Soil Water erosion status and its impact on the ecological environment in Yulin during coal exploitation over the recent 30 years based on the RUSLE model
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摘要:
研究目的 榆林市是中国重要的煤业化工基地，也是黄河中上游水土流失最严重的地区之一，研究榆林市煤炭开发过程中土壤水力侵蚀及其对生态环境的影响，对于推动区域高质量发展有重要作用。
研究方法 采用多源数据和修正通用土壤流失方程（RUSLE），估算1990—2020年榆林市土壤水力侵蚀量，分析其时空变化特征及对生态环境的潜在影响。
研究结果 结果表明，榆林市土壤水力侵蚀模数逐渐减弱，侵蚀强度均向下级转移，煤炭开发区土壤水蚀模数较低，且下降速率更快，煤炭开发带动区域经济发展，促进退耕还林政策实施和水土保持措施落地，使得植被覆盖因子C和水土保持措施因子P显著下降，植被覆盖度提升，生态环境整体趋优。
结论 研究揭示，该区域煤炭开发对水土保持的负面影响较小，通过合理的生态保护措施可实现资源开发与生态环境的良性互动，对该市生态环境保护与可持续发展具有重要的现实意义。
Abstract:Objectives Yulin City, an important coal industry and chemical base in China, is also one of the regions with the most severe soil erosion in the middle and upper reaches of the Yellow River. Studying soil water erosion and its impacts on the ecological environment during coal development in Yulin City is crucial for promoting high−quality regional development.
Methods This study uses multi−source data and the Revised Universal Soil Loss Equation (RUSLE) to estimate the amount of soil water erosion in Yulin City from 1990 to 2020, and analyzes its spatio−temporal variation characteristics and potential impacts on the ecological environment.
Results The results show that the soil water erosion modulus in Yulin City has gradually decreased, with the erosion intensity shifting to lower grades. The soil water erosion modulus in coal development areas is lower and has a faster decline rate. Coal development has promoted the implementation of the "returning farmland to forest" policy and soil and water conservation measures by driving regional economic development, leading to significant reductions in the vegetation coverage factor (C) and soil and water conservation measure factor (P), an increase in vegetation coverage, and an overall improvement in the ecological environment.
Conclusions The study reveals that coal development in this region has minimal negative impacts on soil and water conservation. Through reasonable ecological protection measures, a benign interaction between resource development and the ecological environment can be achieved, which is of important practical significance for ecological environmental protection and sustainable development in the city.
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Key words:
- soil water erosion /
- Yulin City /
- coal development /
- RUSLE model /
- spatiotemporal variation /
- ecological environment
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表 1 水土流失模型（RUSLE）各因子主要数据来源
Table 1. Main data sources of RUSLE factors
土壤水蚀因子 数据集 发布单位 分辨率 降雨侵蚀力因子R 中国1km分辨率逐月降水量数据集 国家地球系统科学数据中心 1 km 土壤可蚀性因子K 世界土壤数据库（HWSD） 联合国粮食及农业组织 1 km 坡长坡度因子LS 陕西30 m数字高程模型（DEM） 自然资源陕西省卫星应用技术中心 30 m 植被覆盖管理因子C NOAA CDR AVHRR NDVI 数据集 国家地球系统科学数据中心 5 km 水土保持措施因子P GlobeLand30数据集 国家基础地理信息中心 30 m 
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表 2 榆林地区农田水保措施因子P值
Table 2. P factor value of farmland in Yulin City
坡度/° ≤5 5~10 10~15 15~20 20~25 >25 P 0.11 0.22 0.31 0.58 0.74 0.80
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表 3 土壤水蚀强度分级
Table 3. Classification of soil erosion intensity
分级 级别 侵蚀模数/（t·hm−2 ·a−1) 1 微度侵蚀 <10 2 轻度侵蚀 10~25 3 中度侵蚀 25~50 4 强度侵蚀 50~80 5 极强度侵蚀 80~150 6 剧烈侵蚀 >150
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表 4 榆林地区土壤水蚀各因子特征值
