TY  - JOUR
A1  - Kreibich, Heidi
A1  - Botto, Anna
A1  - Merz, Bruno
A1  - Schröter, Kai
T1  - Probabilistic, Multivariable Flood Loss Modeling on the Mesoscale with BT-FLEMO
JF  - Risk analysis
N2  - Flood loss modeling is an important component for risk analyses and decision support in flood risk management. Commonly, flood loss models describe complex damaging processes by simple, deterministic approaches like depth-damage functions and are associated with large uncertainty. To improve flood loss estimation and to provide quantitative information about the uncertainty associated with loss modeling, a probabilistic, multivariable Bagging decision Tree Flood Loss Estimation MOdel (BT-FLEMO) for residential buildings was developed. The application of BT-FLEMO provides a probability distribution of estimated losses to residential buildings per municipality. BT-FLEMO was applied and validated at the mesoscale in 19 municipalities that were affected during the 2002 flood by the River Mulde in Saxony, Germany. Validation was undertaken on the one hand via a comparison with six deterministic loss models, including both depth-damage functions and multivariable models. On the other hand, the results were compared with official loss data. BT-FLEMO outperforms deterministic, univariable, and multivariable models with regard to model accuracy, although the prediction uncertainty remains high. An important advantage of BT-FLEMO is the quantification of prediction uncertainty. The probability distribution of loss estimates by BT-FLEMO well represents the variation range of loss estimates of the other models in the case study.
KW  - Damage modeling
KW  - multiparameter
KW  - probabilistic
KW  - uncertainty
KW  - validation
Y1  - 2016
U6  - https://doi.org/10.1111/risa.12650
SN  - 0272-4332
SN  - 1539-6924
VL  - 37
IS  - 4
SP  - 774
EP  - 787
PB  - Wiley
CY  - Hoboken
ER  - 
TY  - JOUR
A1  - Dormann, Carsten F.
A1  - Schymanski, Stanislaus J.
A1  - Cabral, Juliano Sarmento
A1  - Chuine, Isabelle
A1  - Graham, Catherine
A1  - Hartig, Florian
A1  - Kearney, Michael
A1  - Morin, Xavier
A1  - Römermann, Christine
A1  - Schröder-Esselbach, Boris
A1  - Singer, Alexander
T1  - Correlation and process in species distribution models: bridging a dichotomy
JF  - Journal of biogeography
N2  - Within the field of species distribution modelling an apparent dichotomy exists between process-based and correlative approaches, where the processes are explicit in the former and implicit in the latter. However, these intuitive distinctions can become blurred when comparing species distribution modelling approaches in more detail. In this review article, we contrast the extremes of the correlativeprocess spectrum of species distribution models with respect to core assumptions, model building and selection strategies, validation, uncertainties, common errors and the questions they are most suited to answer. The extremes of such approaches differ clearly in many aspects, such as model building approaches, parameter estimation strategies and transferability. However, they also share strengths and weaknesses. We show that claims of one approach being intrinsically superior to the other are misguided and that they ignore the processcorrelation continuum as well as the domains of questions that each approach is addressing. Nonetheless, the application of process-based approaches to species distribution modelling lags far behind more correlative (process-implicit) methods and more research is required to explore their potential benefits. Critical issues for the employment of species distribution modelling approaches are given, together with a guideline for appropriate usage. We close with challenges for future development of process-explicit species distribution models and how they may complement current approaches to study species distributions.
KW  - Hypothesis generation
KW  - mechanistic model
KW  - parameterization
KW  - process-based model
KW  - species distribution model
KW  - SDM
KW  - uncertainty
KW  - validation
Y1  - 2012
U6  - https://doi.org/10.1111/j.1365-2699.2011.02659.x
SN  - 0305-0270
VL  - 39
IS  - 12
SP  - 2119
EP  - 2131
PB  - Wiley-Blackwell
CY  - Hoboken
ER  -