黄土高原煤碳产量占全国70%以上，大规模开采活动导致区域内生态环境退化与土壤侵蚀加剧。已有研究主要探讨了煤炭开采对土壤属性、植被覆盖等环境要素的影响，然而鲜有研究定量研究煤矿区土壤侵蚀时空特征及其与环境变化的关系，限制了煤矿区土地复垦与生态修复。本研究基于遥感影像解译、实测数据等资料与方法，分析了2003-2019年间黄土高原彬长煤矿区气象、地形、植被、土地利用、土壤性质等环境因子的时空变化特征；探究了2014-2019年彬长矿区开采所致的地表沉降；利用修订的通用土壤流失方程（Revised Universal Soil Loss Equation，RUSLE）模拟了矿区2003-2019年逐年与2014-2019年逐季节土壤侵蚀速率，并结合历史调查数据验证了模型模拟精度，进而阐明矿区年尺度（2003-2019年）与季节尺度（2014-2019年）土壤侵蚀的时空变化规律；最后，综合评估环境因子变化和土壤侵蚀模拟结果，定量分析彬长矿区环境变化对土壤侵蚀的影响。主要研究结果如下：

  （1）环境变化方面。2003年至2019年间，彬长矿区降水量波动幅度较大，呈非显著上升趋势（p>0.05），其中侵蚀性降雨（日降水量>12 mm）约占总降水量的60%；矿区平均植被覆盖度呈显著上升趋势（p<0.01），年增长率约为1%；矿区城镇建设用地和林地面积均呈显著上升趋势（p<0.01），耕地和草地面积非显著下降（p>0.05），水体面积无明显变化；年植被覆盖度与年降水量相关性较弱（R²=0.090，p>0.05），与林地面积变化显著正相关（R²=0.629，p<0.01）。2014至2019年间，彬长矿区有9处较明显的开采沉陷，累计沉陷量在58.94 mm至97.45 mm之间；沉陷区植被覆盖度波动幅度大于非沉陷区；各沉陷区的土地利用变化不同，累计沉陷量越大的区域，土地利用面积波动幅度越大；季节植被覆盖度与季节降水量（2014-2019年）显著正相关（R²=0.623，p<0.01）。

  （2）土壤侵蚀时空分布特征。RUSLE模型模拟结果表明，2006年彬长矿区整体土壤侵蚀速率为25.80 t•ha^-1•a^-1，2014-2019年沉陷区年均侵蚀速率为矿区整体的122%，与2006年野外调查结果接近（25.46 t•ha^-1•a^-1、132%），表明模拟结果精度较高。2003-2019年间，矿区平均侵蚀速率39.69 t•ha^-1•a^-1，2003年土壤侵蚀速率最高（85.56 t•ha^-1•a^-1），2009年最低（15.54 t•ha^-1•a^-1）；平均侵蚀速率在2003-2019年间呈非显著下降趋势（p>0.05），侵蚀速率减小的区域占矿区总面积的63.59%，但矿区大部分区域（94.74%）的侵蚀速率变化不显著。2014年至2019年，矿区土壤侵蚀速率季节分布呈夏季高、冬季低的特点；沉陷区侵蚀速率在年尺度上和季节尺度上均高于矿区平均侵蚀速率，矿区平均侵蚀速率越大时，沉陷区侵蚀速率与矿区平均侵蚀速率差异越大，说明沉陷区对侵蚀更为敏感。

  （3）环境变化对土壤侵蚀的影响方面。2003年至2019年间，年土壤侵蚀速率与降水量显著正相关（R²=0.60，p<0.01），与植被覆盖度和土地利用面积变化关系不显著（p>0.05）。空间分布上，植被覆盖度较高的区域侵蚀相对较小；由于林地、城镇建设用地等面积增加，彬长矿区土壤侵蚀速率较低的区域面积明显上升。2014年至2019年间，沉陷区季节土壤侵蚀速率与降水量、地表沉陷量显著正相关（R²>0.60，p<0.01），降水量对侵蚀的影响大于地表沉陷量，侵蚀速率与植被覆盖度变化关系不显著（p>0.05）。季节尺度上各因子对侵蚀的影响排序为降水量>沉陷量>植被覆盖度。

