title: [Calculation of soil water erosion modulus based on RUSLE and its assessment under support of artificial neural network].
abstract: With Hengshan County of Shanxi Province in the North Loess Plateau as an example, and by using ETM + and remote sensing data and RUSLE module, this paper quantitatively derived the soil and water loss in loess hilly region based on "3S" technology, and assessed the derivation results under the support of artificial neural network. The results showed that the annual average erosion modulus of Hengshan County was 103.23 t x hm(-2), and the gross erosion loss per year was 4. 38 x 10(7) t. The erosion was increased from northwest to southeast, and varied significantly with topographic position. A slight erosion or no erosion happened in walled basin, flat-headed mountain ridges and sandy area, which always suffered from dropping erosion, while strip erosion often happened on the upslope of mountain ridge and mountaintop flat. Moderate rill erosion always occurred on the middle and down slope of mountain ridge and mountaintop flat, and weighty rushing erosion occurred on the steep ravine and brink. The RUSLE model and artificial neural network technique were feasible and could be propagandized for drainage areas control and preserved practice.
authors.affiliation: China Land Surveying & Planning Institute, Beijing 100035, China. yuhuan@sdau.edu.cn
authors.forename: Yuhuan
authors.initials: Y
authors.lastname: Li
authors.forename: Jing
authors.initials: J
authors.lastname: Wang
authors.forename: Jixian
authors.initials: J
authors.lastname: Zhang
mesh_terms: D002681:China; D017753:Ecosystem; D004784:Environmental Monitoring; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D012987:Soil / Q000032:analysis*; D014867:Water / Q000032:analysis*
chemical_list: D012987:Soil; D014867:Water