Factors Controlling Contemporary Suspended Sediment Yield in the Caucasus Region

Golosov, Valentin; Tsyplenkov, Anatoly

doi:10.3390/w13223173

Cited by 12 publications

(5 citation statements)

References 106 publications

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“…High amounts of erosion also contribute to high sediment loads (Gwapedza et al, 2021), and also have negative effects on land and livelihoods, aquatic ecosystems, water availability, and power generation infrastructure (Bannatyne et al, 2022;Vercruysse et al, 2017). The contributions of climate change and human activities have a very significant effect on increasing erosion, surface runoff, and sediment in a watershed from year to year (Chen et al, 2022;Golosov and Tsyplenkov, 2021).…”

Section: Sediment Loadmentioning

confidence: 99%

Evaluation of Wanggu Watershed Carrying Capacity on Water System Indicators in Southeast Sulawesi, Indonesia

2023

indones. j. env. man. sus.

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The water system or hydrological indicators determine the good and bad of a watershed’s carrying capacity. The hydrological indicators include discharge fluctuations, annual flow coefficient, sediment load, flood frequency, and water use index. The purpose of this study was to evaluate the carrying capacity of the Wanggu watershed based on hydrological indicators. The method used is the score and weight method for all hydrological indicator data in accordance with the watershed evaluation guidelines for hydrological indicators. The research data is sourced from primary data and secondary data. Primary data comes from direct observation, while secondary data comes from agencies related to this research. Data analysis using Microsoft Excel in monthly and annual data analysis by producing tables and figures. The results of this study indicate that fluctuations in discharge or the regime coefficient of the Wanggu River Basin are 96.45 which are classified as high, as well as erosion and surface runoff, namely sediment load conditions of 19.73 which are also included in the high category. While the value of the annual flow coefficient is 0.32, the average frequency of flooding every year occurs once in two years and the water use index is 0.69. The three parameters are categorized as being in the middle class. From the accumulated weights and scores of all water system indicator parameters, a value of 111.25 is included in the bad class category. So the Wanggu watershed has a poor carrying capacity value from the water management indicator.

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Section: Sediment Loadmentioning

confidence: 99%

Evaluation of Wanggu Watershed Carrying Capacity on Water System Indicators in Southeast Sulawesi, Indonesia

2023

indones. j. env. man. sus.

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“…Previous sediment yield studies in the Caucasus region were primarily based on gauging station measurements (e.g., Golosov and Tsyplenkov, 2021;Mozzherin and Sharifullin, 2015) or cosmogenic 10 Be concentrations (Forte et al, 2022). For example, a Tsyplenkov et al ( 2019) study analysed area-specific sediment yields from 200 gages in the North and South Caucasus.…”

Section: Sediment Yieldmentioning

confidence: 99%

“…To meet the rising demand for food without compromising the ecosystem's health, there is an urgent need for sustainable intensification of agriculture to meet Sustainable Development Goal 2. However, soil erosion and sediment export from hillslopes are significant problems associated with agriculture, especially in parts of the world where society is already living in extreme environments, especially mountain regions such as the Caucasus (Forte et al, 2016;Golosov and Tsyplenkov, 2021;Perov et al, 2017;Vezzoli et al, 2020). At a river basin scale, soil erosion threatens food, water, and energy security due to the loss of productive soil and nutrients from hillslopes, pollution of downstream water bodies by sediment and contaminants (Ivanov et al, 2021), and siltation of hydropower dams and reservoirs (Hasholt et al, 2000;Syvitski et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…In particular, mountainous environments remain severely understudied, with only a few runoff and sediment transport measurements available (Vanmaercke et al, 2011). The low mountain topographic zone (500-1500 m) of the North Caucasus is not an exception (Golosov and Tsyplenkov, 2021). Historically, pastoralism and animal husbandry have been important forms of agriculture in the region (Holland, 2016;Hovsepyan, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…No matter the fact that the population density there is among the highest in the Great Caucasus region (Vinogradova et al, 2018), the gauging station density is low (Rets et al, 2020), especially the ones measuring sediment transport (Golosov and Tsyplenkov, 2021). The results from gauging measurements alone may not always indicate the regional SY patterns (Vanmaercke et al, 2012(Vanmaercke et al, , 2014.…”

