FIRST DENUDATION RATE ESTIMATES FOR RIVER BASINS IN CENTRAL CUBA FROM GEOCHEMICAL, COSMOGENIC ISOTOPE, AND SEDIMENT YIELD DATA

AbstractMeasures of present-day glacial erosion vary widely with the technique employed. This paper quantifies the glacial material trapped in a proglacial lake during the Würm glacial period. The Combe d'Ain site was occupied by a meltwater lake where all the detrital material entering it from the Jura glacier accumulated. Sediment yield is computed from three factors: (1) the size of the sediment source area, (2) the length of time the system operated, and (3) the volume of sediment trapped. The sediment budget of the lake system suggests a detrital sediment yield of 4400±1700 metric tons per square kilometer and per calendar year. This represents a denudation rate of 1.6±0.6 mm per year, illustrating that mechanical erosion by the Jura glacier is more intensive than other processes of erosion.

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Sediment Load and Suspended Sediment Concentration Prediction

Soil and Water Research ◽

10.17221/6502-swr ◽

2013 ◽

Vol 1 (No. 1) ◽

pp. 23-31 ◽

Cited By ~ 2

Author(s):

Bečvář Martin

Keyword(s):

Suspended Sediment ◽

Sediment Yield ◽

Suspended Sediment Concentration ◽

Sediment Load ◽

Sediment Concentration ◽

River Basins ◽

River Systems ◽

Sediment Yields ◽

Suspended Sediment Concentrations ◽

Annual Sediment

Sediment is a natural component of riverine environments and its presence in river systems is essential. However, in many ways and many places river systems and the landscape have been strongly affected by human activities which have destroyed naturally balanced sediment supply and sediment transport within catchments. As a consequence a number of severe environmental problems and failures have been identified, in particular the link between sediments and chemicals is crucial and has become a subject of major scientific interest. Sediment load and sediment concentration are therefore highly important variables that may play a key role in environment quality assessment and help to evaluate the extent of potential adverse impacts. This paper introduces a methodology to predict sediment loads and suspended sediment concentrations (SSC) in large European river basins. The methodology was developed within an MSc research study that was conducted in order to improve sediment modelling in the GREAT-ER point source pollution river modelling package. Currently GREAT-ER uses suspended sediment concentration of 15 mg/l for all rivers in Europe which is an obvious oversimplification. The basic principle of the methodology to predict sediment concentration is to estimate annual sediment load at the point of interest and the amount of water that transports it. The amount of transported material is then redistributed in that corresponding water volume (using the flow characteristic) which determines sediment concentrations. Across the continent, 44 river basins belonging to major European rivers were investigated. Suspended sediment concentration data were collected from various European basins in order to obtain observed sediment yields. These were then compared against the traditional empiric sediment yield estimators. Three good approaches for sediment yield prediction were introduced based on the comparison. The three approaches were applied to predict annual sediment yields which were consequently translated into suspended sediment concentrations. SSC were predicted at 47 locations widely distributed around Europe. The verification of the methodology was carried out using data from the Czech Republic. Observed SSC were compared against the predicted ones which validated the methodology for SSC prediction.

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A Regression-Based Prediction Model of Suspended Sediment Yield in the Cuyahoga River in Ohio Using Historical Satellite Images and Precipitation Data

Water ◽

10.3390/w12030881 ◽

2020 ◽

Vol 12 (3) ◽

pp. 881 ◽

Cited By ~ 2

Author(s):

Richard Ampomah ◽

Hossein Hosseiny ◽

Lan Zhang ◽

Virginia Smith ◽

Kristin Sample-Lord

Keyword(s):

Land Cover ◽

Suspended Sediment ◽

Sediment Yield ◽

Flood Management ◽

Mean Annual Precipitation ◽

Ecological Processes ◽

Yield Data ◽

Suspended Sediment Yield ◽

Land Cover Data ◽

The Mean

Urbanization typically results in increased imperviousness which alters suspended sediment yield and impacts geomorphic and ecological processes within urban streams. Therefore, there is an increasing interest in the ability to predict suspended sediment yield. This study assesses the combined impact of urban development and increased precipitation on suspended sediment yield in the Cuyahoga River using statistical modeling. Historical satellite-based land-cover data was combined with precipitation and suspended sediment yield data to create a Multiple Linear Regression (MLR) model for the Cuyahoga watershed. An R2 value of 0.71 was obtained for the comparison between the observed and predicted results based on limited land-use and land-cover data. The model also shows that every 1 mm increase in the mean annual precipitation has the potential to increase the mean annual suspended sediment yield by 860 tons/day. Further, a 1 km2 increase in developed land area has the potential to increase mean annual suspended sediment yield by 0.9 tons/day. The framework proposed in this study provides decision makers with a measure for assessing the potential impacts of future development and climate alteration on water quality in the watershed and implications for stream stability, dam and flood management, and in-stream and near-stream infrastructure life.

