 0.87 for the testing dataset). The RF models outperformed all other models at all spatial resolutions and the RF model at 2 m spatial resolution was superior for the present flood inventory and predictor variables. The majority of the models had a moderate performance for predictions outside the training area based on Kappa evaluation (minimum AUC = 0.8). Aspect and altitude were the most influencing factors on the image-based and point-based models respectively. Data-driven models can be a reliable tool for urban pluvial flood susceptibility mapping wherever a reliable flood inventory is available.},
  language  = {en}
}
@misc{SeleemAyzelBronstertetal.2023,
  author    = {Seleem, Omar and Ayzel, Georgy and Bronstert, Axel and Heistermann, Maik},
  title     = {Transferability of data-driven models to predict urban pluvial flood water depth in Berlin, Germany},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {1323},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-58916},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-589168},
  pages     = {809 -- 822},
  year      = {2023},
  abstract  = {Data-driven models have been recently suggested to surrogate computationally expensive hydrodynamic models to map flood hazards. However, most studies focused on developing models for the same area or the same precipitation event. It is thus not obvious how transferable the models are in space. This study evaluates the performance of a convolutional neural network (CNN) based on the U-Net architecture and the random forest (RF) algorithm to predict flood water depth, the models' transferability in space and performance improvement using transfer learning techniques. We used three study areas in Berlin to train, validate and test the models. The results showed that (1) the RF models outperformed the CNN models for predictions within the training domain, presumable at the cost of overfitting; (2) the CNN models had significantly higher potential than the RF models to generalize beyond the training domain; and (3) the CNN models could better benefit from transfer learning technique to boost their performance outside training domains than RF models.},
  language  = {en}
}
@misc{SeleemHeistermannBronstert2021,
  author    = {Seleem, Omar and Heistermann, Maik and Bronstert, Axel},
  title     = {Efficient Hazard Assessment For Pluvial Floods In Urban Environments},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {18},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-52215},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-522158},
  pages     = {19},
  year      = {2021},
  abstract  = {The presence of impermeable surfaces in urban areas hinders natural drainage and directs the surface runoff to storm drainage systems with finite capacity, which makes these areas prone to pluvial flooding. The occurrence of pluvial flooding depends on the existence of minimal areas for surface runoff generation and concentration. Detailed hydrologic and hydrodynamic simulations are computationally expensive and require intensive resources. This study compared and evaluated the performance of two simplified methods to identify urban pluvial flood-prone areas, namely the fill-spill-merge (FSM) method and the topographic wetness index (TWI) method and used the TELEMAC-2D hydrodynamic numerical model for benchmarking and validation. The FSM method uses common GIS operations to identify flood-prone depressions from a high-resolution digital elevation model (DEM). The TWI method employs the maximum likelihood method (MLE) to probabilistically calibrate a TWI threshold (τ) based on the inundation maps from a 2D hydrodynamic model for a given spatial window (W) within the urban area. We found that the FSM method clearly outperforms the TWI method both conceptually and effectively in terms of model performance.},
  language  = {en}
}
@article{SeleemHeistermannBronstert2021,
  author    = {Seleem, Omar and Heistermann, Maik and Bronstert, Axel},
  title     = {Efficient Hazard Assessment For Pluvial Floods In Urban Environments},
  series = {Water},
  volume    = {13},
  journal   = {Water},
  number    = {18},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2073-4441},
  doi       = {10.3390/w13182476},
  pages     = {17},
  year      = {2021},