Table 4. Characteristic values of soil erosion factors in Yulin
因子 单位 特征值 1990年 2000年 2010年 2020年 R (MJ.mm)/(hm2.h.a) 最大值 2020.80 1535.83 1970.7 2021.19 最小值 904.66 811.22 788.25 873.51 平均值 1521.50 1165.16 1336.40 1491.90 K (t.hm2)/(h.hm2.MJ.mm) 最大值 - - - 0.089 最小值 - - - 0 平均值 - - - 0.064 LS 无量纲 最大值 - - - 81.11 最小值 - - - 0.01 平均值 - - - 8.27 C 无量纲 最大值 1 1 1 1 最小值 0 0 0 0 平均值 0.232 0.223 0.225 0.148 P 无量纲 最大值 1 1 1 1 最小值 0 0 0 0 平均值 0.738 0.738 0.735 0.709
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表 5 榆林地区土壤水蚀情况
Table 5. Soil erosion in Yulin City
项目 区域 1990年 2000年 2010年 2020年 年均 土壤水蚀模数/
(t·hm−2·a−1)神府开发区 131.58 71.04 101.11 63.97 91.93 清水锦界开发区 80.72 41.31 64.86 31.65 54.64 金鸡滩麻黄梁开发区 43.88 27.42 37.55 21.17 32.50 榆横北开发区 32.33 20.17 22.33 13.79 22.15 榆横南开发区 171.20 159.91 131.55 88.23 137.72 开发区外 135.48 107.27 119.86 96.03 114.66 榆林市 128.10 100.84 110.67 85.57 106.29 土壤水蚀量/
(t·a−1)神府开发区 2.36×107 1.27×107 1.81×107 1.15×107 1.65×107 清水锦界开发区 1.36×107 6.95×106 1.09×107 5.33×106 9.19×106 金鸡滩麻黄梁开发区 6.54×106 4.09×106 5.60×106 3.15×106 4.84×106 榆横北开发区 8.67×106 5.41×106 5.99×106 3.70×106 5.94×106 榆横南开发区 6.57×107 6.13×107 5.05×107 3.38×107 5.28×107 开发区外 5.24×108 4.15×108 4.64×108 3.71×108 4.44×108 榆林市 6.42×108 5.05×108 5.55×108 4.29×108 5.33×108
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表 6 榆林地区各级土壤水蚀面积
Table 6. Soil erosion area at all levels in Yulin City
km2 分级 区域 1990年 2000年 2010年 2020年 微度侵蚀 煤炭开发区内 3260.97 3356.66 3349.74 3759.35 煤炭开发区外 8330.69 8789.18 8568.22 9551.08 总计 11591.66 12145.84 11917.97 13310.43 轻度侵蚀 煤炭开发区内 347.15 1025.68 586.70 1844.77 煤炭开发区外 2515.30 3339.03 2813.05 3798.28 总计 2862.45 4364.71 3399.75 5643.05 中度侵蚀 煤炭开发区内 1540.28 2196.92 2191.26 1768.46 煤炭开发区外 3813.38 4132.11 3945.23 4055.92 总计 5353.66 6329.03 6136.49 5824.38 强度侵蚀 煤炭开发区内 1488.35 920.75 1106.04 726.51 煤炭开发区外 3179.97 3225.99 3117.06 3197.85 总计 4668.31 4146.74 4223.10 3924.36 极强度侵蚀 煤炭开发区内 1231.28 890.63 1038.74 763.99 煤炭开发区外 4928.61 5206.30 5138.93 5056.67 总计 6159.89 6096.93 6177.67 5820.66 剧烈侵蚀 煤炭开发区内 1929.36 1406.74 1524.90 934.30 煤炭开发区外 10354.86 8430.21 9540.32 7463.02 总计 12284.22 9836.95 11065.22 8397.32
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[1] Beasley D B, Huggins L F, Monke E J. 1980. Answers: A model for watershed planning[J]. Transactions of the ASAE–American Society of Agricultural Engineers, 23(4): 938−944. doi: 10.13031/2013.34692
[2] Cai C F, Ding S W, Shi Z H, et al. 2000. Study of applying USLE and geographical information system IDRISI to predict soil erosion in small watershed[J]. Journal of Soil Water Conservation, 14(2): 19−24(in Chinese with English abstract).
[3] Cao W, Liu L L, Wu D. 2018. Soil erosion changes and driving factors in the Three−River Headwaters region[J]. Acta Prataculturae Sinica, 27(6): 10−22(in Chinese with English abstract).
[4] Chen F, Li H B. 2021. Spatial−temporal variations of soil erosion in Southern Yunnan Mountainous Area using GlS and RUSLE: A case study in Yuanyang County, Yunnan Province, China[J]. Chinese Journal of Applied Ecology, 32(2): 629−637(in Chinese with English abstract).
[5] Chen H. 2019. Spatial and temporal changes of soil erosion and its drivingfactors before and after the “Grain for Green” project in the Loess Plateau[D]. Doctoral Dissertation of Northwest A&F University of China(in Chinese with English abstract).
