Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
doi:10.5194/hess-2016-394
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
23 Aug 2016
Review status
A revision of this discussion paper is under review for the journal Hydrology and Earth System Sciences (HESS).
Regional soil erosion assessment based on sample survey and geostatistics
Shuiqing Yin1,2, Zhengyuan Zhu3, Li Wang3, Baoyuan Liu1,2, Yun Xie1,2, Guannan Wang4, and Yishan Li1,2 1State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
2School of Geography, Beijing Normal University, Beijing 100875, China
3Department of Statistics, Iowa State University, Ames 50010, USA
4Department of Mathematics, College of William & Mary, Williamsburg 23185, USA
Abstract. Soil erosion is one of the major environmental problems in China. From 2010–2012 in China, the fourth national census for soil erosion sampled 32 364 Primary Sampling Units (PSUs, micro watersheds) with the areas of 0.2–3 km2. Land use and soil erosion controlling factors including rainfall erosivity, soil erodibility, slope length, slope steepness, biological practice, engineering practice, and tillage practice for the PSUs were surveyed, and soil loss rate for each land use in the PSUs were estimated using an empirical model Chinese Soil Loss Equation (CSLE). Though the information collected from the sample units can be aggregated to estimate soil erosion conditions on a large scale, the problem of estimating soil erosion condition on a regional scale has not been well addressed. The aim of this study is to introduce a new spatial interpolation method based on Bivariate Penalized Spline over Triangulation (BPST) for the estimation of regional soil erosion. We compared five interpolation models based on BPST to generate a regional soil erosion assessment from the PSUs. Land use, rainfall erosivity, and soil erodibility at the resolution of 250 × 250 m pixels for the entire domain were used as the auxiliary information. Shaanxi province (3116 PSUs) in China was used to conduct the comparison and assessment as it is one of the most serious erosion areas. The results showed that three models with land use as the auxiliary information generated much lower mean squared errors (MSE) than the other two models without land use. The model assisted by the land use, rainfall erosivity factor (R), and soil erodibility factor (K) is the best one, which has MSE less than half that of the model smoothing soil loss in the PSUs directly. 56.5 % of total land in Shaanxi province has annual soil loss greater than 5 t ha−1 y−1. High (20–40 t ha−1 y−1),severe (40–80 t ha−1 y−1) and extreme (>80 t ha−1 y−1) erosion occupied 14.3 % of the total land. The farmland, forest, shrub land and grassland in Shaanxi province had mean soil loss rates of 19.00, 3.50, 10.00, 7.20 t ha−1 y−1, respectively. Annual soil loss was about 198.7 Mt in Shaanxi province, with 67.8 % of soil loss originating from the farmlands and grasslands in Yan'an and Yulin districts in the northern Loess Plateau region and Ankang and Hanzhong districts in the southern Qingba mountainous region. This methodology provides a more accurate regional soil erosion assessment and can help policy-makers to take effective measures to mediate soil erosion risks.

Citation: Yin, S., Zhu, Z., Wang, L., Liu, B., Xie, Y., Wang, G., and Li, Y.: Regional soil erosion assessment based on sample survey and geostatistics, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-394, in review, 2016.
Shuiqing Yin et al.
Shuiqing Yin et al.
Shuiqing Yin et al.

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