The Loess Plateau produces over 70% of China’s coal, and large-scale mining activities have led to serious ecological degradation and soil erosion problems in the region. Previous studies have primarily focused on the effects of coal mining on soil properties, vegetation coverage and other environmental elements. However, few studies have quantitatively investigated the spatial and temporal distribution of soil erosion in coal mining areas and its relationship with environmental change, constraining land reclamation and ecological restoration in the coal mining areas. This study investigated the spatial and temporal variability of environmental factors such as meteorology, topography, vegetation cover, land use and soil properties in the Binchang coal mining area on the Loess Plateau from 2003 to 2019 based on remote sensing image interpretation and field measured data, and explored land subsidence caused by mining in the Binchang mining area from 2014 to 2019. The Revised Universal Soil Loss Equation (RUSLE) was employed to estimate the annual soil erosion rates during 2003-2019 and seasonal erosion rates during 2014-2019, while the accuracy of modelling results was verified with historical field survey results. Based on the modelling results, the spatiotemporal pattern of annual (2003-2019) and seasonal (2014-2019) soil erosion rates over the mining area was investigated. Lastly, the relationships between environmental changes and modelled erosion rates were studied to assess the impact of environmental changes on soil erosion in the Binchang mining area. The main findings are as follows.

(1) Between 2003 and 2019, precipitation in the Binchang mining area fluctuated considerably and showed an insignificant upward trend (p>0.05), with erosive rainfall (daily precipitation >12 mm) accounting for about 60% of the total precipitation; the average vegetation cover in the mining area showed a significant upward trend (p<0.01), with the annual growth rate being approximately 1%; The area of built-up region and forest showed a significant upward trend (p<0.01), while that of arable land and grassland decreased insignificantly (p>0.05), and water bodies did not change significantly; the annual vegetation cover was weakly related with annual precipitation (R²=0.090, p>0.05), and significantly positively related with the changes in forest land area (R²=0.629, p<0.01). During 2014-2019, nine areas with land subsidence were found, with cumulative subsidence ranging from 58.94 mm to 97.45 mm; vegetation coverage was more fluctuating in the subsidence areas than that in areas without subsidence; land use changes differed among the subsidence areas, with fluctuations in land use area being greater in areas with greater cumulative subsidence; and a significantly positive correlation was found between seasonal vegetation coverage and seasonal precipitation (2014-2019) (R² = 0.623, p <0.01).

(2) The RUSLE modelling results showed that the overall soil erosion rate of the Binchang mining area in 2006 was 25.80 t•ha^-1•a^-1, and the average annual erosion rate of the subsidence area from 2014-2019 was 122% that of the overall mine area, which are close to the field survey results in 2006 (25.46 t•ha^-1•a^-1, p < 0.01). This demonstrated that the modelling results were satisfactory. During 2003-2019, the average erosion rate of the mining area was 39.69 t•ha^-1•a^-1, with the highest erosion rate occurring in 2003 (85.5 t•ha^-1•a^-1). The highest and lowest erosion rate (85.56 t•ha^-1•a^-1) was found in 2003 and 2009 (15.54 t•ha^-1•a^-1), respectively; the average erosion rate showed an insignificant decreasing trend between 2003 and 2019 (p> 0.05), and the area with decreased erosion rate accounted for 63.59% of the Binchang mining area, but most of the mining area (94.74%) showed an insignificant erosion rate change. During 2014-2019, soil erosion rate was found to be high in summer and low in winter; the soil erosion rate in the subsidence area was higher than the average soil erosion rate across the mining area on both the annual scale and seasonal scale. The greater the average erosion rate, the greater the difference between the erosion rate of the subsidence area and the whole mining area. This indicated that the subsidence area was more prone to erosion.