  abstract  = {The presence of impermeable surfaces in urban areas hinders natural drainage and directs the surface runoff to storm drainage systems with finite capacity, which makes these areas prone to pluvial flooding. The occurrence of pluvial flooding depends on the existence of minimal areas for surface runoff generation and concentration. Detailed hydrologic and hydrodynamic simulations are computationally expensive and require intensive resources. This study compared and evaluated the performance of two simplified methods to identify urban pluvial flood-prone areas, namely the fill-spill-merge (FSM) method and the topographic wetness index (TWI) method and used the TELEMAC-2D hydrodynamic numerical model for benchmarking and validation. The FSM method uses common GIS operations to identify flood-prone depressions from a high-resolution digital elevation model (DEM). The TWI method employs the maximum likelihood method (MLE) to probabilistically calibrate a TWI threshold (τ) based on the inundation maps from a 2D hydrodynamic model for a given spatial window (W) within the urban area. We found that the FSM method clearly outperforms the TWI method both conceptually and effectively in terms of model performance.},
  language  = {en}
}
@article{HeistermannCrisologoAbonetal.2013,
  author    = {Heistermann, Maik and Crisologo, Irene and Abon, Catherine Cristobal and Racoma, B. A. and Jacobi, S. and Servando, N. T. and David, C. P. C. and Bronstert, Axel},
  title     = {Using the new Philippine radar network to reconstruct the Habagat of August 2012 monsoon event around Metropolitan Manila},
  series = {Natural hazards and earth system sciences},
  volume    = {13},
  journal   = {Natural hazards and earth system sciences},
  number    = {3},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1561-8633},
  doi       = {10.5194/nhess-13-653-2013},
  pages     = {653 -- 657},
  year      = {2013},
  abstract  = {From 6 to 9 August 2012, intense rainfall hit the northern Philippines, causing massive floods in Metropolitan Manila and nearby regions. Local rain gauges recorded almost 1000mm within this period. However, the recently installed Philippine network of weather radars suggests that Metropolitan Manila might have escaped a potentially bigger flood just by a whisker, since the centre of mass of accumulated rainfall was located over Manila Bay. A shift of this centre by no more than 20 km could have resulted in a flood disaster far worse than what occurred during Typhoon Ketsana in September 2009.},
  language  = {en}
}
@incollection{BronstertCrisologoHeistermannetal.2020,
  author    = {Bronstert, Axel and Crisologo, Irene and Heistermann, Maik and {\"O}zt{\"u}rk, Ugur and Vogel, Kristin and Wendi, Dadiyorto},
  title     = {Flash-floods: more often, more severe, more damaging?},
  series = {Climate change, hazards and adaptation options: handling the impacts of a changing climate},
  booktitle = {Climate change, hazards and adaptation options: handling the impacts of a changing climate},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-37425-9},
  issn      = {1610-2010},
  doi       = {10.1007/978-3-030-37425-9_12},
  pages     = {225 -- 244},
  year      = {2020},
  abstract  = {In recent years, urban and rural flash floods in Europe and abroad have gained considerable attention because of their sudden occurrence, severe material damages and even danger to life of inhabitants. This contribution addresses questions about possibly changing environmental conditions which might have altered the occurrence frequencies of such events and their consequences. We analyze the following major fields of environmental changes. Altered high intensity rain storm conditions, as a consequence of regionalwarming; Possibly altered runoff generation conditions in response to high intensity rainfall events; Possibly altered runoff concentration conditions in response to the usage and management of the landscape, such as agricultural, forest practices or rural roads; Effects of engineering measures in the catchment, such as retention basins, check dams, culverts, or river and geomorphological engineering measures. We take the flash-flood in Braunsbach, SW-Germany, as an example, where a particularly concise flash flood event occurred at the end of May 2016. This extreme cascading natural event led to immense damage in this particular village. The event is retrospectively analyzed with regard to meteorology, hydrology, geomorphology and damage to obtain a quantitative assessment of the processes and their development. The results show that it was a very rare rainfall event with extreme intensities, which in combination with catchment properties and altered environmental conditions led to extreme runoff, extreme debris flow and immense damages. Due to the complex and interacting processes, no single flood cause can be identified, since only the interplay of those led to such an event. We have shown that environmental changes are important, but-at least for this case study-even natural weather and hydrologic conditions would still have resulted in an extreme flash flood event.},
