Human impact on sediment fluxes within the Blue Nile and Atbara River basins

Balthazar, Vincent; Vanacker, Veerle; Girma, Atkilt; Poesen, Jean; Golla, Semunesh

doi:10.1016/j.geomorph.2012.10.013

Cited by 55 publications

(42 citation statements)

References 50 publications

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“…This is illustrated by a few regional or country-wide SY compilations in Africa (e.g. Dunne, 1979;Rooseboom, 1978, Nyssen et al, 2004Liénou et al, 2005;Balthazar et al, 2012). Whereas these compilation studies are an important step forward, a comprehensive continent-wide compilation of African SY data is currently lacking.…”

Section: Introductionmentioning

confidence: 99%

“…Some models have been proposed to predict SY for specific African regions, but they are mostly based on a relatively limited number of catchments and involve large uncertainties when applied to catchments in other regions (e.g. Picouet et al, 2001;Ning Ma, 2006;Haregeweyn et al, 2008;Meshesha et al, 2011;Schmengler, 2011;Balthazar et al, 2012). Furthermore, these studies focus on only a few specific African regions (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Sediment yield in Africa

Vanmaercke

Poesen

Broeckx

et al. 2014

Earth-Science Reviews

Self Cite

141

142

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Several studies have compiled and analyzed measured contemporary catchment sediment yield (SY, [t km -2 y -1 ]) values for various regions of the world. Although this has significantly contributed to our understanding of SY, Africa remains severely underrepresented in these studies. The objective of this article is therefore: i) to review and compile available SY data for Africa; ii) to explore the spatial variability of these SY data; and iii) to examine which environmental factors explain this spatial variability.A literature review resulted in a dataset of SY measurements for 682 African catchments from 84 publications and reports, representing more than 8,340 catchment-years of observations.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sediment yield in Africa

Vanmaercke

Poesen

Broeckx

et al. 2014

Earth-Science Reviews

Self Cite

141

142

View full text Add to dashboard Cite

show abstract

“…Several authors have shown the effectiveness of statistical relationships, which allow one to estimate river sediment transport depending on easily available geomorphologic, hydrological and climatic parameters [1,[18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33]. Sediment yield is controlled by factors that control erosion and sediment delivery, including local topography, soil properties, climate, vegetation cover, catchment morphology, drainage network characteristics and land use [26,28].…”

Section: Introductionmentioning

confidence: 99%

Principal Component and Multiple Regression Analyses for the Estimation of Suspended Sediment Yield in Ungauged Basins of Northern Thailand

Wuttichaikitcharoen

Babel

2014

Water

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Predicting sediment yield is necessary for good land and water management in any river basin. However, sometimes, the sediment data is either not available or is sparse, which renders estimating sediment yield a daunting task. The present study investigates the factors influencing suspended sediment yield using the principal component analysis (PCA). Additionally, the regression relationships for estimating suspended sediment yield, based on the selected key factors from the PCA, are developed. The PCA shows six components of key factors that can explain at least up to 86.7% of the variation of all variables. The regression models show that basin size, channel network characteristics, land use, basin steepness and rainfall distribution are the key factors affecting sediment yield. The validation of regression relationships for estimating suspended sediment yield shows the error of estimation ranging from −55% to +315% and −59% to +259% for suspended sediment yield and for area-specific suspended sediment yield, respectively. The proposed relationships may be considered useful for predicting suspended sediment yield in ungauged basins of Northern Thailand that have geologic, climatic and hydrologic conditions similar to the study area.

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“…Land-use management practices (e.g., urbanization, changes in land use, land management and agricultural practices), changes in water management practices (e.g., dam constructions or demolition, streamflow regulation, introduction of flood control mechanisms) and river sand mining are the most prominent human-induced drivers that affect fluvial sediment supply [7,12,13,15,18]. Owing to the aforementioned factors, human activities have simultaneously increased catchment sediment yield via accelerated soil erosion, yet, have also significantly reduced the amount of sediment received by the coasts due to retention within reservoirs [3,7,13,15,16,[20][21][22]]. …”

Section: Factors Affecting Fluvial Sediment Supply To Coastsmentioning

confidence: 99%

“…Instead of using countrywide estimates of GNP/capita and population density to estimate the human-induced soil erosion factor (E h ), high-resolution spatial information published by [24] in the form of a human footprint index (HFPI) is used in this study, so that the anthropogenic influences on sedimentation is better represented [21,23]. The human footprint index is developed by using several global datasets such as population distribution, urban areas, roads, navigable rivers, electrical infrastructures and agricultural land use [25].…”

Section: Assessment Of Fluvial Sediment Supply To Coastsmentioning

confidence: 99%

Significance of Fluvial Sediment Supply in Coastline Modelling at Tidal Inlets

Bamunawala

Maskey

Duong

et al. 2018

JMSE

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Abstract:The sediment budget associated with future coastline change in the vicinity of tidal inlets consists of four components; sea level rise-driven landward movement of the coastline (i.e., the Bruun effect), basin infilling effect due to sea level rise-induced increase in accommodation space, basin volume change due to variation in river discharge, and coastline change caused by change in fluvial sediment supply. These four components are affected by climate change and/or anthropogenic impacts. Despite this understanding, holistic modelling techniques that account for all the aforementioned processes under both climate change and anthropogenic influences are lacking. This manuscript presents the applications of a newly-developed reduced complexity modelling approach that accounts for both climate change and anthropogenically-driven impacts on future coastline changes. Modelled results corresponding to the year 2100 indicate considerable coastline recessions at Wilson Inlet (152 m) and the Swan River system (168 m) in Australia and Tu Hien Inlet (305 m) and Thuan An Inlet (148 m) in Vietnam. These results demonstrate that coastline models should incorporate both climate change and anthropogenic impacts to quantify future changes in fluvial sediment supply to coasts to achieve better estimates of total coastline changes at tidal inlets. Omission of these impacts is one of the major drawbacks in all the existing coastline models that simulate future coastline changes at tidal inlets. A comparison of these modelled future coastline changes with the predictions made by a relevant existing modelling technique (Scale Aggregated Model for Inlet-interrupted Coasts (SMIC)) indicates that the latter method overestimates total coastline recessions at the Swan River system, and the Tu Hien and Thuan An Inlets by 7%, 10%, and 30%, respectively, underlining the significance of integrating both climate change and anthropogenic impacts to assess future coastline changes at tidal inlets.

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Human impact on sediment fluxes within the Blue Nile and Atbara River basins

Cited by 55 publications

References 50 publications

Sediment yield in Africa

Sediment yield in Africa

Principal Component and Multiple Regression Analyses for the Estimation of Suspended Sediment Yield in Ungauged Basins of Northern Thailand

Significance of Fluvial Sediment Supply in Coastline Modelling at Tidal Inlets

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