(3) From 2003 to 2019, annual soil erosion rate was significantly and positively correlated with precipitation (R²=0.60, p<0.01), but insignificantly related with changes in vegetation coverage and land use area (p>0.05). In terms of spatial distribution, erosion rates were found to be relatively lower in areas with high vegetation coverage; the area with low soil erosion rate in the Binchang coal mining area increased significantly due to the increase in the area of forest land and urban construction land. Between 2014 and 2019, seasonal erosion rate in the subsidence area was significantly positively correlated with precipitation and the amount of surface subsidence (R²>0.60, p<0.01). The impact of precipitation on erosion was stronger than that of subsidence. No significant relationship was found between erosion rate and vegetation coverage (p>0.05). The effect of the factors on erosion on a seasonal scale followed the sequence of precipitation > subsidence > vegetation coverage.

[1] MORGAN R P C. Soil erosion and conservation [M]. John Wiley & Sons, 2009.

[2] 张桃林. 土壤退化研究的进展与趋向 [C]// 1999, 中国土壤学会海峡两岸土壤肥料学术研讨会.

[3] 张洪江. 土壤侵蚀原理 [M]. 中国林业出版社, 2000.

[4] VAN OOST K, QUINE T, GOVERS G, et al. The impact of agricultural soil erosion on the global carbon cycle [J]. Science, 2007, 318(5850): 626-629.

[5] ROTHWELL J J, LINDSAY J B, EVANS M G, et al. Modelling suspended sediment lead concentrations in contaminated peatland catchments using digital terrain analysis [J]. ecological engineering, 2010, 36(5): 623-630.

[6] SMITH J R. Soil Erosion and its remedy by terracing and tree planting [J]. Science, 1914, 39(1015): 858.

[7] BENNETT H H. Some Aspects of Soil Erosion as a National Problem [J]. Routledge Falmer Reader in History of Education, 1929, 10(2001): 55-74

[8] BATES C G, ZEASMAN O R. Soil erosion - a local and national problem [J]. 1930, 1-100.

[9] LOWDERMILK W C. Influence of Forest Litter on Run-Off, Percolation, and Erosion [J]. Journal of Forestry, 1930, 28(4): 474-91(18).

[10] WALKER R H, BROWN P E. Soil erosion in Iowa [J]. Proceedings of the Iowa Academy of Science, 1936, 79(2): 92-95.

[11] SHARPE C. Landslides and related phenomena [J]. Soil Science, 1938, 3-137.

[12] 崔宗培. 中国水利百科全书 [M]. 水利电力出版社, 1991.

[13] ZHANG L, WANG J, BAI Z, et al. Effects of vegetation on runoff and soil erosion on reclaimed land in an opencast coal-mine dump in a loess area [J]. Catena, 2015, 128:44-53.

[14] 田冲, 汤达祯, 周志军, 等. 彬长矿区水文地质特征及其对煤层气的控制作用 [J]. 煤田地质与勘探, 2012, 40(1): 45-48.

[15] 钱鸣高, 许家林, 缪协兴. 煤矿绿色开采技术 [J].中国矿业大学学报, 2003(04): 5-10.

[16] 王双明, 黄庆享, 范立民, 等. 生态脆弱区煤炭开发与生态水位保护 [M]. 科学出版社, 2010.

[17] 白中科, 赵景逵, 李晋川, 等. 大型露天煤矿生态系统受损研究——以平朔露天煤矿为例 [J]. 生态学报, 1999(06): 870-875.

[18] 黄翌, 汪云甲, 王猛, 等. 黄土高原山地采煤沉陷对土壤侵蚀的影响 [J]. 农业工程学报, 2014, 30(1): 228-235.

[19] LI P, MU X, HOLDEN J, et al. Comparison of soil erosion models used to study the Chinese Loess Plateau [J]. Earth-Science Reviews, 2017, 170:17-30.

[20] 蔡强国, 刘纪根. 关于我国土壤侵蚀模型研究进展 [J]. 地理科学进展, 2003, 22(3): 242-250.

[21] RENARD K G, FOSTER G R, WEESIES G A, et al. RUSLE: Revised universal soil loss equation [J]. Journal of soil and Water Conservation, 1991, 46(1): 30-33.