[6] Chen J, Liao A P, Tong X H, et al. 2015. Global land covermapping at 30m resolution: A POK−based operational approach[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 103: 7−27. doi: 10.1016/j.isprsjprs.2014.09.002
[7] De Roo A P J. 1996. The lisem project: An introduction[J]. Hydrological Prochydrological Processes, (10): 1021−1025.
[8] Flanagan D C, Ascough J C, Nicks A D. 1995. Overview of the WEPP erosion prediction mode[J]. USCD–Water Erosion Prediction Project.
[9] Fu S H, Liu B Y, Zhou Y G. 2015. Calculation tool of topographic factors[J]. Science of Soil and Water Conservation, 13(5): 105−110 (in Chinese with English abstract).
[10] Guo S Q, Han L, Zhao Y H, et al. 2019. Temporal and spatial changes of soil erosion and landscape pattern in the Qinling area[J]. Chinese Journal of Ecology, 38(7): 2167(in Chinese with English abstract).
[11] Hu Z Q, Li Y, Chen Y. 2020. The mechanism and key technology of the Yellow River sediment in ecological rehabilitation[J]. Journal of China University of Mining & Technology, 51(1): 1−15(in Chinese with English abstract).
[12] Li B Y, Ren Z Y, Yi L. 2015. Dynamic change trend of soil erosion in Yulin City from 2001 to 2010[J]. Arid Zone Research, 32(5): 918−925(in Chinese with English abstract).
[13] Li G Z, Fu S H, Liu B Y. 2012. Sampling program of water erosion inventory in the first national water resource survey[J]. Science of Soil and Water Conservation, 10(1): 77−81(in Chinese with English abstract).
[14] Li T H, Zheng L N. 2012. Soil erosion changes in the Yanhe watershed from 2001 to 2010 based on RUSLE mode[J]. Journal of Natural Resources, 27(7): 1164−1175(in Chinese with English abstract).
[15] Liu B Y, Nearing M A, Risse L M. 1994. Slope gradient effects on soil loss for steep slopes[J]. Transactions of the ASAE, 37(6): 1835−1840. doi: 10.13031/2013.28273
[16] Liu B Y, Nearing M A, Shi P J, et al. 2000. Slope length effects on soil loss for steep slopes[J]. Soil Science Society of America Journal, 64: 1759−1763. doi: 10.2136/sssaj2000.6451759x
[17] Liu G B, Shang Z P, Yao W Y, et al. 2017. Ecological effects of ecological projects on the Loess Plateau[J]. Bulletin of the Chinese Academy of Sciences, 32: 11−19(in Chinese with English abstract).
[18] Liu Y, Wei J L, Yue H, et al. 2020. Analysis on temporal and spatial characteristics and driving factors of soil erosion in Shendong mining area[J]. Science of Surveying and Mapping, 47(1): 142−153(in Chinese with English abstract).
[19] Nachtergaele F O, Velthuizen, Verelst L, et al. 2012. Harmonized World Soil Database (version 1.2)[DS]. International Soil Reference and Information Centre.
[20] Peng S, Ding Y, Liu W, et al. 2019. 1 km monthly temperature and precipitation dataset for China from 1901 to 2017[J]. Earth System Science Data, 11(4): 1931−1946. doi: 10.5194/essd-11-1931-2019
[21] Qin J X, Wang Z L. 2011. Research on predicting soil erosion in Conghua City based on GIS and RUSLE[J]. Pearl River, 32(2): 37−41(in Chinese with English abstract).
[22] Tao H B, Wang W F. 2018. Analysis of nitrogen and phosphorus losses in soil erosion process based on GIS——Taking Dingxi City Anding District as an example[J]. Journal of Green Science and Technology, (24): 15−17(in Chinese with English abstract).
[23] Wang B W, Yang Q K, Liu Z H, et al. 2007. Extraction of topographic factor values of the modified universal soil loss equation based on DEM and GIS[J]. Science of Soil and Water Conservation in China, 5(2): 18−23(in Chinese with English abstract).
[24] Wang D H, Fang Y H, Li J L, et al. 2022. Analysis of precipitation characteristics and precipitation prediction in Yulin area[J]. Yellow River, 44(5): 30−34(in Chinese with English abstract).
[25] Wang W Z, Jiao J Y. 1996. Qutantitative evaluation on factors influencing soil erosion in China[J]. Bulletin of Soil and Water Conservation, (5): 1−20(in Chinese with English abstract).
[26] Wang Z Y, Chen X Y, Ma C S, et al. 2021. Changes in soil erosion and ecological service value before and after the conversion of farmland to forest in Yulin City, Northern Shaanxi[J]. Journal of Northwest Forestry University, 36(3): 59−67(in Chinese with English abstract).