  language  = {en}
}
@article{BronstertAgarwalBoessenkooletal.2018,
  author    = {Bronstert, Axel and Agarwal, Ankit and Boessenkool, Berry and Crisologo, Irene and Fischer, Madlen and Heistermann, Maik and Koehn-Reich, Lisei and Andres Lopez-Tarazon, Jose and Moran, Thomas and Ozturk, Ugur and Reinhardt-Imjela, Christian and Wendi, Dadiyorto},
  title     = {Forensic hydro-meteorological analysis of an extreme flash flood},
  series = {The science of the total environment : an international journal for scientific research into the environment and its relationship with man},
  volume    = {630},
  journal   = {The science of the total environment : an international journal for scientific research into the environment and its relationship with man},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0048-9697},
  doi       = {10.1016/j.scitotenv.2018.02.241},
  pages     = {977 -- 991},
  year      = {2018},
  abstract  = {The flash-flood in Braunsbach in the north-eastern part of Baden-Wuerttemberg/Germany was a particularly strong and concise event which took place during the floods in southern Germany at the end of May/early June 2016. This article presents a detailed analysis of the hydro-meteorological forcing and the hydrological consequences of this event. A specific approach, the "forensic hydrological analysis" was followed in order to include and combine retrospectively a variety of data from different disciplines. Such an approach investigates the origins, mechanisms and course of such natural events if possible in a "near real time" mode, in order to follow the most recent traces of the event. The results show that it was a very rare rainfall event with extreme intensities which, in combination with catchment properties, led to extreme runoff plus severe geomorphological hazards, i.e. great debris flows, which together resulted in immense damage in this small rural town Braunsbach. It was definitely a record-breaking event and greatly exceeded existing design guidelines for extreme flood discharge for this region, i.e. by a factor of about 10. Being such a rare or even unique event, it is not reliably feasible to put it into a crisp probabilistic context. However, one can conclude that a return period clearly above 100 years can be assigned for all event components: rainfall, peak discharge and sediment transport. Due to the complex and interacting processes, no single flood cause or reason for the very high damage can be identified, since only the interplay and the cascading characteristics of those led to such an event. The roles of different human activities on the origin and/or intensification of such an extreme event are finally discussed. (C) 2018 Elsevier B.V. All rights reserved.},
  language  = {en}
}
@article{SeleemAyzelCostaTomazdeSouzaetal.2022,
  author    = {Seleem, Omar and Ayzel, Georgy and Costa Tomaz de Souza, Arthur and Bronstert, Axel and Heistermann, Maik},
  title     = {Towards urban flood susceptibility mapping using data-driven models in Berlin, Germany},
  series = {Geomatics, natural hazards and risk},
  volume    = {13},
  journal   = {Geomatics, natural hazards and risk},
  number    = {1},
  publisher = {Taylor \& Francis},
  address   = {London},
  issn      = {1947-5705},
  doi       = {10.1080/19475705.2022.2097131},
  pages     = {1640 -- 1662},
  year      = {2022},
  abstract  = {Identifying urban pluvial flood-prone areas is necessary but the application of two-dimensional hydrodynamic models is limited to small areas. Data-driven models have been showing their ability to map flood susceptibility but their application in urban pluvial flooding is still rare. A flood inventory (4333 flooded locations) and 11 factors which potentially indicate an increased hazard for pluvial flooding were used to implement convolutional neural network (CNN), artificial neural network (ANN), random forest (RF) and support vector machine (SVM) to: (1) Map flood susceptibility in Berlin at 30, 10, 5, and 2 m spatial resolutions. (2) Evaluate the trained models' transferability