Forecasting Of Water Retention Capacity Of Soil And Water Conservation In Small Watershed In Southwest China

Ensuring the sustainable utilization of water is the guarantee of social and economic stability and healthy development of an important premise and key. Practice shows that the long-term conservation of water and soil, keep are equally important significance. In a river basin, as a unit watershed comprehensive treatment is the effective way of controlling actively soil and water loss, keeping soil and water resources sustainable utilization and accelerating the construction of ecological environment. And it is also important experience to soil and water conservation in China. Therefore, in the serious soil erosion in the mountainous southwest, water conservation is important and urgent in soil-and-water conservation work.Through drawing lessons from water conservation in forest ecosystems mechanism, this paper studies and analyzes mainly the quantitative relationship between water and various factors that affect the water of the small watershed protection, and establishes a small basin of water-maintained calculation model focusing on analysis of them described additive model based on water balance principle. Based on vegetation types and land utilization form, the small watershed will be divided into forest, grassland, paddy fields and other areas by MapGIS, and then we can calculate respectively the capacity of maintaining water according to their respective holding-water characteristics.By research, it is found that the forest is the key area impacting on water in small watershed. The main regions of forest water retention capacity focus in forest canopy and regional soil layers and the understory in the forest litter layers, and the key factors of affecting its water storage capacity is the vegetation type, canopy density, age, litter thickness, undergrowth cover degree and ground covers degree. The key factors were selected as the input value, and take the water-holding capacity of crown, litter, soil, and their sum as the output to establish the BP neural network model. Its advantage is improving the efficiency of solving the problem by the use of fuzzy neural networks to deal with the complex interaction between the various factors relations.