[22] LI P, ZANG Y, MA D, et al. Soil erosion rates assessed by RUSLE and PESERA for a Chinese Loess Plateau catchment under land‐cover changes [J]. Earth Surface Processes and Landforms, 2020, 45(3): 707-722.

[23] RENARD K G, FOSTER G R, WEESIES G, et al. Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE) [M]. United States Department of Agriculture Washington, DC, 1997.

[24] WALTHAM A C. Ground subsidence [M]. United Kingdom, 1989.

[25] KRATZSCH H. Mining subsidence engineering [M]. Springer Science & Business Media, 2012.

[26] CARNEC C, DELACOURT C. Three years of mining subsidence monitored by SAR interferometry, near Gardanne, France [J]. Journal of applied geophysics, 2000, 43(1): 43-54.

[27] BOZEMAN M. Underground hard-rock mining: subsidence and hydrologic environmental impacts [J]. Center for science in public participation, 2002.

[28] BAEK J, KIM S W, PARK H J, et al. Analysis of ground subsidence in coal mining area using SAR interferometry [J]. Geosciences Journal, 2008, 12(3): 277-284.

[29] TOM-DERY D, DAGBEN Z, COBBINA S J. Effect of illegal small-scale mining operations on vegetation cover of arid northern Ghana [J]. Research journal of environmental and earth sciences, 2012, 4(6): 674-679.

[30] MORENO-DE LAS HERAS M, NICOLAU J, ESPIGARES T. Vegetation succession in reclaimed coal-mining slopes in a Mediterranean-dry environment [J]. Ecological engineering, 2008, 34(2): 168-178.

[31] SCHMIDT H, GLAESSER C. Multitemporal analysis of satellite data and their use in the monitoring of the environmental impacts of open cast lignite mining areas in Eastern Germany [J]. International Journal of Remote Sensing, 1998, 19(12): 2245-2260.

[32] PECHAROVA E, BROUMOVÁ-DUŠÁKOVÁ H, NOVOTNÁ K, et al. Function of vegetation in new landscape units after brown coal mining [J]. International Journal of Mining, Reclamation and Environment, 2011, 25(4): 367-376.

[33] LATIFOVIC R, FYTAS K, CHEN J, et al. Assessing land cover change resulting from large surface mining development [J]. International journal of applied earth observation and geoinformation, 2005, 7(1): 29-48.

[34] MALAVIYA S, MUNSI M, OINAM G, et al. Landscape approach for quantifying land use land cover change (1972–2006) and habitat diversity in a mining area in Central India (Bokaro, Jharkhand) [J]. Environmental monitoring and assessment, 2010, 170(1): 215-229.

[35] PANDEY B, AGRAWAL M, SINGH S. Ecological risk assessment of soil contamination by trace elements around coal mining area [J]. Journal of Soils and Sediments, 2016, 16(1): 159-168.

[36] SIKDAR P K, CHAKRABORTY S, ADHYA E, et al. Land use/land cover changes and groundwater potential zoning in and around Raniganj coal mining area, Bardhaman District, West Bengal-a GIS and remote sensing approach [J]. Journal of Spatial Hydrology, 2004, 4(2).

[37] 张安兵, 张兆江, 高井祥, 等. GPS用于矿区沉陷区地表高精度动态监测的可行性研究 [J]. 煤炭学报, 2009, 34(10): 1322-1327.

[38] 张安兵. 动态变形监测数据混沌特性分析及预测模型研究 [D]. 北京:中国矿业大学, 2009.

[39] 杨成生. 基于 D-InSAR 技术的煤矿沉陷监测 [D]. 西安:长安大学, 2008.

[40] 汤伏全, 李林宽, 李小涛, 刘世伟. 基于无人机影像的采动地表裂缝特征研究 [J].煤炭科学技术, 2020, 48(10): 130-136.

[41] 黄丹勇. 矿区土地复垦与生态环境恢复综述 [J]. 湖南有色金属, 2011, 27(6): 45-48.

[42] 郭逍宇, 张金屯, 宫辉力, 等. 安太堡矿区复垦地植被恢复过程多样性变化 [J]. 生态学报, 2005, (04): 763-770.

