1. 西北农林科技大学 水土保持研究所 黄土高原土壤侵蚀与旱地农业 国家重点实验室, 陕西 杨陵,712100
2. 中国科学院 水利部 水土保持研究所, 陕西 杨陵,712100
纸质出版:2022
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孟祥冬, 曾奕, 方怒放. 地形和土地利用对黄土丘陵沟壑区土壤侵蚀速率的影响[J]. 水土保持通报, 2022,42(5):25-32.
Meng Xiangdong, Zeng Yi, Fang Nufang. Effects of Topography and Land Use on Soil Erosion Rate in Loess Hilly and Gully Region[J]. Bulletin of Soiland Water Conservation, 2022, 42(5): 25-32.
孟祥冬, 曾奕, 方怒放. 地形和土地利用对黄土丘陵沟壑区土壤侵蚀速率的影响[J]. 水土保持通报, 2022,42(5):25-32. DOI: 10.13961/j.cnki.stbctb.20220525.002.
Meng Xiangdong, Zeng Yi, Fang Nufang. Effects of Topography and Land Use on Soil Erosion Rate in Loess Hilly and Gully Region[J]. Bulletin of Soiland Water Conservation, 2022, 42(5): 25-32. DOI: 10.13961/j.cnki.stbctb.20220525.002.
[目的
]
分析地形和土地利用对坝控小流域侵蚀速率的影响,为黄土丘陵沟壑区土壤侵蚀治理和水土保持措施的制定提供理论依据。[方法
]
基于无人机(unmanned aerial vehicle,UAV)摄影测量技术获取流域高分辨率数字高程模型(digital elevation model,DEM)和影像数据并准确提取流域的地形因子和土地利用要素,采用偏最小二乘回归方法确定坝控小流域地形和土地利用对土壤侵蚀速率的影响及其相对重要性。[结果
]
坝控小流域侵蚀速率变化范围为2 869~14 191 t/(km
2
·a),平均侵蚀速率为9 984 t/(km
2
·a);坝控小流域的地形和土地利用因子存在一定差异,LS因子与L因子、连通性指数(IC)与地形湿度指数(TWI)、流域面积(A)与流域长度(BL)和形状因子(Ff)之间存在显著相关性(p<0.01);侵蚀速率偏最小二乘回归模型中最大VIP值为坡长因子(VIP=1.66;RCs=0.30),其次是地形湿度指数(VIP=1.62;RCs=0.25)、坡度坡长因子(VIP=1.43;RCs=0.27)、连通性指数(VIP=1.39;RCs=-0.19)、农地面积占比(VIP=1.03;RCs=0.10)和草地面积占比(VIP=1.03;RCs=-0.10)。[结论
]
各坝控小流域侵蚀速率存在显著差异,坡长因子、坡度坡长因子、地形湿度指数、连通性指数、农地面积比例和草地面积比例是影响流域侵蚀速率的重要影响因子,且VIP值都大于1。
[Objective] The influence of topography and land use on the soil erosion rate of dam-controlled catchments was analyzed in order to provide a theoretical basis for soil erosion control and soil and water conservation measures in a loess hilly and gully region. [Methods] A high-resolution digital elevation model (DEM) and image data for catchments were obtained by use of unmanned aerial vehicle (UAV) photogrammetry technology. Topographical factors and land use of the catchments were accurately extracted. Partial least squares regression was used to determine the impact and relative importance of topography and land use on soil erosion rate in dam-controlled catchments. [Results] The variation range of soil erosion rate in dam-controlled catchments was 2 869~14 191 t/(km2·yr)
with an average value of 9 984 t/(km2·yr). Differences existed in topographic and land use factors in dam-controlled catchments. Significant correlations (p<0.01) were observed between LS factor and L factor; connectivity index (IC) and topographic wetness index (TWI); catchment area (A) and watershed length (BL) and shape factor (Ff). From the partial least squares regression of soil erosion rate
the maximum VIP value was detected for the slope length factor (VIP=1.66; RCs=0.30)
followed by topographic wetness index (VIP=1.62; RCs=0.25)
LS factor (VIP=1.43; RCs=0.27)
connectivity index (VIP=1.39; RCs=-0.19)
percentage of agricultural area (VIP=1.03; RCs=0.10)
and percentage of grassland area (VIP=1.03; RCs=-0.10). [Conclusion] There were significant differences in soil erosion rate in the dam-controlled catchments. Slope length factor
LS factor
topographic wetness index
connectivity index
percentage of agricultural area
and percentage of grassland area were important factors influencing soil erosion rate
with all having VIP values greater than 1.
Alewell C, Ringeval B, Ballabio C, et al. Global phosphorus shortage will be aggravated by soil erosion [J]. Nature Communications, 2020,11:4546.
Borrelli P, Robinson D A, Fleischer L R, et al. An assessment of the global impact of 21st century land use change on soil erosion [J]. Nature Communications, 2017,8(1):2013.