in space. (3) Estimate the most useful factors for flood susceptibility mapping. The models' performance was validated using the Kappa, and the area under the receiver operating characteristic curve (AUC). The results indicated that all models perform very well (minimum AUC = 0.87 for the testing dataset). The RF models outperformed all other models at all spatial resolutions and the RF model at 2 m spatial resolution was superior for the present flood inventory and predictor variables. The majority of the models had a moderate performance for predictions outside the training area based on Kappa evaluation (minimum AUC = 0.8). Aspect and altitude were the most influencing factors on the image-based and point-based models respectively. Data-driven models can be a reliable tool for urban pluvial flood susceptibility mapping wherever a reliable flood inventory is available.},
  language  = {en}
}
@article{VormoorHeistermannBronstertetal.2018,
  author    = {Vormoor, Klaus Josef and Heistermann, Maik and Bronstert, Axel and Lawrence, Deborah},
  title     = {Hydrological model parameter (in)stability},
  series = {Hydrological sciences journal = Journal des sciences hydrologiques},
  volume    = {63},
  journal   = {Hydrological sciences journal = Journal des sciences hydrologiques},
  number    = {7},
  publisher = {Routledge, Taylor \& Francis Group},
  address   = {Abingdon},
  issn      = {0262-6667},
  doi       = {10.1080/02626667.2018.1466056},
  pages     = {991 -- 1007},
  year      = {2018},
  abstract  = {This paper investigates the transferability of calibrated HBV model parameters under stable and contrasting conditions in terms of flood seasonality and flood generating processes (FGP) in five Norwegian catchments with mixed snowmelt/rainfall regimes. We apply a series of generalized (differential) split-sample tests using a 6-year moving window over (i) the entire runoff observation periods, and (ii) two subsets of runoff observations distinguished by the seasonal occurrence of annual maximum floods during either spring or autumn. The results indicate a general model performance loss due to the transfer of calibrated parameters to independent validation periods of -5 to -17\%, on average. However, there is no indication that contrasting flood seasonality exacerbates performance losses, which contradicts the assumption that optimized parameter sets for snowmelt-dominated floods (during spring) perform particularly poorly on validation periods with rainfall-dominated floods (during autumn) and vice versa.},
  language  = {en}
}
@article{SeleemAyzelBronstertetal.2023,
  author    = {Seleem, Omar and Ayzel, Georgy and Bronstert, Axel and Heistermann, Maik},
  title     = {Transferability of data-driven models to predict urban pluvial flood water depth in Berlin, Germany},
  series = {Natural Hazards and Earth System Sciences},
  volume    = {23},
  journal   = {Natural Hazards and Earth System Sciences},
  number    = {2},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1684-9981},
  doi       = {10.5194/nhess-23-809-2023},
  pages     = {809 -- 822},
  year      = {2023},
  abstract  = {Data-driven models have been recently suggested to surrogate computationally expensive hydrodynamic models to map flood hazards. However, most studies focused on developing models for the same area or the same precipitation event. It is thus not obvious how transferable the models are in space. This study evaluates the performance of a convolutional neural network (CNN) based on the U-Net architecture and the random forest (RF) algorithm to predict flood water depth, the models' transferability in space and performance improvement using transfer learning techniques. We used three study areas in Berlin to train, validate and test the models. The results showed that (1) the RF models outperformed the CNN models for predictions within the training domain, presumable at the cost of overfitting; (2) the CNN models had significantly higher potential than the RF models to generalize beyond the training domain; and (3) the CNN models could better benefit from transfer learning technique to boost their performance outside training domains than RF models.},
  language  = {en}
}
@misc{PetrowHeistermannBronstert2017,
  author    = {Petrow, Theresia and Heistermann, Maik and Bronstert, Axel},
  title     = {Analysis of Flash Floods in Germany},
  series = {Hydrologie und Wasserbewirtschaftung},
  volume    = {61},
  journal   = {Hydrologie und Wasserbewirtschaftung},