[43] WU Q, LIU K, SONG C, et al. Remote sensing detection of vegetation and landform damages by coal mining on the Tibetan Plateau [J]. Sustainability, 2018, 10(11): 3851.

[44] 陈秋计. 基于GIS的煤矿区土地损毁程度评价研究 [J]. 矿业研究与开发, 2013, 33(04): 77-80.

[45] 刘英, 雷少刚, 陈孝杨, 等. 神东矿区植被覆盖度时序变化与驱动因素分析及引导恢复策略 [J/OL]. 煤炭学报: 1-14 [2021-06-05].

[46] GILLEY J E, GEE G, BAUER A, et al. Runoff and erosion characteristics of surface-mined sites in western North Dakota [J]. Transactions of the ASAE, 1977, 20(4): 697-700.

[47] CARROLL C, MERTON L, BURGER P. Impact of vegetative cover and slope on runoff, erosion, and water quality for field plots on a range of soil and spoil materials on central Queensland coal mines [J]. Soil Research, 2000, 38(2): 313-328.

[48] MORENO-DE LAS HERAS M, MERINO-MART N L, NICOLAU J. Effect of vegetation cover on the hydrology of reclaimed mining soils under Mediterranean-Continental climate [J]. Catena, 2009, 77(1): 39-47.

[49] YELLISHETTY M, MUDD G M, SHUKLA R. Prediction of soil erosion from waste dumps of opencast mines and evaluation of their impacts on the environment [J]. International Journal of Mining, Reclamation and Environment, 2013, 27(2): 88-102.

[50] CHABUKDHARA M, SINGH O P. Coal mining in northeast India: an overview of environmental issues and treatment approaches [J]. International Journal of Coal Science & Technology, 2016, 3(2): 87-96.

[51] BARGAWA W S, PUTRA A, NURCHOLIS M. Analysis of erosion using hydroseeding on post coal mining in Melak site [J]. International Journal of GEOMATE, 2019: 1-7.

[52] KARAN S K, GHOSH S, SAMADDER S R. Identification of spatially distributed hotspots for soil loss and erosion potential in mining areas of Upper Damodar Basin–India [J]. Catena, 2019, 182: 104144.

[53] LAYEGHI N, JAVADI S A, JAFARI M, et al. Measuring the Land Use Based Risk of Soil Erosion in a Mining-Dominated Landscape in Northern Iran [J]. Journal of Ecological Engineering, 2020, 21: 7.

[54] RAMLI M, THAMRIN M, ASRAFIL M. Analysis of Soil Erosion on Mine Area [C]// IOP Conference Series: Materials Science and Engineering. IOP Publishing, 2020, 875(1): 012052.

[55] PACETTI T, LOMPI M, PETRI C, et al. Mining activity impacts on soil erodibility and reservoirs silting: Evaluation of mining decommissioning strategies [J]. Journal of Hydrology, 2020, 589: 125107.

[56] 白中科, 段永红, 杨红云, 等. 采煤沉陷对土壤侵蚀与土地利用的影响预测 [J]. 农业工程学报, 2006(06): 67-70.

[57] 王丽云, 王小燕, 王义, 等. 神东矿区2005—2018年水土流失动态变化研究 [J]. 中国水土保持, 2021(01): 60-62.

[58] 王晓彤, 张加琼, 杨明义, 王永吉. 榆神府矿区典型小流域侵蚀产沙对退耕还林(草)及煤矿开采的响应 [J]. 应用生态学报, 2020, 31(06): 1971-1979.

[59] 周颖. 新疆准东矿区土壤风蚀研究 [D]. 乌鲁木齐:新疆大学, 2016.

[60] 高钏. 江淮丘陵矿产资源集中区典型县土地利用与土壤侵蚀分布特征 [D]. 泰安:山东农业大学, 2019.

[61] 黄颖伟. 辽宁省矿区遥感调查及土壤侵蚀估算研究 [D]. 沈阳:沈阳农业大学, 2018.