Lal R. Soil erosion by wind and water: Problems and prospects [M]//Soil Erosion Research Methods: Routledge, 2017:1-10.
Sartori M, Philippidis G, Ferrari E, et al. A linkage between the biophysical and the economic: Assessing the global market impacts of soil erosion [J]. Land Use Policy, 2019,86:299-312.
Wuepper D, Borrelli P, Finger R. Countries and the global rate of soil erosion [J]. Nature Sustainability, 2020,3(1):51-55.
Jiang Chong, Yang Zhiyuan, Li Minting, et al. Exploring soil erosion trajectories and their divergent responses to driving factors: A model-based contrasting study in highly eroded mountain areas [J]. Environmental Science and Pollution Research International, 2021,28(12):14720-14738.
Liu Wen, Li Zhenwei, Zhu Jingxuan, et al. Dominant factors controlling runoff coefficients in Karst watersheds [J]. Journal of Hydrology, 2020,590:125486.
郝姗姗,李梦华,马永强,等.黄土丘陵区土壤侵蚀因子敏感性分析[J].中国水土保持科学,2019,17(2):77-86.
史志华,宋长青.土壤水蚀过程研究回顾[J].水土保持学报,2016,30(5):1-10.
Wang Xiao, Zhao Xiaoli, Zhang Zengxiang, et al. Assessment of soil erosion change and its relationships with land use/cover change in China from the end of the 1980s to 2010 [J]. Catena, 2016,137:256-268.
Fu Bojie, Wang Shuai, Liu Yu, et al. Hydrogeomorphic ecosystem responses to natural and anthropogenic changes in the loess plateau of China [J]. Annual Review of Earth and Planetary Sciences, 2017,45(1):223-243.
Sun Wenyi, Shao Quanqin, Liu Jiyuan, et al. Assessing the effects of land use and topography on soil erosion on the Loess Plateau in China [J]. Catena, 2014,121:151-163.
Zhang H Y, Shi Z H, Fang N F, et al. Linking watershed geomorphic characteristics to sediment yield: Evidence from the Loess Plateau of China [J]. Geomorphology, 2015,234:19-27.
Rajbanshi J, Bhattacharya S. Assessment of soil erosion, sediment yield and basin specific controlling factors using RUSLE-SDR and PLSR approach in Konar River basin, India [J]. Journal of Hydrology,2020,587:124935.
Li Zhenwei, Xu Xianli, Zhu Jingxuan, et al. Effects of lithology and geomorphology on sediment yield in Karst mountainous catchments [J]. Geomorphology, 2019,343:119-128.
Wang Chunmei, Yang Qinke, Guo Weiling, et al. Influence of resolution on slope in areas with different topographic characteristics [J]. Computers & Geosciences, 2012,41:156-168.
Lu Shaojuan, Liu Baoyuan, Hu Yaxian, et al. Soil erosion topographic factor (LS): Accuracy calculated from different data sources [J]. Catena, 2020,187:104334.
Fisher J R B, Acosta E A, Dennedy-Frank P J, et al. Impact of satellite imagery spatial resolution on land use classification accuracy and modeled water quality [J]. Remote Sensing in Ecology and Conservation, 2018,4(2):137-149.
Mulakala J. Measurement Accuracy of the DJI Phantom 4 RTK & Photogrammetry [M]. DroneDeploy, Published in Partnership with DJI, 2019.
Fang N F, Zeng Y, Ni L S, et al. Estimation of sediment trapping behind check dams using high-density electrical resistivity tomography [J]. Journal of Hydrology, 2019,568:1007-1016.
Zeng Yi, Fang Nufang, Shi Zhihua. Effects of human activities on soil organic carbon redistribution at an agricultural watershed scale on the Chinese Loess Plateau [J]. Agriculture, Ecosystems & Environment, 2020,303:107112.
陈晓征.基于高精度DEM的黄土淤地坝信息提取及特征分析[D].江苏 南京:南京师范大学,2020.
刘蓓蕾.黄土高原淤地坝建设与地形特征的响应关系研究[D].陕西 西安:西安理工大学,2021.
Moore I D, Grayson R B, Ladson A R. Digital terrain modelling: A review of hydrological, geomorphological, and biological applications [J]. Hydrological Processes, 1991,5(1):3-30.
Shi Z H, Ai L, Li X, et al. Partial least-squares regression for linking land-cover patterns to soil erosion and sediment yield in watersheds [J]. Journal of Hydrology, 2013,498:165-176.
魏艳红.延河与皇甫川流域典型淤地坝淤积特征及其对输沙变化的影响[D].北京: 中国科学院教育部水土保持与生态环境研究中心,2017.
汪亚峰,傅伯杰,侯繁荣,等.基于差分GPS技术的淤地坝泥沙淤积量估算[J].农业工程学报,2009,25(9):79-83.
张信宝,温仲明,冯明义,等.应用
137
Cs示踪技术破译黄土丘陵区小流域坝库沉积赋存的产沙记录[J].中国科学(D辑:地球科学),2007,37(3):405-410.
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