  publisher = {Bundesanst. f{\"u}r Gew{\"a}sserkunde},
  address   = {Koblenz},
  issn      = {1439-1783},
  pages     = {212 -- 212},
  year      = {2017},
  language  = {en}
}
@misc{KneisAbonBronstertetal.2016,
  author    = {Kneis, David and Abon, Catherine Cristobal and Bronstert, Axel and Heistermann, Maik},
  title     = {Verification of short-term runoff forecasts for a small Philippine basin (Marikina)},
  series = {Hydrological sciences journal = Journal des sciences hydrologiques},
  volume    = {62},
  journal   = {Hydrological sciences journal = Journal des sciences hydrologiques},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {0262-6667},
  doi       = {10.1080/02626667.2016.1183773},
  pages     = {205 -- 216},
  year      = {2016},
  abstract  = {Storm runoff from the Marikina River Basin frequently causes flood events in the Philippine capital region Metro Manila. This paper presents and evaluates a system to predict short-term runoff from the upper part of that basin (380km(2)). It was designed as a possible component of an operational warning system yet to be installed. For the purpose of forecast verification, hindcasts of streamflow were generated for a period of 15 months with a time-continuous, conceptual hydrological model. The latter was fed with real-time observations of rainfall. Both ground observations and weather radar data were tested as rainfall forcings. The radar-based precipitation estimates clearly outperformed the raingauge-based estimates in the hydrological verification. Nevertheless, the quality of the deterministic short-term runoff forecasts was found to be limited. For the radar-based predictions, the reduction of variance for lead times of 1, 2 and 3hours was 0.61, 0.62 and 0.54, respectively, with reference to a no-forecast scenario, i.e. persistence. The probability of detection for major increases in streamflow was typically less than 0.5. Given the significance of flood events in the Marikina Basin, more effort needs to be put into the reduction of forecast errors and the quantification of remaining uncertainties.},
  language  = {en}
}
@article{AbonKneisCrisologoetal.2016,
  author    = {Abon, Catherine Cristobal and Kneis, David and Crisologo, Irene and Bronstert, Axel and David, Carlos Primo Constantino and Heistermann, Maik},
  title     = {Evaluating the potential of radar-based rainfall estimates for streamflow and flood simulations in the Philippines},
  series = {GEOMATICS NATURAL HAZARDS \& RISK},
  volume    = {7},
  journal   = {GEOMATICS NATURAL HAZARDS \& RISK},
  publisher = {Routledge, Taylor \& Francis Group},
  address   = {Abingdon},
  issn      = {1947-5705},
  doi       = {10.1080/19475705.2015.1058862},
  pages     = {1390 -- 1405},
  year      = {2016},
  abstract  = {This case study evaluates the suitability of radar-based quantitative precipitation estimates (QPEs) for the simulation of streamflow in the Marikina River Basin (MRB), the Philippines. Hourly radar-based QPEs were produced from reflectivity that had been observed by an S-band radar located about 90 km from the MRB. Radar data processing and precipitation estimation were carried out using the open source library wradlib. To assess the added value of the radar-based QPE, we used spatially interpolated rain gauge observations (gauge-only (GO) product) as a benchmark. Rain gauge observations were also used to quantify rainfall estimation errors at the point scale. At the point scale, the radar-based QPE outperformed the GO product in 2012, while for 2013, the performance was similar. For both periods, estimation errors substantially increased from daily to the hourly accumulation intervals. Despite this fact, both rainfall estimation methods allowed for a good representation of observed streamflow when used to force a hydrological simulation model of the MRB. Furthermore, the results of the hydrological simulation were consistent with rainfall verification at the point scale: the radar-based QPE performed better than the GO product in 2012, and equivalently in 2013. Altogether, we could demonstrate that, in terms of streamflow simulation, the radar-based QPE can perform as good as or even better than the GO product - even for a basin such as the MRB which has a comparatively dense rain gauge network. This suggests good prospects for using radar-based QPE to simulate and forecast streamflow in other parts of the Philippines where rain gauge networks are not as dense.},
  language  = {en}
}