Channel processes of a large alluvial river under human impacts

Amissah, Gabriel J.

doi:10.14232/phd.10425

Cited by 3 publications

(6 citation statements)

References 299 publications

(477 reference statements)

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“…Its entrance nozzle is 7.6 cm × 7.6 cm sized, and the sediment is collected in a sample bag (250 µm-mesh), thus it can trap medium sand or coarser sediments. Sampling was done applying 60 s sampling durations, as in a previous study (Amissah 2020) it was found to be the most effective. Simultaneously, an acoustic Doppler current profiler (ADCP) was also used across the transect to measure the mean velocity and water depth, while the water stage was read at the fluviometer at Makó on each sampling day.…”

Section: Methodsmentioning

confidence: 99%

Bedload transport measurements on the Maros river, Hungary

Kiss¹,

Amissah²,

Mezősi³

et al. 2021

Landsc. environ.

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Sediment transport is a vital component in hydrological and fluvial geomorphological studies, however, the temporal and spatial changes in sediment fluxes, and the efficiency of bedload samplers are rarely analysed, as bedload measurements are quite difficult. The aim of the present study is to measure the bedload transport of the sand-bedded Maros River (Hungary) at low stages using the Helley-Smith bedload sampler. In order to understand the variability in the bedload transport, the water stage and discharge across the channel section were also measured. The variability of the bedload was caused by an active in-channel bar and translational sediment pulses. The created bedload transport rating curve could be applied just below 300 m3/s water discharge thus further measurements are needed to evaluate the bedload transport of higher discharges.

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Section: Methodsmentioning

confidence: 99%

Bedload transport measurements on the Maros river, Hungary

Kiss¹,

Amissah²,

Mezősi³

et al. 2021

Landsc. environ.

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“…The Tisza River is the longest tributary (962 km) of the Danube [16], and its catchment area (157,200 km 2 ) covers 19.5% of the Danube's catchment area [61]. The Maros/Mures River is the greatest tributary of the Tisza (length: 750 km; catchment area: 30,000 km 2 ) and one of the most dynamic rivers of the Carpathian Basin [62]. The study was performed at their confluence area (Figure 1).…”

Section: Study Areamentioning

confidence: 99%

“…The flood of the Maros usually precedes the flood of the Tisza by a few days; however, they could also occur simultaneously during long-lasting floods [64]. As a result of their low slope conditions, they could be impounded by the Danube or each other [47,62]. Usually both rivers have a flood period in early spring (March-April) caused by snowmelt and in early summer (June-July) due to summer rainfall.…”

Section: Study Areamentioning

confidence: 99%

“…Usually both rivers have a flood period in early spring (March-April) caused by snowmelt and in early summer (June-July) due to summer rainfall. Usually, the early spring flood conveys more discharge (15% of the annual transported water [65] and sediment) than the early summer flood [16,62]. Sometimes the summer flood superimposes the spring flood (e.g., in 2006) because of the low slope (2.9 cm/km; [16,66]) on the long lowland section of the Tisza River, which results in high flood waves [62].…”

Section: Study Areamentioning

confidence: 99%

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Remote Sensing of Sediment Discharge in Rivers Using Sentinel-2 Images and Machine-Learning Algorithms

2022

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The spatio-temporal dynamism of sediment discharge (Qs) in rivers is influenced by various natural and anthropogenic factors. Unfortunately, most rivers are only monitored at a limited number of stations or not gauged at all. Therefore, this study aims to provide a remote-sensing-based alternative for Qs monitoring. The at-a-station hydraulic geometry (AHG) power–law method was compared to the at-many-stations hydraulic geometry (AMHG) method; in addition, a novel AHG machine-learning (ML) method was introduced to estimate water discharge at three gauging stations in the Tisza (Szeged and Algyő) and Maros (Makó) Rivers in Hungary. The surface reflectance of Sentinel-2 images was correlated to in situ suspended sediment concentration (SSC) by support vector machine (SVM), random forest (RF), artificial neural network (ANN), and combined algorithms. The best performing water discharge and SSC models were employed to estimate the Qs. Our novel AHG ML method gave the best estimations of water discharge (Szeged: R2 = 0.87; Algyő: R2 = 0.75; Makó: R2 = 0.61). Furthermore, the RF (R2 = 0.9) and combined models (R2 = 0.82) showed the best SSC estimations for the Maros and Tisza Rivers. The highest Qs were detected during floods; however, there is usually a clockwise hysteresis between the SSC and water discharge, especially in the Tisza River.

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“…The aims are to (1) evaluate the total amount (GSB) of eroded and trapped material along the 243 km long reach of the Middle Tisza (Hungary) during the last 180 years; (2) to calculate the net SB (NSB) changes; (3) to highlight the periods and locations of active sediment sources or sinks; and finally (4) to evaluate the role of various human impacts on long-term SB changes. The mean bankfull depth of the Tisza is rapidly changing (11.5-21.5 m) spatiotemporally [31]; thus, to avoid considerable errors, the areal approach of Wishart et al [17] was followed, and the depth was not considered in the SB calculations.…”

Section: Introductionmentioning

confidence: 99%

Reconstruction of a Long-Term, Reach-Scale Sediment Budget Using Lateral Channel Movement Data as a Proxy: A Case Study on the Lowland Section of the Tisza River, Hungary

Kiss,

Tóth,

Török

et al. 2024

Hydrology

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Humans have influenced the sediment transport of rivers on a centurial scale. Our goal was to use the rate of lateral channel processes as a proxy to reconstruct sediment budget (SB) changes of a lowland river (Middle Tisza, Hungary) on a historical scale (1838–2017). The gross sediment budget (GSB) refers to the total area of eroded and accumulated surfaces, and the net sediment budget (NSB) indicates the sediment sink or source characteristics. At the beginning (1838–1890), the artificial cut-offs increased the slope and channel erosion, but the eroded sediment deposited in the oxbows, so the reach acted as a sediment sink (NSB: +0.1–0.8 m2/m/y). Then (1890–1929), a quasi-equilibrium state developed (NSB: −0.2 m2/m/y to +0.4 m2/m/y). Later (1929–1976), the bank protections impeded lateral erosion, so the system became a sediment sink again (NSB: +0.1–0.7 m2/m/y). Finally (1976–2017), the erosional processes accelerated due to dam construction and revetment collapses, and now the river is a sediment source (NSB: −0.03 to −0.08 m2/m/y). This study proved that (1) the actual SB could not be projected in the long term, as it was heavily modified, and (2) lateral channel changes could be used as a proxy to estimate long-term SB.

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Channel processes of a large alluvial river under human impacts

Cited by 3 publications

References 299 publications

Bedload transport measurements on the Maros river, Hungary

Bedload transport measurements on the Maros river, Hungary

Remote Sensing of Sediment Discharge in Rivers Using Sentinel-2 Images and Machine-Learning Algorithms

Reconstruction of a Long-Term, Reach-Scale Sediment Budget Using Lateral Channel Movement Data as a Proxy: A Case Study on the Lowland Section of the Tisza River, Hungary

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