1. 山东省水文中心,山东,济南,250002
2. 潍坊市水文中心,山东,潍坊,266071
3. 济南大学 水利与环境学院,山东,济南,250022
纸质出版:2022
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邢先双, 董明明, 郭静, 等. 鲁中山区CSLE模型中植被和地形因子的优化方法[J]. 水土保持通报, 2022,42(2):136-143.
Xing Xianshuang, Dong Mingming, Guo Jing, et al. Optimization Method of Vegectation and Terrain Factors in CSLE Model at a Mountainous Area of Central Shandong Province[J]. Bulletin of Soiland Water Conservation, 2022, 42(2): 136-143.
邢先双, 董明明, 郭静, 等. 鲁中山区CSLE模型中植被和地形因子的优化方法[J]. 水土保持通报, 2022,42(2):136-143. DOI: 10.13961/j.cnki.stbctb.2022.02.019.
Xing Xianshuang, Dong Mingming, Guo Jing, et al. Optimization Method of Vegectation and Terrain Factors in CSLE Model at a Mountainous Area of Central Shandong Province[J]. Bulletin of Soiland Water Conservation, 2022, 42(2): 136-143. DOI: 10.13961/j.cnki.stbctb.2022.02.019.
[目的
]
优化中国土壤侵蚀模型CSLE的因子计算方法,提高该模型在鲁中低山丘陵小流域的模拟精度,为低山丘陵区小流域的土壤侵蚀因子动态监测方法提供技术支撑。[方法
]
以淄博市郝峪小流域为研究区,将国产高分卫星数据和无人机低空遥感数据相结合,对CSLE模型中的地形地貌因子和植被覆盖与生物措施因子进行了算法优化,通过与国家监测数据的对比,验证优化后土壤侵蚀模型因子的优越性。[结果
]
①模型因子算法优化验证结果表明,坡度坡长因子频率曲线相似度为0.91,可以进行土壤侵蚀计算; ②对于植被覆盖度提取的尺度转换模型,拟合优度系数R
2
为0.686 8,可以进行植被覆盖与生物措施因子计算。③优化模型后的土壤侵蚀数据与国家监测的土壤侵蚀数据的相关系数为0.686 8。[结论
]
优化了CSLE模型中因子提取计算的方法提高了模型的模拟精度。因子优化后计算的土壤侵蚀模数更符合当地实际情况。
[Objective] The factor calculation method of the Chinese soil loss equation (CSLE) were optimized to improve the simulation accuracy of CSLE for a hilly watershed of Shandong Province in order to provide technical support for dynamic monitoring of soil erosion factors in this region. [Methods] The Haoyu small watershed of Zibo City was taken as the research area. Factors in the CSLE model
such as vegetation cover
biological measures
and topographical features
were optimized by combining domestic high-resolution satellite data and UAV low-altitude remote sensing data. The superiority of the optimized soil erosion model factor was verified by comparing with national monitoring data. [Results] ① The factors of rainfall erosion and soil erodibility were consistent with the dynamic monitoring results of soil erosion in Shandong Province. The main soil conservation engineering measures were terraces
for which the factor value for ridge terraces was 0.084 and the factor value for stone ridge terraces was 0.121; the factor value for farming measures in the study area was 0.425. ② The similarity of the slope and length factor frequency curve was 0.91
which can be used for soil erosion calculation; the goodness of fit coefficient (R2) was 0.686 8 for the scale conversion model for vegetation coverage extraction
which can be used for the calculation of vegetation cover and biological measures. ③ The correlation coefficient between the soil erosion data calculated by the optimized model and the soil erosion data monitored by the state was 0.686 8. [Conclusion] The optimized method of factor extraction and calculation in the CSLE model could improve the simulation accuracy of the model
and the soil erosion modulus calculated after factor optimization is more in line with the actual local situation.
杨强强.大凌河流域不同空间尺度典型流域泥沙输移比及其影响因素研究[J].中国水能及电气化,2018(5):18-22.
张骁,赵文武,刘源鑫.遥感技术在土壤侵蚀研究中的应用述评[J].水土保持通报,2017,37(2):228-238.
Zhang Hengda, Zhang Ronghua, Qi Fei, et al. The CSLE model based soil erosion prediction: Comparisons of sampling density and extrapolation method at the county level [J]. Catena, 2018, 165: 465-472.
董丽霞,蒋光毅,张志兰,等.重庆市中国土壤流失方程因子研究进展[J].中国水土保持,2021,4(2):40-44,6.
Ei Jazouli A, Barakat A, Ghafiri A, et al. Soil erosion modeled with USLE, GIS, and remote sensing: a case study of Ikkour watershed in Middle Atlas (Morocco) [J]. Geoscience Letters, 2017, 4(1): 1-12.
Phinzi K, Ngetar N S. The assessment of water-borne erosion at catchment level using GIS-based RUSLE and remote sensing: A review [J]. International Soil and Water Conservation Research, 2019, 7(1): 27-46.
方天纵,秦朋遥,王黎明.高时空分辨率植被覆盖获取方法及其在土壤侵蚀监测中的应用[J].生态学报,2019,39(15):5679-5689.
符素华, 刘宝元, 周贵云, 等. 坡长坡度因子计算工具[J]. 中国水土保持科学, 2015, 13(5): 105-110.
孙禹.植被盖度在土壤侵蚀模数计算中的应用[J].水土保持通报,2013,33(5):185-189,309.
顾朝军. 黄土区土壤水文物理特性及流域产汇流机制变化对植被恢复的响应[D]. 陕西 杨凌:西北农业大学, 2019.
杨力华.
LS
因子尺度变换及其在土壤侵蚀抽样调查中的应用[D]. 北京:中国科学院大学,2020.
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