@misc{KhoshBinGhomashBachmannCaviedesVoulliemeetal., author = {Khosh Bin Ghomash, Shahin and Bachmann, Daniel and Caviedes-Voulli{\`e}me, Daniel and Hinz, Christoph}, title = {Impact of Rainfall Movement on Flash Flood Response: A Synthetic Study of a Semi-Arid Mountainous Catchment}, series = {Water}, volume = {14}, journal = {Water}, number = {12}, issn = {2073-4441}, doi = {10.3390/w14121844}, abstract = {Rainfall is a spatiotemporally varied process and key to accurately capturing catchment runoff and determining flood response. Flash flood response of a catchment can be strongly governed by a rainfall's spatiotemporal variability and is influenced by storm movement which drives a continuous spatiotemporal change throughout a rainfall event. In this work, the sensitivity of runoff and flooded areas to rainfall movement are assessed in the Kan catchment (Iran). The allochthonous nature of floods in the catchment and how they interact with the effects of rainfall movement are investigated. Fifty synthetic rain hyetographs are generated and traversed over the catchment under different velocities and directions and used to force a 1D/2D hydrodynamic model. The results suggest rainfall movement affects the runoff response in different degrees. Peak discharge, hydrograph shapes and flooded areas are affected. Storms with higher velocities result in higher peaks and faster onsets of runoff and consequently higher flooded areas in comparison to slower storms. The direction of the movement also plays a role. Storms moving along the average direction of the stream result in higher peaks and flooded areas. The relevance of storm direction is greater for slow moving storms. Additionally, the influence of rainfall movement is modulated by hyetograph structure, and the allochthonous behavior is greatly dependent on the location within the drainage network at which it is assessed.}, language = {en} } @misc{KhoshBinGhomashBachmannCaviedesVoulliemeetal., author = {Khosh Bin Ghomash, Shahin and Bachmann, Daniel and Caviedes-Voulli{\`e}me, Daniel and Hinz, Christoph}, title = {Storm movement effects on the flash flood response of the Kan catchment}, series = {EGU General Assembly 2022, Vienna, Austria, 23-27 May 2022}, journal = {EGU General Assembly 2022, Vienna, Austria, 23-27 May 2022}, doi = {10.5194/egusphere-egu22-2494}, abstract = {Rainfall is a complex, spatial and temporally variated process and one of the core inputs for hydrological and hydrodynamic modelling. Most rainfalls are known to be moving storms with varying directions and velocities. Storm movement is known to be an important influence on runoff generation, both affecting peak discharge and the shape of hydrographs. Therefore, exploring the extent rainfall dynamics affect runoff generation and consequently flooded areas, can be an asset in effective flood risk management. In this work, we study how storm movement (e.g. characterized by velocity and direction) can affect surface flow generation, water levels and flooded areas within a catchment. Moreover, the influence of rainfall temporal variability in correlation with storm movement is taken into account. This is achieved by means of numerical-based, spatially explicit surface flow simulations using the tool ProMaIDes (2021), a free software for risk-based evaluation of flood risk mitigation measures. The storm events are generated using a microcanonical random cascade model and further on trajected across the catchment area. The study area is the Kan river catchment located in the province of Tehran (Iran) with a total area of 836 km², which has experienced multiple flooding events in recent years. Due to its semi-arid climate, steep topography with narrow valleys, this area has high potential for flash flood occurrence as a result of high intensity precipitation. The results of this study show a range of possible magnitudes of influence of rainfall movement on the catchment´s runoff response. The resulting flood maps highlight the importance of rainfall velocity and most importantly the direction of the movement in the estimation of flood events as well as their likelihood in catchment area. Moreover, its shown that the magnitude of influence of storm velocity and direction on discharge strongly depends on the location within the river network which it is measured.}, language = {en} } @misc{KaestnerCaviedesVoulliemeFrechenetal., author = {K{\"a}stner, Karl and Caviedes-Voullieme, Daniel and Frechen, Tobias Nanu and Hinz, Christoph}, title = {Theory and empirical evidence for the irregularity of self-organized vegetation patterns}, series = {EGU General Assembly 2022, Vienna, Austria, 23-27 May 2022}, journal = {EGU General Assembly 2022, Vienna, Austria, 23-27 May 2022}, doi = {10.5194/egusphere-egu22-11905}, abstract = {In arid environments, vegetation tends to self-organize into patches separated by bare soil. This is necessitated by the lack of water for sustaining a continuous vegetation cover and facilitated by the attraction of water from barren interpatch areas by the vegetation. This process is a positive feedback which introduces spatially heterogeneity into otherwise homogeneous environments, characterised by regular patterns. These patterns are typically considered to be periodic and distinguished on hand of their wavelength. Such patterns have so far been studied with numerical models which generate periodic patterns in homogeneous environments. However, environments are rarely homogeneous, as topography and soil-hydraulic properties vary in space. This raises the questions to which degree heterogeneity of vegetation is self-organized or imposed by the environment, and how environmental heterogeneity interacts with the self-organization process. In contrast to the persisting conceptual model of periodic patterns, natural vegetation exhibit a high degree of irregularity. Several studies have linked this irregularity to heterogeneity in the environment, but a comprehensive theory for analysing the irregularity has not yet been established. Furthermore remains the extend of irregularity unexplored on a global scale. To fill this gap, we, demonstrate empirically the global prevalence of irregularity in vegetation patterns and find that natural vegetation patterns are stochastic, rather than periodic. We then propose a stochastic framework to conceptually describe and measure the regularity, based on the spectral density of the patterns. In addition to the dominant wavelength, measuring the spatial scale, it reveals a novel parameter, measuring the regularity. The parameter is determined by the correlation structure and discriminates gradually between the limit cases of periodicity and white noise. Applied to natural and computer-generated patterns, we find that the former are highly irregular, while the latter are close to periodic. We reproduce the stochasticity of patterns with numerical models by introducing spatial heterogeneity of the model coefficients. We provide a fresh look at the nature of vegetations patterns and present a comprehensive theory for a more holistic understanding of self-organized systems.}, language = {en} }