Literature DB >> 27344122

A mathematical model for the transfer of soil solutes to runoff under water scouring.

Ting Yang1, Quanjiu Wang2, Laosheng Wu3, Pengyu Zhang4, Guangxu Zhao4, Yanli Liu4.   

Abstract

The transfer of nutrients from soil to runoff often causes unexpected pollution in water bodies. In this study, a mathematical model that relates to the detachment of soil particles by water flow and the degree of mixing between overland flow and soil nutrients was proposed. The model assumes that the mixing depth is an integral of average water flow depth, and it was evaluated by experiments with three water inflow rates to bare soil surfaces and to surfaces with eight treatments of different stone coverages. The model predicted outflow rates were compared with the experimentally observed data to test the accuracy of the infiltration parameters obtained by curve fitting the models to the data. Further analysis showed that the comprehensive mixing coefficient (ke) was linearly correlated with Reynolds' number Re (R(2)>0.9), and this relationship was verified by comparing the simulated potassium concentration and cumulative mass with observed data, respectively. The best performance with the bias error analysis (Nash Sutcliffe coefficient of efficiency (NS), relative error (RE) and the coefficient of determination (R(2))) showed that the predicted data by the proposed model was in good agreement with the measured data. Thus the model can be used to guide soil-water and fertilization management to minimize nutrient runoff from cropland.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Mixing depth; Simulation model; Soil detachment; Soil-solute transport; Surface runoff

Year:  2016        PMID: 27344122     DOI: 10.1016/j.scitotenv.2016.06.094

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


  1 in total

1.  Mathematical model of ammonium nitrogen transport with overland flow on a slope after polyacrylamide application.

Authors:  Chang Ao; Peiling Yang; Shumei Ren; Weimin Xing
Journal:  Sci Rep       Date:  2018-04-23       Impact factor: 4.379

  1 in total

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