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Forecasting of Water Retention Capacity of Soil and Water Conservation in Small Watershed in Southwest China
Author: YangXueFeng
Tutor: ZhouFuChun
School: Chongqing Jiaotong University
Course: Hydrology and Water Resources
Keywords: Water retention capacity Small Watershed Influencing factors BP neural network MapGIS Southwest China
CLC: S157
Type: Master's thesis
Year: 2010
Downloads: 34
Quote: 0
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Abstract
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Ensure the sustainable use of water resources is to ensure social and economic stability , an important prerequisite for the healthy development with key . The long-term practice of soil and water conservation : water retention and soil conservation is equally important ; watershed as a unit small watershed management is the sustainable use of effective erosion control , protection of soil and water resources , an effective way to speed up the construction of ecological environment , of Soil and Water Conservation experience . So , serious soil erosion in the mountains of southwest and water conservation work in the Small Watershed is particularly important and urgent . Learn forest ecosystems in the mechanism of water conservation , research and analysis impact factor with the water retention capacity of the quantitative relationship between the water retention capacity of the small watershed basin , and in accordance with the principle of water balance , the establishment of a computational model of the water retention capacity of the small watershed analyzes elaborated . additive model . Form, according to the vegetation type and land use MapGIS software Small Watershed Division for the area of woodland, grassland , paddy fields , water retention capacity were calculated according to the water-holding characteristics . Found to affect the water retention capacity of the small watershed critical area is woodland , woodland storage capacity mainly concentrated areas critical factor affecting its water storage capacity is the type of vegetation in the the woodland soil layer and understory litter layer , Yu closed degrees , age, litter layer thickness, understory cover and ground cover plants . Select these key factor for the inputs to the canopy water holding capacity of litter layer water-holding capacity , the woodland soil water holding capacity and three forest possidetis total water output , BP neural network model . The advantages of using neural network fuzzy processing the mutual complex relationships between the various factors to improve the efficiency of the solution to the problem .
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CLC: > Agricultural Sciences > Agriculture as the foundation of science > Soil > Soil and Water Conservation
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