文章摘要
李朝月, 方海燕.基于SWAT模型的寿昌江流域产沙模拟及影响因素分析[J].水土保持学报,2019,33(6):127~135,142
基于SWAT模型的寿昌江流域产沙模拟及影响因素分析
Simulation of Sediment Yield and Analysis of Influencing Factors in the Shouchang River Basin Based on SWAT Model
投稿时间:2019-05-15  
DOI:10.13870/j.cnki.stbcxb.2019.06.018
中文关键词: 侵蚀产沙  SWAT模型  寿昌江流域  主成分  景观指数
英文关键词: soil erosion and sediment yield  SWAT model  Shouchang River Basin  principal components  landscape metrics
基金项目:国家自然科学基金面上项目(41571271,41977066)
作者单位E-mail
李朝月1,2, 方海燕1,2 1. 中国科学院地理科学与资源研究所陆地水循环及地表过程重点实验室, 北京 100101

2. 中国科学院大学资源与环境学院
, 北京 100049 
fanghy@igsnrr.ac.cn 
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中文摘要:
      为分析山地丘陵地带侵蚀产沙的变化及驱动机制,应用SWAT模型对浙江省建德市寿昌江流域进行了产流产沙模拟,并基于Fragstats 4.2对不同年份土地利用数据进行景观指数计算,进而分析流域内侵蚀产沙状况,探讨了坡度、坡长、海拔高程、流域面积、降雨以及景观格局对侵蚀产沙的影响,并进行主成分分析。结果表明:(1)构建的SWAT模型在寿昌江流域具有很好的适用性,在产流模拟中,校准期和验证期的R2分别为0.95和0.88,NSE分别为0.93和0.87,PBIAS分别为+4.96%和+5.36%;在产沙模拟中,校准期和验证期的R2分别为0.73和0.72,NSE分别为0.69和0.64,PBIAS分别为-4.3%和-20%,均满足模拟要求,保证了模拟结果的精度。(2)整个寿昌江流域1980-2010年最大侵蚀产沙负荷均小于500 t/(km2·a),土壤侵蚀强度属于微度,土壤保持能力良好。(3)地形因子、景观多样性因子、景观形状因子、雨强因子4个主成分对产沙模数的贡献率分别为51.48%,18.51%,10.70%,6.94%,地形因子是影响流域侵蚀产沙的主要因素。(4)景观指数与产沙模数间存在显著相关性且对产沙影响显著,在今后的土地利用规划中应考虑景观特征,达到改善流域土壤侵蚀的目的。
英文摘要:
      In order to analyze the change and driving mechanism of erosion and sediment yield in the hillside area, this paper applied SWAT model to simulate sediment yield in Shouchang River Basin of Jiande City, Zhejiang Province, and calculated the landscape metrics based on Fragstats 4.2 for land use data in different years. The sediment yields in the basin were analyzed, the effects of slope, slope length, elevation, drainage area, rainfall, and landscape pattern on soil and sediment yield were discussed, and the principal components analysis was carried out. The main results were as follows:(1) The SWAT model had good applicability in the Shouchang River basin, R2, NSE and PBIAS all met the simulation and ensured the accuracy of the simulation results. (2) The maximum sediment yield of the entire Shouchang River basin from 1980 to 2010 was less than 500 t/(km2·a), and the soil erosion intensity was slight and the soil erosion retention ability was good. (3) The contribution rates of four principal components of topographic factor, landscape diversity factor, landscape shape factor, and rain intensity factor to sediment yield were 51.48%, 18.51%, 10.70%, and 6.94%, respectively, and topographic factor was the main factor affecting soil erosion and sediment yield. (4) There was a significant correlation between the landscape metrics and the sediment yield, and the landscape metrics had a significant impact on the sediment yield. In the future land-use planning, the landscape characteristics should be effectively considered to improve the soil erosion in the basin.
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