Quantification of soil spatial and temporal variability at watershed scale is important in ecological modeling, precision agriculture, and natural resources management. The spatio-temporal variations of soil nitrogen ...Quantification of soil spatial and temporal variability at watershed scale is important in ecological modeling, precision agriculture, and natural resources management. The spatio-temporal variations of soil nitrogen under different land uses in a small watershed （12.10 km^2） in the hilly area of purple soil at the upper reaches of the Yangtze River in southwestern China were investigated by using conventional statistics, geostatistics, and a geographical information system in order to provide information for land management and control of environmental issues. A total of 552 soil samples （o to 15 cm） from 276 sites within the watershed were collected in April and August of 2o11, and analyzed for soil total nitrogen （STN） and nitrate nitrogen （NO3-N）. We compared spatial variations of STN and NO3-N under different land uses as well as the temporal variations in April （dry season） and August （rainy season）. Results showed that STN contents were deeply affected by land-use types; median STN values ranged from 0.94to 1.27g.kg-I, and STN contents decreased in the following order： paddy field 〉 foresfland 〉 sloping cropland. No significant difference was found for STN contents between April and August under the same land use. However, NO3- N contents were 23.26, 10.58, and 26.19 mg·kg^-1 in April, and 1.34, 8.51, and 3.00 mg·kg^-1 in August for the paddy field, sloping cropland and forestland, respectively. Nugget ratios for STN indicatedmoderate spatial dependence in the paddy field and sloping cropland, and a strong spatial dependence in forestland. The processes of nitrogen movement, transformation, absorption of plant were deeply influenced by land use types; as a result, great changes of soil nitrogen levels at spatial and temporal scales were demonstrated in the studied watershed.展开更多
Soil type maps at the scale of I Z 1 000 000 are used extensively to provide soil spatial distribution information for soil erosion assessment and watershed management models in China. However, the soil property maps ...Soil type maps at the scale of I Z 1 000 000 are used extensively to provide soil spatial distribution information for soil erosion assessment and watershed management models in China. However, the soil property maps produced through conventional direct linking method usually suffer low accuracy as well as the lack of spatial details within a soil type polygon. This paper presents an effective method to produce detailed soil property map based on representative samples which were extracted from each polygon on the 1 ： 1 000 000 soil type map. The representative sample of each polygon is defined as the location that can represent the largest area within the polygon. The representativeness of a candidate sample is determined by calculating the soil-forming environment condition similarities between the sample and other locations. Once the representative sample of each polygon has been chosen, the property values of the existing typical samples are assigned to the corresponding representative samples with the same soil type. Finally, based on these representative samples, the detailed soil property map could be produced by using existing digital soil mapping methods. The case study in XuanCheng City, Anhui Province of China, demonstrated the proposed method could produce soil property map at a higher level of spatial details and accuracy： 1） The soil organic matter （SOM） map produced based on the representative samples can not only depict the detailed spatial distribution of SOM within a soil type polygon but also largely reduce the abrupt change of soil property at the boundaries of two adjacent polygons. 2） The Root Mean Squared Error （RMSE） of the SOM map based on the representative samples is 1.61, and it is 1.37 for the SOM map produced by using conventional direct linking method. Therefore, the proposed method is an effective approach to produce spatial detailed soil property map with higher accuracy for environment simulation models.展开更多
基金this project was provided by the Natural Science Foundation of China (Grant No.41271321)the National Key Basic Research Program of China (Grant no. 2012CB417101)
文摘Quantification of soil spatial and temporal variability at watershed scale is important in ecological modeling, precision agriculture, and natural resources management. The spatio-temporal variations of soil nitrogen under different land uses in a small watershed （12.10 km^2） in the hilly area of purple soil at the upper reaches of the Yangtze River in southwestern China were investigated by using conventional statistics, geostatistics, and a geographical information system in order to provide information for land management and control of environmental issues. A total of 552 soil samples （o to 15 cm） from 276 sites within the watershed were collected in April and August of 2o11, and analyzed for soil total nitrogen （STN） and nitrate nitrogen （NO3-N）. We compared spatial variations of STN and NO3-N under different land uses as well as the temporal variations in April （dry season） and August （rainy season）. Results showed that STN contents were deeply affected by land-use types; median STN values ranged from 0.94to 1.27g.kg-I, and STN contents decreased in the following order： paddy field 〉 foresfland 〉 sloping cropland. No significant difference was found for STN contents between April and August under the same land use. However, NO3- N contents were 23.26, 10.58, and 26.19 mg·kg^-1 in April, and 1.34, 8.51, and 3.00 mg·kg^-1 in August for the paddy field, sloping cropland and forestland, respectively. Nugget ratios for STN indicatedmoderate spatial dependence in the paddy field and sloping cropland, and a strong spatial dependence in forestland. The processes of nitrogen movement, transformation, absorption of plant were deeply influenced by land use types; as a result, great changes of soil nitrogen levels at spatial and temporal scales were demonstrated in the studied watershed.
基金Under the auspices of Program of International Science & Technology Cooperation,Ministry of Science and Technology of China(No.2010DFB24140)National Natural Science Foundation of China(No.41023010,41001298)National High Technology Research and Development Program of China(No.2011AA120305)
文摘Soil type maps at the scale of I Z 1 000 000 are used extensively to provide soil spatial distribution information for soil erosion assessment and watershed management models in China. However, the soil property maps produced through conventional direct linking method usually suffer low accuracy as well as the lack of spatial details within a soil type polygon. This paper presents an effective method to produce detailed soil property map based on representative samples which were extracted from each polygon on the 1 ： 1 000 000 soil type map. The representative sample of each polygon is defined as the location that can represent the largest area within the polygon. The representativeness of a candidate sample is determined by calculating the soil-forming environment condition similarities between the sample and other locations. Once the representative sample of each polygon has been chosen, the property values of the existing typical samples are assigned to the corresponding representative samples with the same soil type. Finally, based on these representative samples, the detailed soil property map could be produced by using existing digital soil mapping methods. The case study in XuanCheng City, Anhui Province of China, demonstrated the proposed method could produce soil property map at a higher level of spatial details and accuracy： 1） The soil organic matter （SOM） map produced based on the representative samples can not only depict the detailed spatial distribution of SOM within a soil type polygon but also largely reduce the abrupt change of soil property at the boundaries of two adjacent polygons. 2） The Root Mean Squared Error （RMSE） of the SOM map based on the representative samples is 1.61, and it is 1.37 for the SOM map produced by using conventional direct linking method. Therefore, the proposed method is an effective approach to produce spatial detailed soil property map with higher accuracy for environment simulation models.