[62] 兰利花, 田毅. 土壤地带性分布下的典型矿区土壤修复模式 [J]. 江西农业学报, 2021, 33(01): 40-49.

[63] TSUNEKAWA A, LIU G, YAMANAKA N, et al. Restoration and Development of the Degraded Loess Plateau, China [M]. Springer Japan, 2014.

[64] 王金成, 井明博, 段春燕, 等. 陇东黄土高原石油污染土壤环境因子对金盏菊 (Calendula officinalis)-微生物联合修复的响应 [J]. 环境科学学报, 2015, 35(9): 2971-2981.

[65] 程爱国, 宁树正, 袁同兴. 中国煤炭资源综合区划研究 [J]. 中国煤炭地质, 2011, 23(08): 5-8.

[66] 唐克丽, 陈永宗. 黄土高原地区土壤侵蚀区域特征及其治理途径 [J]. 北京: 中国科学技术出版社, 1991, 19(90): 1-2.

[67] 牛冲槐, 张敏, 樊燕萍. 山西省煤炭开采对生态环境影响评价 [J]. 太原理工大学学报, 2006, 37(6): 649-653.

[68] 景可, 陈永宗, 卢金发. 黄河下游治理中几个问题的讨论 [J]. 人民黄河, 1988, (04): 58-63.

[69] 魏忠义, 马锐, 白中科, 等. 露天矿大型排土场水蚀特征及其植被控制效果研究——以安太堡露天煤矿南排土场为例 [J]. 水土保持学报, 2004, 18(1): 164-167.

[70] 王贞. 神东煤田不同下垫面侵蚀产沙规律及水动力参数特征 [D]. 杨凌:中国科学院研究生院 (教育部水土保持与生态环境研究中心), 2011.

[71] 吕春娟, 白中科, 赵景逵. 矿区土壤侵蚀与水土保持研究进展 [J]. 水土保持学报, 2003, 17(6): 85-88.

[72] 刘瑞顺. 内蒙古永利煤矿排土场边坡土壤侵蚀调查与试验研究 [D]. 杨凌:西北农林科技大学, 2014.

[73] 马雄德, 范立民, 张晓团, 等. 陕西省榆林市榆神府矿区土地荒漠化及其景观格局动态变化 [J]. 灾害学, 2015, 30(04): 126-129.

[74] 王尚义, 石瑛, 牛俊杰, 等. 煤矸石山不同植被恢复模式对土壤养分的影响——以山西省河东矿区1号煤矸石山为例 [J]. 地理学报, 2013, 68(3): 372-379.

[75] 何书金, 郭焕成, 韦朝阳, 等. 中国煤矿区的土地复垦 [J]. 地理研究, 1996, 15(3): 23-32.

[76] 李新举, 胡振琪, 李晶, 等. 采煤塌陷地复垦土壤质量研究进展 [J]. 农业工程学报, 2007, 23(6): 276-280.

[77] 黄广龙, 周建, 龚晓南. 矿山排土场散体岩土的强度变形特性 [J]. 浙江大学学报(工学版), 2000, 34(1): 56-61.

[78] 王世云. 黄土高原露天煤矿复垦农用地跟踪监测研究 [D]. 北京:中国地质大学, 2014.

[79] 吕春娟. 矿区排土场岩土侵蚀特征及植被恢复的水保效应 [D]. 晋中:山西农业大学, 2004.

[80] 史沛丽, 张玉秀, 胡振琪, 等. 采煤塌陷对中国西部风沙区土壤质量的影响机制及修复措施 [J]. 中国科学院大学学报, 2017, 34(03): 318-328.

[81] 贾俊姝, 周心澄, 高国雄, 等. 采煤沉陷区土地利用变化及其景观异质性分析―以山西省东大煤矿为例 [J]. 水土保持通报, 2007, 27(6): 199-202.

[82] 孙琦. 大型露天煤矿土地损毁生态风险评价及空间防范措施 [D]. 北京:中国地质大学, 2014.

[83] 庞志刚. 金堆城北部排土场水土流失灾害现状及治理对策研究 [D]. 西安:长安大学, 2014.