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Soil erosion and sediment delivery in a mountain catchment under scenarios of land use change using a spatially distributed numerical model

Hydrology and Earth System Sciences ◽

10.5194/hess-16-1321-2012 ◽

2012 ◽

Vol 16 (5) ◽

pp. 1321-1334 ◽

Cited By ~ 54

Author(s):

L. C. Alatorre ◽

S. Beguería ◽

N. Lana-Renault ◽

A. Navas ◽

J. M. García-Ruiz

Keyword(s):

Land Use ◽

Soil Erosion ◽

Sediment Yield ◽

Model Calibration ◽

Global Optimum ◽

Model Parameters ◽

Sediment Delivery ◽

Yield Data ◽

Good Convergence ◽

Spatially Distributed

Abstract. Soil erosion and sediment yield are strongly affected by land use/land cover (LULC). Spatially distributed erosion models are of great interest to assess the expected effect of LULC changes on soil erosion and sediment yield. However, they can only be applied if spatially distributed data is available for their calibration. In this study the soil erosion and sediment delivery model WATEM/SEDEM was applied to a small (2.84 km2) experimental catchment in the Central Spanish Pyrenees. Model calibration was performed based on a dataset of soil redistribution rates derived from point 137Cs inventories, allowing capture differences per land use in the main model parameters. Model calibration showed a good convergence to a global optimum in the parameter space, which was not possible to attain if only external (not spatially distributed) sediment yield data were available. Validation of the model results against seven years of recorded sediment yield at the catchment outlet was satisfactory. Two LULC scenarios were then modeled to reproduce land use at the beginning of the twentieth century and a hypothetic future scenario, and to compare the simulation results to the current LULC situation. The results show a reduction of about one order of magnitude in gross erosion (3180 to 350 Mg yr−1) and sediment delivery (11.2 to 1.2 Mg yr−1 ha−1) during the last decades as a result of the abandonment of traditional land uses (mostly agriculture) and subsequent vegetation recolonization. The simulation also allowed assessing differences in the sediment sources and sinks within the catchment.

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Assessment of uncertainties in soil erosion and sediment yield estiamtes at ungauged basins: an application to the Garra River basin, India

10.5194/hess-2017-383 ◽

2017 ◽

Cited By ~ 1

Author(s):

Somil Swarnkar ◽

Anshu Malini ◽

Shivam Tripathi ◽

Rajiv Sinha

Keyword(s):

Soil Erosion ◽

River Basin ◽

Sediment Yield ◽

Uncertainty Propagation ◽

River Basins ◽

Large River ◽

Delivery Ratio ◽

Mountainous Region ◽

Ungauged Basins ◽

Sediment Delivery

Abstract. High soil erosion and excessive sediment load are serious problems in several Himalayan River basins. To apply mitigation procedures, precise estimation of soil erosion and sediment yield with associated uncertainties are needed. Here, Revised Universal Soil Loss Equation (RUSLE) and Sediment Delivery Ratio (SDR) equations are used to estimate the spatial pattern of soil erosion (SE) and sediment yield (SY) in the Garra River basin, a small Himalayan tributary of River Ganga. A methodology is proposed for quantifying and propagating uncertainties in SE, SDR and SY estimates. Expressions for uncertainty propagation are derived by first-order uncertainty analysis, making the method viable even for large river basins. The methodology is applied to investigate the relative importance of different RUSLE factors in estimating the magnitude and uncertainties of SE over two distinct morpho-climatic regimes of the Garra River basin, namely, upper mountainous region & lower alluvial plains. The results suggest that average SE in the basin falls in very high category (20.4 ± 4.1 t/ha/y) with higher values in the upper mountainous region (84.4 ± 13.9 t/ha/y) than in the lower alluvial plains (17.7 ± 3.6 t/ha/y). Furthermore, the topographic steepness (LS) and crop practice (CP) factors exhibit higher uncertainties than other RUSLE factors. The annual average SY is estimated at two locations in the basin – Nanak Sagar dam (NSD) for the period 1962–2008 and Husepur gauging station (HGS) for 1987–2002. The SY at NSD and HGS are estimated to be 8.0 ± 1.4 × 105 t/y and 7.9 ± 1.7 ×106 t/y, respectively, and the estimated 90 % confidence interval contains the observed values 6.4 × 105 t/y and 7.2 × 106 t/y. The study demonstrated the usefulness of the proposed methodology for quantifying uncertainty in SE and SY estimates at ungauged basins.

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A New Indicator to Better Represent the Impact of Landscape Pattern Change on Basin Soil Erosion and Sediment Yield in the Upper Reach of Ganjiang, China

Land ◽

10.3390/land10090990 ◽

2021 ◽

Vol 10 (9) ◽

pp. 990

Author(s):

Yongfen Zhang ◽

Nong Wang ◽

Chongjun Tang ◽

Shiqiang Zhang ◽

Yuejun Song ◽

...

