Advanced methods to investigate hydro‐morphological processes in open‐water environments

Haun, Stefan; Dietrich, Stephan

doi:10.1002/esp.5131

Cited by 5 publications

(2 citation statements)

References 132 publications

(155 reference statements)

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“…Morphological processes in rivers may have significant effects on both the environment and society [9], [10]. The evolution of the meanders could endanger the surrounding infrastructure, as happened in 1311 (2024) 012002 IOP Publishing doi:10.1088/1755-1315/1311/1/012002 2 the Babon River bend which is near the Dinar Indah Housing Complex, Meteseh, Tembalang, Semarang City, Central Java (Figure 1).…”

Section: Introductionmentioning

confidence: 99%

Flow patterns at river bends and its response to surrounding infrastructures

Pinasti,

Wijayanti,

Nurfaida

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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On January 6, 2023, high-intensity precipitation occurred in the Babon River watershed, causing the river overflow and flood in several areas. Severe impact in the surrounding area was observed, such as in the Dinar Indah Housing Complex. Hydrodynamic complexity around a river bend points out the importance of understanding the flow patterns at a river bend. Therefore, this study aimed to describe the flow pattern of the river bend and analyze its response to the surrounding infrastructure using the HEC-RAS 6.3 model. Furthermore, improvement to structural mitigation was also designed. Field observations were also conducted to gather field data on the flood impact. The model results indicate that the highest water level within the river bend is 1.9 m, and the highest velocity is 5.85 m/s, which is on the outer bend. A dyke was then planned to be about 3.75 meters high, accompanied by a retaining wall to protect the river bank using the interlocking permeable revetment (IPR). Dyke and retaining walls provide stability against shear, overturning, and collapse.

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Section: Introductionmentioning

confidence: 99%

Flow patterns at river bends and its response to surrounding infrastructures

Pinasti,

Wijayanti,

Nurfaida

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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“…The observed topographic change for comparison with modeled topographic change stems from topographic data in the form of digital elevation models (DEMs). The precision and availability of DEMs have increased exponentially in recent years due to advances in remote sensing, such as airborne survey techniques, combined with ground-based and boat-based data recordings (Gruen, 2008;Haun & Dietrich, 2021;Marcus & Fonstad, 2008;Notebaert et al, 2009;Pajares, 2015). The comparison of two DEMs at two different times constitutes a DEM of difference (DoD) (Milan et al, 2007) with variable observation uncertainty that is accounted for in the procedure of producing a DoD (Wheaton et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Fuzzy map comparisons enable objective hydro‐morphodynamic model validation

Negreiros

Schwindt

Haun

et al. 2021

Earth Surf Processes Landf

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Numerical modeling represents a state-of-the-art technique to simulate hydromorphodynamic processes in river ecosystems. Numerical models are often validated based on observed topographic change in the form of pixel information on net erosion or deposition over a simulation period. When model validation is performed by a pixel-by-pixel comparison of exactly superimposed simulated and observed pixels, zero or negative correlation coefficients are often calculated, suggesting poor model performance. Thus, a pixel-by-pixel approach penalizes quantitative simulation errors, even if a model conceptually works well. To distinguish between reasonably wellperforming and non-representative models, this study introduces and tests fuzzy map comparison methods. First, we use a fuzzy numerical map comparison to compensate for spatial offset errors in correlation analyses. Second, we add a level of fuzziness with a fuzzy kappa map comparison to additionally address quantitative inaccuracy in modeled topographic change by categorizing data. Sample datasets from a physical lab model and datasets from a 6.9 km long gravel-cobble bed river reach enable the verification of the relevance of fuzzy map comparison methods.The results indicate that a fuzzy numerical map comparison is a viable technique to compensate for model errors stemming from spatial offset. In addition, fuzzy kappa map comparisons are suitable for objectively expressing subjectively perceived correlation between two maps, provided that a small number of categories is used. The methods tested and the resulting spatially explicit comparison maps represent a significant opportunity to improve the evaluation and potential calibration of numerical models of river ecosystems in the future.

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Introducing seasonal snow memory into the RUSLE

et al. 2022

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Purpose The sediment supply to rivers, lakes, and reservoirs has a great influence on hydro-morphological processes. For instance, long-term predictions of bathymetric change for modeling climate change scenarios require an objective calculation procedure of sediment load as a function of catchment characteristics and hydro-climatic parameters. Thus, the overarching objective of this study is to develop viable and objective sediment load assessment methods in data-sparse regions. Methods This study uses the Revised Universal Soil Loss Equation (RUSLE) and the SEdiment Delivery Distributed (SEDD) model to predict soil erosion and sediment transport in data-sparse catchments. The novel algorithmic methods build on free datasets, such as satellite and reanalysis data. Novelty stems from the usage of freely available datasets and the introduction of a seasonal snow memory into the RUSLE. In particular, the methods account for non-erosive snowfall, its accumulation over months as a function of temperature, and erosive snowmelt months after the snow fell. Results Model accuracy parameters in the form of Pearson’s r and Nash–Sutcliffe efficiency indicate that data interpolation with climate reanalysis and satellite imagery enables viable sediment load predictions in data-sparse regions. The accuracy of the model chain further improves when snow memory is added to the RUSLE. Non-erosivity of snowfall makes the most significant increase in model accuracy. Conclusion The novel snow memory methods represent a major improvement for estimating suspended sediment loads with the empirical RUSLE. Thus, the influence of snow processes on soil erosion and sediment load should be considered in any analysis of mountainous catchments.

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Advanced methods to investigate hydro‐morphological processes in open‐water environments

Cited by 5 publications

References 132 publications

Flow patterns at river bends and its response to surrounding infrastructures

Flow patterns at river bends and its response to surrounding infrastructures

Fuzzy map comparisons enable objective hydro‐morphodynamic model validation

Introducing seasonal snow memory into the RUSLE

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