Literature DB >> 19067210

An experimental method to verify soil conservation by check dams on the Loess Plateau, China.

X Z Xu1, H W Zhang, G Q Wang, S C Chen, W Q Dang.   

Abstract

A successful experiment with a physical model requires necessary conditions of similarity. This study presents an experimental method with a semi-scale physical model. The model is used to monitor and verify soil conservation by check dams in a small watershed on the Loess Plateau of China. During experiments, the model-prototype ratio of geomorphic variables was kept constant under each rainfall event. Consequently, experimental data are available for verification of soil erosion processes in the field and for predicting soil loss in a model watershed with check dams. Thus, it can predict the amount of soil loss in a catchment. This study also mentions four criteria: similarities of watershed geometry, grain size and bare land, Froude number (Fr) for rainfall event, and soil erosion in downscaled models. The efficacy of the proposed method was confirmed using these criteria in two different downscaled model experiments. The B-Model, a large scale model, simulates watershed prototype. The two small scale models, D(a) and D(b), have different erosion rates, but are the same size. These two models simulate hydraulic processes in the B-Model. Experiment results show that while soil loss in the small scale models was converted by multiplying the soil loss scale number, it was very close to that of the B-Model. Obviously, with a semi-scale physical model, experiments are available to verify and predict soil loss in a small watershed area with check dam system on the Loess Plateau, China.

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Year:  2008        PMID: 19067210     DOI: 10.1007/s10661-008-0630-x

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  1 in total

1.  Check dam sediments: an important indicator of the effects of environmental changes on soil erosion in the Loess Plateau in China.

Authors:  Yafeng Wang; Liding Chen; Bojie Fu; Yihe Lü
Journal:  Environ Monit Assess       Date:  2014-03-13       Impact factor: 2.513

  1 in total

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