Keyword(s):

Land Use ◽

Soil Erosion ◽

River Basin ◽

Landscape Metrics ◽

Landscape Pattern ◽

Sediment Yield ◽

River Basins ◽

Landscape Patterns ◽

Soil Erodibility ◽

Land Use Pattern

Landscape patterns are a result of the combined action of natural and social factors. Quantifying the relationships between landscape pattern changes, soil erosion, and sediment yield in river basins can provide regulators with a foundation for decision-making. Many studies have investigated how land-use changes and the resulting landscape patterns affect soil erosion in river basins. However, studies examining the effects of terrain, rainfall, soil erodibility, and vegetation cover factors on soil erosion and sediment yield from a landscape pattern perspective remain limited. In this paper, the upper Ganjiang Basin was used as the study area, and the amount of soil erosion and the amount of sediment yield in this basin were first simulated using a hydrological model. The simulated values were then validated. On this basis, new landscape metrics were established through the addition of factors from the revised universal soil loss equation to the land-use pattern. Five combinations of landscape metrics were chosen, and the interactions between the landscape metrics in each combination and their effects on soil erosion and sediment yield in the river basin were examined. The results showed that there were highly similar correlations between the area metrics, between the fragmentation metrics, between the spatial structure metrics, and between the evenness metrics across all the combinations, while the correlations between the shape metrics in Combination 1 (only land use in each year) differed notably from those in the other combinations. The new landscape indicator established based on Combination 4, which integrated the land-use pattern and the terrain, soil erodibility, and rainfall erosivity factors, were the most significantly correlated with the soil erosion and sediment yield of the river basin. Finally, partial least-squares regression models for the soil erosion and sediment yield of the river basin were established based on the five landscape metrics with the highest variable importance in projection scores selected from Combination 4. The results of this study provide a simple approach for quantitatively assessing soil erosion in other river basins for which detailed observation data are lacking.

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Predicting Impacts of Land Use and Climate Change on Erosion and Sediment Yield in River Basins Using SHETRAN

Handbook of Erosion Modelling ◽

10.1002/9781444328455.ch14 ◽

2011 ◽

pp. 263-288 ◽

Cited By ~ 9

Author(s):

J. C. Bathurst

Keyword(s):

Climate Change ◽

Land Use ◽

Sediment Yield ◽

River Basins

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Estimation of Potential Soil Erosion and Sediment Yield: A Case Study of the Transboundary Chenab River Catchment

Water ◽

10.3390/w13243647 ◽

2021 ◽

Vol 13 (24) ◽

pp. 3647

Author(s):

Muhammad Gufran Ali ◽

Sikandar Ali ◽

Rao Husnain Arshad ◽

Aftab Nazeer ◽

Muhammad Mohsin Waqas ◽

...

Keyword(s):

Soil Erosion ◽

Time Scales ◽

Environmental Degradation ◽

Sediment Yield ◽

Soil Loss ◽

European Space Agency ◽

River Basins ◽

Delivery Ratio ◽

River Catchment ◽

Chenab River

Near real-time estimation of soil loss from river catchments is crucial for minimizing environmental degradation of complex river basins. The Chenab river is one of the most complex river basins of the world and is facing severe soil loss due to extreme hydrometeorological conditions, unpredictable hydrologic response, and complex orography. Resultantly, huge soil erosion and sediment yield (SY) not only cause irreversible environmental degradation in the Chenab river catchment but also deteriorate the downstream water resources. In this study, potential soil erosion (PSE) is estimated from the transboundary Chenab river catchment using the Revised Universal Soil Loss Equation (RUSLE), coupled with remote sensing (RS) and geographic information system (GIS). Land Use of the European Space Agency (ESA), Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data, and world soil map of Food and Agriculture Organization (FAO)/The United Nations Educational, Scientific and Cultural Organization were incorporated into the study. The SY was estimated on monthly, quarterly, seasonal, and annual time-scales using sediment delivery ratio (SDR) estimated through the area, slope, and curve number (CN)-based approaches. The 30-year average PSE from the Chenab river catchment was estimated as 177.8, 61.5, 310.3, 39.5, 26.9, 47.1, and 99.1 tons/ha for annual, rabi, kharif, fall, winter, spring, and summer time scales, respectively. The 30-year average annual SY from the Chenab river catchment was estimated as 4.086, 6.163, and 7.502 million tons based on area, slope, and CN approaches. The time series trends analysis of SY indicated an increase of 0.0895, 0.1387, and 0.1698 million tons per year for area, slope, and CN-based approaches, respectively. It is recommended that the areas, except for slight erosion intensity, should be focused on framing strategies for control and mitigation of soil erosion in the Chenab river catchment.

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