|Table of Contents|

Spatial variability and conditional simulation of soil total nitrogen and available phosphorus in Longtan watershed of the Dabieshan Mountain, China(PDF)

Chinese Journal of Applied & Environmental Biology[ISSN:1006-687X/CN:51-1482/Q]

Issue:
2014 02
Page:
281-285
Research Field:
Articles
Publishing date:

Info

Title:
Spatial variability and conditional simulation of soil total nitrogen and available phosphorus in Longtan watershed of the Dabieshan Mountain, China
Author(s):
CHENG Xianfu SUN Honghu ZHANG Guoyao LV Jun WANG Chuanhui
1College of Territorial Resources and Tourism, Anhui Normal University, Wuhu 241003, China 2Anhui Key Laboratory of Natural Disaster Process and Prevention, Wuhu 241003, China
Keywords:
soil property spatial variability Kriging conditional simulation uncertainty Longtan watershed in Dabieshan Mountain
CLC:
S153.6
PACS:
DOI:
10.3724/SP.J.1145.2014.00281
DocumentCode:

Abstract:
To study on the spatial variability of soil properties for the understanding of the differences in soil is important. Using ordinary Kriging and sequential Gauss simulation methods, we calculated and simulated the spatial distribution of soil total nitrogen and available phosphorus in the Longtan watershed of the Dabieshan Mountain. The results showed that the spatial variability of soil total nitrogen and available phosphorus were moderate with strong spatial autocorrelation. Semivariogram was of exponential model, with total nitrogen variable range of 333 m and phosphorus variable range of 474 m. Total nitrogen content was mainly 1.2-1.6 g kg-1, accounting for 34.96% of the total area, higher in the central and southern watershed. Available phosphorus content was mainly 60-100 mg kg-1, accounting for 42.17% of the total area, comparatively higher in the northwestern and southern watershed. The 1 000 sequential Gauss simulation showed that the soil total nitrogen and available phosphorus obtained by ordinary Kriging spatial distributions was smooth, while the result from sequential Gauss simulation was relatively discrete with great volatility. The critical probability value of 0.50 can meet the conditional simulation requirement. Stochastic simulation can describe the spatial distribution of soil properties uncertainty and provide a powerful tool for spatial structure of regional soil attributes.

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Last Update: 2014-05-04