@misc{KaestnerHinzCaviedesVoulliemeetal., author = {K{\"a}stner, Karl and Hinz, Christoph and Caviedes-Voulli{\`e}me, Daniel and Frechen, Tobias Nanu and Vijsel, Roeland C. van de}, title = {A metaanalysis of the regularity of environmental spatialpatterns and a theory relating them to stochastic processes}, series = {EGU General Assembly 2023, Vienna, Austria, 24-28 Apr 2023}, journal = {EGU General Assembly 2023, Vienna, Austria, 24-28 Apr 2023}, doi = {10.5194/egusphere-egu23-5817}, language = {en} } @misc{ShlewetCaviedesVoulliemeKaestneretal., author = {Shlewet, Marlin and Caviedes-Voulli{\`e}me, Daniel and K{\"a}stner, Karl and Hinz, Christoph}, title = {Effects of urban structures on spatial and temporal flood distribution}, series = {EGU General Assembly 2023, Vienna, Austria, 24-28 Apr 2023}, journal = {EGU General Assembly 2023, Vienna, Austria, 24-28 Apr 2023}, doi = {10.5194/egusphere-egu23-9498}, language = {en} } @misc{ShlewetKaestnerCaviedesVoulliemeetal., author = {Shlewet, Marlin and K{\"a}stner, Karl and Caviedes-Voulli{\`e}me, Daniel and Hinz, Christoph}, title = {Einfluss urbaner Strukturen auf die r{\"a}umliche und zeitliche Dynamik pluvialer Fluten}, series = {Abstract-Band, Tag der Hydrologie 2023, Nachhaltiges Wassermanagement - Regionale und Globale Strategien, 22. \& 23.03.2023, Ruhr-Universit{\"a}t Bochum \& Hochschule Bochum}, journal = {Abstract-Band, Tag der Hydrologie 2023, Nachhaltiges Wassermanagement - Regionale und Globale Strategien, 22. \& 23.03.2023, Ruhr-Universit{\"a}t Bochum \& Hochschule Bochum}, language = {de} } @misc{KaestnerVijselCaviedesVoulliemeetal., author = {K{\"a}stner, Karl and Vijsel, Roeland C. van de and Caviedes-Voulli{\`e}me, Daniel and Hinz, Christoph}, title = {Unravelling the spatial structure of regular environmental spatial patterns}, series = {EGU General Assembly 2024, Vienna, Austria \& Online, 14-19 April 2024}, journal = {EGU General Assembly 2024, Vienna, Austria \& Online, 14-19 April 2024}, publisher = {Copernicus GmbH}, doi = {10.5194/egusphere-egu24-3412}, abstract = {Spatial patterns where patches of high biomass alternate with bare ground occur in many resource-limited ecosystems. Especially fascinating are regular patterns, which are self-similar at a lag distance corresponding to the typical distance between patches. Regular patterns are understood to form autogenously through self-organization, which can be generated with deterministic reaction-diffusion models. Such models generate highly regular patterns, which repeat at the characteristic wavelength and are therefore periodic. Natural patterns do not repeat, as they are noisy and as the patch size and spacing vary. Natural patterns are therefore usually perceived as perturbed periodic patterns. However, the self-similarity of natural patterns decreases at longer lag distances, which indicates that their spatial structure is not a perturbed periodic structure originating through deterministic processes. Here, we provide an overview of our recent work on the spatial structure and formation of natural environmental spatial patterns as a basis for discussion: First, we develop a statistical periodicity test and compile a large dataset of more than 10,000 regular environmental spatial patterns. We find that neither isotropic (spotted) nor anisotropic (banded) patterns are periodic. Instead, we find that their spatial structure can be well described as random fields originating through stochastic processes. Second, we recognize the regularity as a gradually varying property, rather than a dichotomous property of being periodic or not. We develop a method for quantifying the regularity and apply it in a metastudy to a set of natural and model-generated patterns found in the literature. We find that patterns generated with deterministic reaction-diffusion models do not well reproduce the spatial structure of environmental spatial structure, as they are too regular. Third, we develop an understanding of pattern formation through stochastic reaction-diffusion processes, which incorporate random environmental heterogeneities. We find that regular patterns form through filtering of the environmental heterogeneities and identify stochastic processes which reproduce both isotropic and anisotropic patterns.