Influence of flow concentration on parameter importance and prediction uncertainty of pesticide trapping by vegetative filter strips

被引:68
|
作者
Fox, Garey A. [1 ]
Munoz-Carpena, Rafael [2 ]
Sabbagh, George J. [3 ]
机构
[1] Oklahoma State Univ, Dept Biosyst & Agr Engn, Stillwater, OK 74078 USA
[2] Univ Florida, Dept Agr & Biol Engn, Gainesville, FL 32611 USA
[3] Oklahoma State Univ, Stilwell, KS 66085 USA
关键词
Concentrated flow; Pesticides; Sensitivity analysis; Uncertainty analysis; Uniform flow; Vegetative filter strips; SATURATED HYDRAULIC CONDUCTIVITY; SENSITIVITY-ANALYSIS; GRASS BARRIERS; SEDIMENT; MODEL; REMOVAL; BUFFERS; RUNOFF; DESIGN; SOIL;
D O I
10.1016/j.jhydrol.2010.01.020
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Flow concentration is a key hydrologic factor limiting the effectiveness of vegetated filter strips (VFS) in removing pesticides from surface runoff. Numerical models, such as VFSMOD-W, offer a mechanistic approach for evaluating VFS effectiveness under various hydrological conditions including concentrated flow. This research hypothesizes that the presence of concentrated flow drastically alters the importance of various hydrological, sedimentological, and pesticide input factors and the prediction uncertainty of pesticide reduction. Using data from a VFS experimental field study investigating chlorpyrifos and atrazine transport, a two-step global sensitivity and uncertainty analysis framework was used with VFSMOD-W based on (1) a screening method (Morris) and (2) a variance-based method (extended Fourier Analysis Sensitivity Test, FAST). The vertical, saturated hydraulic conductivity was consistently the most important input factor for predicting infiltration, explaining 49% of total output variance for uniform sheet flow, but only 8% for concentrated flow. Sedimentation was governed by both hydrologic (vertical, saturated hydraulic conductivity and initial and saturated water content) and sediment characteristics (average particle diameter). The vertical, saturated hydraulic conductivity was the most important input factor for atrazine or chlorpyrifos trapping under uniform sheet flow (explained more than 46% of the total output variance) and concentrated flow (although only explained 8% of the total variance in this case). The 95% confidence intervals for atrazine and chlorpyrifos reduction ranged between 43% and 78% for uniform sheet flow and decreased to between 1% and 16% under concentrated flow. Concentrated flow increased interactions among the system components, enhancing the relative importance of processes that were latent under shallow flow conditions. This complex behavior warrants the need for processbased modeling to be able to predict the performance of VFS under a wide range of specific hydrological conditions. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:164 / 173
页数:10
相关论文
共 50 条
  • [41] Pesticides trapping performance of vegetative filter strips in black soil region, Northeast China: controlled experiments and VFSMOD-W modeling
    Yan, Liming
    Wang, Xinhong
    Ou, Yang
    Pang, Shujiang
    Cui, Qi
    Hou, Xia
    [J]. ECOLOGICAL ENGINEERING, 2024, 209
  • [42] Dynamic prediction of effective runoff sediment particle size for improved assessment of erosion mitigation efficiency with vegetative filter strips
    Reichenberger, Stefan
    Sur, Robin
    Sittig, Stephan
    Multsch, Sebastian
    Carmona-Cabrero, Alvaro
    Javier Lopez, J.
    Munoz-Carpena, Rafael
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2023, 857
  • [43] Impact of plant growth and morphology and of sediment concentration on sediment retention efficiency of vegetative filter strips: Flume experiments and VFSMOD modeling
    Lambrechts, Thomas
    Francois, Sebastien
    Lutts, Stanley
    Munoz-Carpena, Rafael
    Bielders, Charles L.
    [J]. JOURNAL OF HYDROLOGY, 2014, 511 : 800 - 810
  • [44] Shallow water table effects on water, sediment, and pesticide transport in vegetative filter strips - Part 1: nonuniform infiltration and soil water redistribution
    Munoz-Carpena, Rafael
    Lauvernet, Claire
    Carluer, Nadia
    [J]. HYDROLOGY AND EARTH SYSTEM SCIENCES, 2018, 22 (01) : 53 - 70
  • [45] Distinct influence of filter strips on acute and chronic pesticide aquatic environmental exposure assessments across US EPA scenarios
    Sabbagh, George J.
    Munoz-Carpena, Rafael
    Fox, Garey A.
    [J]. CHEMOSPHERE, 2013, 90 (02) : 195 - 202
  • [46] COUPLED PROCESS PARAMETER-ESTIMATION AND PREDICTION UNCERTAINTY USING HYDRAULIC-HEAD AND CONCENTRATION DATA
    GAILEY, RM
    GORELICK, SM
    CROWE, AS
    [J]. ADVANCES IN WATER RESOURCES, 1991, 14 (05) : 301 - 314
  • [47] Uncertainty of debris flow mobility relationships and its influence on the prediction of inundated areas
    Simoni, Alessandro
    Mammoliti, Maria
    Berti, Matteo
    [J]. GEOMORPHOLOGY, 2011, 132 (3-4) : 249 - 259
  • [48] Influence of input and parameter uncertainty on the prediction of catchment-scale groundwater travel time distributions
    Jing, Miao
    Hesse, Falk
    Kumar, Rohini
    Kolditz, Olaf
    Kalbacher, Thomas
    Attinger, Sabine
    [J]. HYDROLOGY AND EARTH SYSTEM SCIENCES, 2019, 23 (01) : 171 - 190
  • [49] Parameter uncertainty in spatial prediction: Checking its importance by cross-validating the Wolfcamp and Rongelap data sets
    Papritz, A
    Moyeed, RA
    [J]. GEOENV III - GEOSTATISTICS FOR ENVIRONMENTAL APPLICATIONS, 2001, 11 : 369 - 380
  • [50] Adaptive Kalman filter approach for stochastic short-term traffic flow rate prediction and uncertainty quantification
    Guo, Jianhua
    Huang, Wei
    Williams, Billy M.
    [J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2014, 43 : 50 - 64