Study On Water And Soil Erosion In Rude Middle South Coteau

This paper collection and investigation on behalf of rude middle south coteau (Linqu xinzhuang Valley.Mengyinxiang menglianggu Valley.Qufu hongshan Valley.Taian water and soil conservation Valley) data, 10 (1980 1990 ) of soil erosion monitoring data based on rude middle south coteau of soil erosion, and reveal different factors affect the runoff, soil erosion and sediment content of its volume, multi-role by the runoff and soil Erosion prediction model, the findings show that:1.Different slope and the slope of the runoff area of soil erosion studyThe same rainfall conditions, in the same slope length (10m, 20m and 40m) runoff plots by the flood runoff and erosion of the slope to increase the increase, with Y = AX + B linear relationship, in the same slope ( 5°,7°,13°,15°,25°) conditions, the runoff plots generated by the flow and erosion of the slope of the increase, with Y = aX + b linear relationship.2. Different herbs and woody plants, the runoff area of soil erosion mechanismIn the same slope (15°), the same slope length (20m) conditions, the runoff plots of different herbs by the flood and erosion by the flow of Congtaidaoxiao in chronological order: Arachis hypogaea L.> Pistacia Chinensis > Solanum tuberosum L.> grassland > Astragalus adsurgens Pall. > Melilotus suaveolens(Daghest an sweetclover), runoff plots of different woody plants generated by flood runoff and erosion Congtaidaoxiao in chronological order: Prunus salicina > Zanthoxylum bungeanum Maxim > Lespedeza bicolor > Morus alba > Radix Puerariae.3. Rainfall characteristics of the different mechanism of soil erosionIn the same slope (15°), the same slope length (20m) planting the same plants (Arachis hypogaea L.) conditions, with rainfall in flood season (1986 -86.1mm, 1988-309.9mm, 1990-599.8mm) of the increased runoff generated by the community Flood runoff and erosion and increase in rainfall and flood runoff was Y = 97.16X +531, R² = 0.826, flood season rainfall and erosion of a Y = 68.29X +786, R² = 0.842 linear relationship, the flood season Runoff and erosion, with the volume of rainfall increased, the size and rainfall runoff with Y = 105.97X +3513.8, R² = 0.875, on the rainfall and erosion of the size of a Y = 39.84X +497.27, R² = 0.897 linear relationship, flood runoff and erosion with the increased I30, 30 minutes maximum rainfall runoff and the size of a Y = 39.945I301.2726, R² = 0.864,30 minutes of the size of the largest rainfall And erosion of a Y = 0.0079I303.2802, R² = 0.894 power function of the relationship.4. Multi-factor under the conditions of soil erosion mechanismGradient of 5°, 7°, 13°, 15°, 25°,10m, 20m,40m and 13°10m, 13°20m, 13°40m area of the runoff and rainfall runoff and erosion of regression analysis and found that, And the corresponding rainfall runoff and erosion of a Y = apb power function; different slope, slope length under the conditions of total rainfall and flood runoff and erosion of regression analysis, 5°, 7°, 13°, 15°, 25°and 13°and 10m and 20m total rainfall and flood runoff and erosion of a Y = apb power function relationship of different slope, slope length under the conditions of rainfall and runoff after the relationship between regression analysis and found that in the rain During the runoff, respectively and a Y = apb power function equation, Y = at2 + bt + c one yuan quadratic equation, Y = aebt index function equations and Y = at3 + bt2 + ct + e equation of one yuan three different slope, slope length conditions The intensity of rainfall and runoff and erosion of a Y = aIb power function and Y = aebI index function.5. The establishment of a comprehensive runoff plots under the conditions of runoff and erosion prediction modelAccording to rude middle south coteau runoff plots identified by the different slope, different slope length, different vegetation cover, precipitation and different rainfall intensity five different factors, the establishment of five factors and runoff and erosion of the prediction model , Respectively runoff prediction model: Q = S^0.4237L^0.304C^-0.5471P^0.8084I₃₀^0.3896, R² = 0.7342 and the erosion of the prediction model Ms = S^3.9L^0.792C^-0.1478P0.6923I300.0033, R² = 0.8859.