The interpolation accuracy for seven soil properties at various sampling scales on the Loess Plateau, China

Abstract

Purpose Knowledge of the changes in interpolation accuracy with changing sampling scales is important when designing an appropriate sampling strategy. The objectives of this study were (1) to analyze the changes in interpolation accuracy with changing sampling scales for seven soil properties and (2) to find a suitable index that could predict the interpolation accuracy well. Materials and methods Nine hundred sixty-one samples were collected from a 30×30-m area. Seven soil properties were measured for each sample. Using a re-sampling analysis method, we grouped the samples under 16 subscales. Then, we divided the 16 subscales into two subsets, the first consisting of eight scales used as training sets and the second having the other eight scales as validation sets. Using the training sets, the interpolation accuracy and the contribution rate (CR) for the seven soil properties were compared and the relations of the interpolation accuracy to the coefficient of variation (CV), or to the ratio of sampling spacing to correlated range (S/R), or to the extent and spacing (E & S) were determined, the accuracy of prediction of which were then tested using the validation sets. Results and discussionThe results showed that the mean interpolation accuracies varied greatly for different soil properties, with mean G values of training sets ranging from 2.4% for soil organic carbon, to 62.1% for sand content. With increasing sampling spacing or decreasing sampling extent, the interpolation accuracy decreased for all soil properties. The scales with the largest CR were not consistent with those with the highest interpolation accuracies. The interpolation accuracy was predicted better by E & S than by CV or by S/R. Conclusions The measurement and analysis gave insight into the changes of interpolation accuracy and CR at various sampling scales. Predicting interpolation accuracy based on the scale parameters of sampling spacing and sampling extent was feasible, which provided a useful means by which to determine appropriate sample size and sampling strategy.

Comparison of interpolation methods for soil moisture prediction on China's Loess Plateau

“…A geostatistical approach can be used to study spatial dynamics of soil moisture. The MLR‐RK or RBFNN‐RK method has been used in several studies to interpolate SMC for the top soil layer at small spatial scales on the CLP (Gao & Shao, 2012; Yao et al., 2013). Only a few SMC interpolations have been down at regional scales or for diverse soil layers using two methods.…”

“…The MLR‐RK method of interpolation of SMC was not very suitable, compared with the other methods. This indicated that the MLR‐RK method was not suitable for SMC interpolation at regional scale (Gao & Shao, 2012; Shen et al., 2019; Yao et al., 2013). The method considers structural and random factors of soil property distribution and thereby enhances interpolation accuracy.…”

Spatio-temporal variability and temporal stability of water contents distributed within soil profiles at a hillslope scale

“…Soil moisture is highly and nonlinearly variable in both time and space due to heterogeneity of climate and soil across different scales (Heathman et al, 2012). Studies have identified important spatiotemporal variability characteristics of SWC from different aspects, such as the spatio-temporal patterns of SWC (Cantón et al, 2004;Brocca et al, 2007), the relationship between the heterogeneity and its mean values (Hupet and Vanclooster, 2002;Choi and Jacobs, 2007), the spatial scaling of SWC (Western and Blöschl, 1999;Gao and Shao, 2012a), and the controlling factors of spatio-temporal patterns (Gómez-Plaza et al, 2001;Zhao et al, 2010).…”

Effects of vegetation, terrain and soil layer depth on eight soil chemical properties and soil fertility based on hybrid methods at urban forest scale in a typical loess hilly region of China

“…The main characteristics of Yan'an urban forest are as follows: (a) By the end of 2015, the total area and coverage rate of forests and trees in the study area was 1016.64 km 2 (suburb forests = 998.76 km 2 , urban green spaces = 16.73 km 2 , street trees = 1.15 km 2 ) and 65.8%, respectively. (b) The soil parent material is relatively homogeneous, the soil type is mainly loessial soil and the thickness ranges from approximately 50 m to 200 m [ 44 ], the soil has been deposited by the wind since the Quaternary period [ 45 ]. (c) However, the water retention properties of loessial soil are very poor because of its low anti-scourability [ 43 ].…”