Literature DB >> 30107304

An overview of patterns and dynamics of suspended sediment transport in an agroforest headwater system in humid climate: Results from a long-term monitoring.

M L Rodríguez-Blanco1, M M Taboada-Castro2, M T Taboada-Castro2.   

Abstract

Small headwater catchments deliver large quantities of suspended sediment (SS) to the ocean. However, there are relatively few studies focused on the study of patterns and dynamics of suspended sediment in headwater catchments over the long-term (10 year or more). In this study, the dynamics of suspended sediment transport were examined at different time scales in a small headwater catchment in NW Spain, based on a 12-year dataset from high-resolution monitoring. The results revealed that, similar to other humid catchments, the hydrological response was highly dependent on initial conditions, especially in autumn and summer. However, in winter and spring the hydrology was more influenced by rainfall amount. The annual suspended sediment was 117 Mg, which equates to a suspended sediment yield of 10 Mg km-2 y-1. The SS yield in the Corbeira catchment is related to runoff generation and flooding, which play a key role in sediment yield from the catchment. About 80% of the annual SS was transported over 12% of the study period. Rainfall and discharge at the beginning of the events were the most important factors in explaining the hydrological response at event scale. Suspended sediment transport in this catchment is determined by event magnitude, while the SS is mainly influenced by variables related to runoff erosivity.
Copyright © 2018 Elsevier B.V. All rights reserved.

Keywords:  Headwater catchment; Humid conditions; Long-term dataset; Multiple regression; Suspended sediment transport

Year:  2018        PMID: 30107304     DOI: 10.1016/j.scitotenv.2018.08.118

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  1 in total

1.  Predicting suspended sediment load in Peninsular Malaysia using support vector machine and deep learning algorithms.

Authors:  Yusuf Essam; Yuk Feng Huang; Ahmed H Birima; Ali Najah Ahmed; Ahmed El-Shafie
Journal:  Sci Rep       Date:  2022-01-07       Impact factor: 4.379

  1 in total

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