Section: Introductionmentioning

confidence: 99%

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Precise sediment flux assessment of a small ungauged low-mountain catchment in the North Caucasus

Tsyplenkov

Kharchenko

Uspensky

et al. 2022

Preprint

Self Cite

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Soil erosion and sediment export from hillslopes are significant problems associated with agriculture, especially in parts of the world where society is already living in extreme environments. In particular, mountainous environments remain severely understudied, with only a few runoff and sediment transport measurements available. It is necessary, therefore, to develop and validate independent methods that do not rely on long-term observations at gauging stations. Here we used three independent methods to predict soil erosion and associated sediment yield (SY) from a 1.84 km² basin in the North Caucasus. The first part concerns assessing the sedimentation rate, which was made using in-situ measurements of volumetric sediment deposition rates. Secondly, we look at the connectivity of sediment sources and the lake. A combination of remote sensing data and field surveys was used to estimate sediment connectivity and erosion mapping. The third part regards the computation of soil erosion using the Revised Universal Soil Loss Equation (RUSLE). There are three major findings in this study that help us understand sediment redistribution patterns in mountainous areas. First, based on the lake sedimentation rate, we found that the mean annual area-specific sediment yield is 514 (95% CI, 249–839) t km− 2 yr− 1. Similar results were obtained from the erosion mapping (i.e., a map of erosion processes) — 428 (95% CI, 322–546) t km− 2 yr− 1. Secondly, the spatial distribution and rates of the erosion processes suggest that sheet and rill erosion are responsible for ca. 40% of total sediment export, slides and rockfalls — 18%, while the rest is removed by soil creep. Additionally, the RUSLE-based modelling of sheet wash and rill erosion has highlighted the areas most prone to soil erosion. The corresponding mean annual soil erosion rate of 1.59 mm yr− 1 was very close to the results obtained from the literature review.

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Modeling stage‐discharge and sediment‐discharge relationships in data‐scarce Himalayan River Basin Dhauliganga, Central Himalaya, using neural networks

Rautela,

Gupta,

Devi

et al. 2024

CLEAN Soil Air Water

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This study focuses on the hydro‐sedimentological characterization and modeling of the Dhauliganga River in Uttarakhand, India. Field data collected from 2018–2020, including stage, velocity, and suspended sediment concentration (SSC), showed notable variations influenced by melting snow, glaciers, and precipitation. Challenges in accurately modeling rivers with a topography and sparse gauging stations were addressed using artificial neural networks (ANN). The calibrated models precisely predicted stage‐discharge and sediment‐discharge relationships, demonstrating the effectiveness of machine learning, particularly ANN‐based modeling, in such challenging terrains. The model's performance was assessed using coefficient of determination (R2), root mean square error (RMSE), and mean square error (MSE). During the calibration phase, the model exhibited notable performance with R2 values of 0.96 for discharge and 0.63 for SSC, accompanied by low RMSE values of 5.29 cu m s–1 for discharge and 0.61 g for SSC. Subsequently, in the prediction phase, the model maintained its robustness, achieving R2 values of 0.97 for discharge and 0.63 for SSC, along with RMSE values of 5.67 cu m s–1 for discharge and 0.68 g for SSC. The study also found a strong agreement between water flow estimates derived from traditional methods, ANN, and actual measurements. The suspended sediment load, influenced by both water flow and SSC, varied annually, potentially modifying aquatic habitats through sediment deposition, and altering aquatic communities. These findings offer crucial insights into the hydro‐sedimentological dynamics of the studied river, providing valuable applications for sustainable water‐resource management in challenging terrains and addressing environmental concerns related to sedimentation, water quality, and aquatic ecosystem.

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Factors Controlling Contemporary Suspended Sediment Yield in the Caucasus Region

Cited by 12 publications

References 106 publications

Evaluation of Wanggu Watershed Carrying Capacity on Water System Indicators in Southeast Sulawesi, Indonesia

Evaluation of Wanggu Watershed Carrying Capacity on Water System Indicators in Southeast Sulawesi, Indonesia

Precise sediment flux assessment of a small ungauged low-mountain catchment in the North Caucasus

Modeling stage‐discharge and sediment‐discharge relationships in data‐scarce Himalayan River Basin Dhauliganga, Central Himalaya, using neural networks

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