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a The State Key Lab. of Remote Sensing Science, Jointly Sponsored by the Inst. of Remote Sensing Applications, Chinese Academy of Sciences and Beijing Normal Univ., Beijing 100101, P.R. China
b The Inst. of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, P.R. China
* Corresponding author (jswu{at}isa.ac.cn)
Received for publication May 7, 2006. Nonpoint-source pollution and water body eutrophication have become increasing concerns for scientists and policymakers. Nitrogen and phosphorus affect environmental pollution, especially lake eutrophication. To assess the environmental risk of soil total nitrogen (TN) and total phosphorus (TP) pollution, a typical ecological unit of Dongting Lake plain was selected as the experimental site. To verify the stationary of the data, a moving windows technique was adopted. Our results showed that Box-Cox transformation achieved normality in the data set and dampened the effect of outliers. The best theoretical model for semivariogram of TN and TP was a spherical model. The ordinary kriging estimates of TN and TP concentrations were mapped. The integrative comparisons of semivariogram parameters with different trends to the kriging prediction errors of TN and TP indicated that the two-order trend is preferable. Kriging SDs provided valuable information that will increase the accuracy of TN and TP mapping. The probability kriging method is useful to assess the risk of N and P pollution by providing the conditional probability of N and P concentrations exceeding the threshold concentrations of 3.2 and 1.05 g/kg, respectively. The probability distribution of TN and TP at different levels will be helpful to conduct risk assessment, optimize fertilization, and control the pollution of N and P.
Abbreviations: KSD, kriging SD TN, soil total nitrogen TP, soil total phosphorus
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