}, language = {en} } @misc{KhoshBinGhomashBachmannCaviedesVoulliemeetal., author = {Khosh Bin Ghomash, Shahin and Bachmann, Daniel and Caviedes-Voulli{\`e}me, Daniel and Hinz, Christoph}, title = {Introducing a dynamic spatiotemporal rainfall generator for flood risk analysis}, series = {EGU General Assembly 2023, Vienna, Austria, 24-28 Apr 2023}, journal = {EGU General Assembly 2023, Vienna, Austria, 24-28 Apr 2023}, doi = {10.5194/egusphere-egu23-2599}, abstract = {Precipitation scenario analysis is a crucial step in flood risk assessment, in which storm events with different probabilities are defined and used as input for the hydrological/hydrodynamic calculations. Rainfall generators may serve as a basis for the precipitation analysis. With the increase in the use of high resolution spatially-explicit hydrological/hydrodynamic models in flood risk calculations, demand for synthetic gridded precipitation input is increasing. In this work, we present a dynamic spatiotemporal rainfall generator. The model is capable of generating catchment-scale rainfields containing moving storms, which enable physically-plausible and spatiotemporally coherent precipitation events. This is achieved by the tools event-based approach, where dynamic storms are identified as clusters of related data that occur at different locations in space and time, and are then used as basis for event regeneration. The implemented methodology, mainly inspired by Dierden et al. (2019), provides an improvement in the spatial coherence of precipitation extremes, which can in turn be beneficial in flood risk calculations. The model has been validated under different databases such as the radar-based RADALON dataset or spatially-interpolated historical raingauge timeseries of different catchments in Germany, which is also presented in this work. The validation indicates the models ability to adequately preserve observed storm statistics in the generated timeseries. The generator is developed as an extension to the state-of-the-science flood risk modelling tool ProMaIDes (Promaides 2023). The model also puts great focus on user accessibility with offering features such as an easy installation process, support for most operating systems, a user interface and an online user manual.}, language = {en} } @misc{MaurerCaviedesVoulliemeGerkeetal., author = {Maurer, Thomas and Caviedes-Voulli{\`e}me, Daniel and Gerke, Horst H. and Hinz, Christoph}, title = {A 3D-spatial approach for modeling soil hydraulic property distributions on the artificial Huehnerwasser catchment}, series = {Geophysical Research Abstracts}, volume = {21}, journal = {Geophysical Research Abstracts}, pages = {1}, abstract = {Knowledge of catchment 3D spatial heterogeneity is crucial for the assessment and modeling of eco-hydrological processes. Especially during the initial development phase of a hydro-geo-system, the primary structural properties have the potential to determine further development pathways. Small-scale heterogeneity (cm to m scale) may have significant effects on processes on larger spatial scales, but is difficult to measure and quantify. The H{\"u}hnerwasser (Chicken Creek) catchment offers the unique opportunity to study early ecosystem development within an initial structural setup that is well-known, from the plot up to the catchment scale. Based on information on the open-cast mining technology, catchment boundaries and sediment properties, we developed a structure generator program for the process-based modeling of specific dumping structures and sediment property distributions on the catchment. The structure generator reproduces the trajectories of spoil ridges and can be conditioned to reproduce actual sediment distributions according to remote sensing and soil sampling data. Alternatively, sediment distribution scenarios can be generated based on geological data from the excavation site, or can be distributed stochastically. Using pedotransfer functions, the effective hydraulic van-Genuchten parameters are then calculated from sediment texture and bulk density. The main application of the 3D catchment model is to provide detailed 3D-distributed flow domain information for hydrological flow modeling. Observation data are available from catchment monitoring are available for determining the boundary conditions (e.g., precipitation), and the calibration / validation of the model (catchment discharge, ground water). The analysis of multiple sediment distribution scenarios allows to evaluate the effect of initial conditions on hydrological behavior development. Generally, the modeling approach can be used to pinpoint the influx of specific soil structural features on ecohydrological processes across spatial scales.}, language = {en} }