@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 = {Effects ofWithin-Storm Variability on Allochthonous Flash Flooding: A Synthetic Study}, series = {Water}, volume = {15}, journal = {Water}, number = {4}, issn = {2073-4441}, doi = {10.3390/w15040645}, abstract = {Rainfall is a spatiotemporally variated process and one of the key elements to accurately capture both catchment runoff response and floodplain extents. Flash floods are the result of intense rainfall, typically associated to highly variable rain in both space and time, such as convective storms. In this work, the extent within-storm variability affects runoff and flooding is explored. The Kan catchment (Tehran, Iran) is used as base topography for the simulations. The allochthonous nature of floods in the catchment and how they interact with the effects of storm variability are further investigated. For this, 300 synthetic rainfall signals with different hyetograph variabilities are generated and imposed on a 1D/2D hydrodynamic model. Additionally, a set of simulations with different levels of spatial variability are performed. The results suggest that temporal and spatial variability affect the runoff response in different degrees. Peak discharge and hydrograph shapes, as well as flooded areas, are affected. The effect of storm temporal variability is shown to be significantly higher than storm spatial variability and storm properties such as return period, duration, and volume. Further on the influence of storm spatiotemporal variability on stream discharge and flood response is seen to be strongly dependent on the location within the drainage network at which it is assessed.}, language = {en} } @inproceedings{CaviedesVoulliemeHinz, author = {Caviedes-Voulli{\`e}me, Daniel and Hinz, Christoph}, title = {An ecohydrological model to explore topographic and rainfall variability effects on vegetation self-organisation}, series = {Computational Methods in Water Resources XXII (CMWR 2018), Bridging gaps between data, models, and predictions}, booktitle = {Computational Methods in Water Resources XXII (CMWR 2018), Bridging gaps between data, models, and predictions}, pages = {2}, language = {en} }