[84] 姚维岭, 余江宽, 路云阁. 基于 ZY-3 卫星数据的神东煤矿区土地退化人为影响因素调查与评价 [J]. 生态与农村环境学报, 2016, 32(3): 355-360.

[85] 聂小军, 高爽, 陈永亮, 张合兵. 西北风积沙区采煤扰动下土壤侵蚀与养分演变特征 [J]. 农业工程学报, 2018, 34(02): 127-134.

[86] ZHAO B, XIANG Y, YAO W, et al. Monitoring surface subsidence in the Binchang mining area using small baseline subset differential interferometric synthetic aperture radar with Sentinel-1A data [J]. Journal of Applied Remote Sensing, 2020, 14(4): 044507.

[87] 刘宝元, 张科利, 焦菊英. 土壤可蚀性及其在侵蚀预报中的应用 [J]. 自然资源学报, 1999(04): 345-350.

[88] CARLSON T N, RIPLEY D A. On the relation between NDVI, fractional vegetation cover, and leaf area index [J]. Remote sensing of Environment, 1997, 62(3): 241-252.

[89] 刘纪远, 布和, 敖斯尔. 中国土地利用变化现伟过程时空特征的研究——基于卫星遥感数据 [J]. 第四纪研究, 2000(03): 229-239.

[90] YE X, KAUFMANN H, GUO X. Landslide monitoring in the Three Gorges area using D-InSAR and corner reflectors [J]. Photogrammetric Engineering & Remote Sensing, 2004, 70(10): 1167-1172.

[91] SOUSA J J, RUIZ A M, HANSSEN R F, et al. PS-InSAR processing methodologies in the detection of field surface deformation—Study of the Granada basin (Central Betic Cordilleras, southern Spain) [J]. Journal of Geodynamics, 2010, 49(3-4): 181-189.

[92] TIZZANI P, BERARDINO P, CASU F, et al. Surface deformation of Long Valley caldera and Mono Basin, California, investigated with the SBAS-InSAR approach [J]. Remote Sensing of Environment, 2007, 108(3): 277-289.

[93] BERARDINO P, FORNARO G, LANARI R, et al. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms [J]. IEEE Transactions on geoscience and remote sensing, 2002, 40(11): 2375-2383.

[94] 章文波, 谢云, 刘宝元. 用雨量和雨强计算次降雨侵蚀力 [J]. 地理研究, 2002 (03): 384-390.

[95] 章文波, 谢云, 刘宝元. 利用日雨量计算降雨侵蚀力的方法研究 [J]. 地理科学, 2002, 22(6): 705-711.

[96] 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.

[97] 蔡崇法, 丁树文, 史志华, 等. 应用 USLE 模型与地理信息系统 IDRISI 预测小流域土壤侵蚀量的研究 [J]. 水土保持学报, 2000(02): 19-24.

[98] 喻锋, 李晓兵, 陈云浩, 等. 皇甫川流域土地利用变化与土壤侵蚀评价 [J]. 生态学报, 2006, 26(6): 1947-1956.

[99] 江忠善, 李秀英. 黄土高原土壤流失预报方程中降雨侵蚀力和地形因子的研究 [J].中国科学院西北水土保持研究所集刊, 1988(01): 40-45.

[100] 张勇, 宋世杰, 杜华栋, 等. 彬长采煤沉陷区水土流失地下关键影响因子甄选 [J].陕西水利, 2018, (06): 133-135+138.

[101] 张勇, 张安虎. 彬长矿区水土流失特征分析与水土保持关键问题 [J]. 能源与环境, 2012, (05): 70-71.

[102] 张勇. 井下采煤的地表水土流失及植被效应研究 [D]. 西安:西安科技大学, 2015.

[103] 杨梅忠, 巨天乙, 马东民, 等. 彬长矿区环境地质灾害的分析预测 [J]. 煤矿环境保护,1999, (05): 30-32.

[104] LI P, MU X, HOLDEN J, et al. Comparison of soil erosion models used to study the Chinese Loess Plateau [J]. Earth-Science Reviews, 2017, 170: 17-30.