@article{GoetzKohrsParraHormazabaletal.2021,
  author    = {Goetz, Jason and Kohrs, Robin and Parra Hormaz{\´a}bal, Eric and Bustos Morales, Manuel and Araneda Riquelme, Mar{\´i}a Bel{\´e}n and Henr{\´i}quez Ruiz, Cristian and Brenning, Alexander},
  title     = {Optimizing and validating the Gravitational Process Path model for regional debris-flow runout modelling},
  series = {Natural hazards and earth system sciences : NHESS / European Geophysical Society},
  volume    = {21},
  journal   = {Natural hazards and earth system sciences : NHESS / European Geophysical Society},
  number    = {8},
  publisher = {European Geophysical Society},
  address   = {Katlenburg-Lindau},
  issn      = {1561-8633},
  doi       = {10.5194/nhess-21-2543-2021},
  pages     = {2543 -- 2562},
  year      = {2021},
  abstract  = {Knowing the source and runout of debris flows can help in planning strategies aimed at mitigating these hazards. Our research in this paper focuses on developing a novel approach for optimizing runout models for regional susceptibility modelling, with a case study in the upper Maipo River basin in the Andes of Santiago, Chile. We propose a two-stage optimization approach for automatically selecting parameters for estimating runout path and distance. This approach optimizes the random-walk and Perla et al.'s (PCM) two-parameter friction model components of the open-source Gravitational Process Path (GPP) modelling framework. To validate model performance, we assess the spatial transferability of the optimized runout model using spatial crossvalidation, including exploring the model's sensitivity to sample size. We also present diagnostic tools for visualizing uncertainties in parameter selection and model performance. Although there was considerable variation in optimal parameters for individual events, we found our runout modelling approach performed well at regional prediction of potential runout areas. We also found that although a relatively small sample size was sufficient to achieve generally good runout modelling performance, larger samples sizes (i.e. >= 80) had higher model performance and lower uncertainties for estimating runout distances at unknown locations. We anticipate that this automated approach using the open-source R software and the System for Automated Geoscientific Analyses geographic information system (SAGA-GIS) will make process-based debris-flow models more readily accessible and thus enable researchers and spatial planners to improve regional-scale hazard assessments.},
  language  = {en}
}
@article{MuellerKoszinskiBrenningetal.2011,
  author    = {Mueller, Marina Elsa Herta and Koszinski, Sylvia and Brenning, Alexander and Verch, Gernot and Korn, Ulrike and Sommer, Michael},
  title     = {Within-field variation of mycotoxin contamination of winter wheat is related to indicators of soil moisture},
  series = {Plant and soil},
  volume    = {342},
  journal   = {Plant and soil},
  number    = {1-2},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {0032-079X},
  doi       = {10.1007/s11104-010-0695-5},
  pages     = {289 -- 300},
  year      = {2011},
  abstract  = {Humidity is an important determinant of the mycotoxin production (DON, ZEA) by Fusarium species in the grain ears. From a landscape perspective humidity is not evenly distributed across fields. The topographically-controlled redistribution of water within a single field rather leads to spatially heterogeneous soil water content and air humidity. Therefore we hypothesized that the spatial distribution of mycotoxins is related to these topographically-controlled factors. To test this hypothesis we studied the mycotoxin concentrations at contrasting topographic relief positions, i.e. hilltops and depressions characterized by soils of different soil moisture regimes, on ten winter wheat fields in 2006 and 2007. Maize was the preceding crop and minimum tillage was practiced in the fields. The different topographic positions were associated with moderate differences in DON and ZEA concentrations in 2006, but with significant differences in 2007, with six times higher median ZEA and two times higher median DON detected at depression sites compared to the hilltops. The depression sites correspond to a higher topographic wetness index as well as redoximorphic properties in soil profiles, which empirically supports our hypothesis at least for years showing wetter conditions in sensitive time windows for Fusarium infections.},
  language  = {en}
}
@article{KuehnBrenningWehrhanetal.2009,
  author    = {K{\"u}hn, J{\"u}rgen and Brenning, Alexander and Wehrhan, Marc and Koszinski, Sylvia and Sommer, Michael},
  title     = {Interpretation of electrical conductivity patterns by soil properties and geological maps for precision agriculture},
  issn      = {1385-2256},
  doi       = {10.1007/s11119-008-9103-z},
  year      = {2009},
  abstract  = {Precision farming needs management rules to apply spatially differentiated treatments in agricultural fields. Digital soil mapping (DSM) tools, for example apparent soil electrical conductivity, corrected to 25A degrees C (EC25), and digital elevation models, try to explain the spatial variation in soil type, soil properties (e.g. clay content), site and crop that are determined by landscape characteristics such as terrain, geology and geomorphology. We examined the use of EC25 maps to delineate management zones, and identified the main factors affecting the spatial pattern of EC25 at the regional scale in a study area in eastern Germany. Data of different types were compared: EC25 maps for 11 fields, soil properties measured in the laboratory, terrain attributes, geological maps and the description of 75 soil profiles. We identified the factors that influence EC25 in the presence of spatial autocorrelation and field-specific random effects with spatial linear mixed-effects models. The variation in EC25 could be explained to a large degree (R (2) of up to 61\%). Primarily, soil organic matter and CaCO3, and secondarily clay and the presence of gleyic horizons were significantly related to EC25. Terrain attributes, however, had no significant effect on EC25. The geological map unit showed a significant relationship to EC25, and it was possible to determine the most important soil properties affecting EC25 by interpreting the geological maps. Including information on geology in precision agriculture could improve understanding of EC25 maps. The EC25 maps of fields should not be assumed to represent a map of clay content to form a basis for deriving management zones because other factors appeared to have a more important effect on EC25.},
  language  = {en}
}