Spatial Variability of Soil Nitrogen and Phosphorus in Small Watershed
CSTR:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Geo-statistics combined with classical statistics were applied to analyze the spatial distribution of soil nitrogen (N) and phosphorus (P) content under three different land uses in Chahe watershed at the lower Yangtze River. The results showed that soil N and P content distribution varied significantly in paddy, upland, and vacant land, while the coefficient of variation also varied greatly among the three land uses. All spatial distributions of N and P content values were anisotropic and directions of most long axes were northwest-southeast. Major ranges in topsoil were between 750~950m with the order of total P(TP)>ammonia N (AN)>total N (TN)>available P (AP)>nitrate N (NN). Higher content of TN was mainly concentrated in the southern part of the small watershed and the gradient direction was consistent with the direction of surface runoff, while distribution of TP was significantly affected by farming and soil particle movement, and the high level of TP was appeared in the accumulation area of the south of small watershed and the north of arid region. TN and TP showed similar structural characteristics under the three farmland types, while both the autocorrelation scales in paddy land were larger than those in upland. Variation of spatial autocorrelation scales showed good consistency with the coefficient of variation. Research results provided a scientific basis for the control of N and P losses in agricultural production and the establishment of non point source pollution model.

    Reference
    Related
    Cited by
Get Citation
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:April 04,2013
  • Revised:
  • Adopted:
  • Online: March 10,2014
  • Published: February 10,2014
Article QR Code