[27] Wei J M, Li C B, Wu L, et al. 2021. Study on soil erosion in Northwestern Sichuan and Southern Gansu (NSSG) based on USLE[J]. Journal of Soil and Water Conservation, 35(2): 31−37,46(in Chinese with English abstract).
[28] Williams J R, Renard K G, Dyke P T. 1983. EPIC: A new method for assessing erosion's effect on soil productivity[J]. Journal of Soil & Water Conservation, 38(5): 381−383.
[29] Wischmeier W H. 1971. A soil erodibility nomograph for farmland and construction sites[J]. Journal of Soil and Water Conservation, 26: 189−193.
[30] Xu Y H, Li J Y, Ren C, et al. 2020. Dynamic evolution and prediction of soil erosion in Yulin City, Shaanxi Province[J]. Journal of Anhui Agricultural Sciences, 48(13): 63−69,77(in Chinese with English abstract).
[31] Yang R, Li Y C. 2013. The study on the standards of ecoligical compensation for coal resources development in the north of Shaanxi—Taking Yulin as an example[J]. Journal of Xi'an Shiyou University (Social Science Edition), 22(2): 1−6(in Chinese with English abstract).
[32] Yang Y K, Xiao P F, Feng X Z, et al. 2017. Accuracy assessment of seven global land cover datasets over China[J]. ISPRS Journal of Photogrammetry and Rmote Sensing, 125: 156−173. doi: 10.1016/j.isprsjprs.2017.01.016
[33] Zhang E W, Peng S Y, Feng H M. 2020. Sensitivity assessment of soil erosion and its spatial pattern evolution in Dianchi Lake Basin based on GIS and RUSLE[J]. Journal of Soil and Water Conservation, 34(2): 115−122 (in Chinese with English abstract).
[34] Zhang K L, Cai Y M, Liu B Y, et al. 2001. Study on soil erodibility and its application in the Loess Plateau area[J]. Acta Ecologica Sinica, 21(10): 1687−1695(in Chinese with English abstract).
[35] Zhang Z, Ren Z Y. 2011. Temporal and spatial differences and its trends in vegetation cover change over the Loess Plateau[J]. Resources Science, Resourves Science, 33(11): 2143–2149(in Chinese with English abstract).
[36] Zhou L H, Wang P T, Cao R C. 2022. Analysis of driving factors of soil erosion and evaluation of ecological security in Yan'an City from 2000 to 2022[J]. Journal of Ecology and Rural Environment, 38(4): 512−520(in Chinese with English abstract).
[37] Zhu Q M, Wang N, Liu J E, et al. 2023. Changes in soil water erosion and driving factors in the ecologically fragile area of northern Shaanxi − A case study of Yulin City[J]. Research of Soil and Water Conservation, 30(5): 41−51,60(in Chinese with English abstract).
[38] Zou Y D, He L, Zhang X P, et al. 2021. Characteristics of land use structure change in Beiluo River Basin during 1970–2019 based on Google Erath engine[J]. Journal of Soil and Water Conservation, 41(6): 209−219(in Chinese with English abstract).
[39] 蔡崇法, 丁树文, 史志华, 等. 2000. 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, (2): 19−24. doi: 10.3321/j.issn:1009-2242.2000.02.005
[40] 曹巍, 刘璐璐, 吴丹. 2018. 三江源区土壤侵蚀变化及驱动因素分析[J]. 草业学报, 27(6): 10−22. doi: 10.11686/cyxb2017359
[41] 陈峰, 李红波. 2021. 基于GIS和RUSLE的滇南山区土壤侵蚀时空演变-以云南省元阳县为例[J]. 应用生态学报, 32(2): 629−637.
[42] 陈浩. 2019. 黄土高原退耕还林前后流域土壤侵蚀时空变化及驱动因素研究[D]. 西北农林科技大学博士学位论文.
[43] 符素华, 刘宝元, 周贵云, 等. 2015. 坡长坡度因子计算工具[J]. 中国水土保持科学, 13(5): 105−110. doi: 10.3969/j.issn.1672-3007.2015.05.016
[44] 郭思琪, 韩磊, 赵永华, 等. 2019. 秦岭地区土壤侵蚀时空变化及景观格局[J]. 生态学杂志, 38(7): 2167.
[45] 胡振琪, 李勇, 陈洋. 2022. 黄河泥沙在生态修复中的作用机理与关键技术[J]. 中国矿业大学学报, 51(1): 1−15. doi: 10.3969/j.issn.1000-1964.2022.1.zgkydxxb202201001
[46] 李柏延, 任志远, 易浪. 2015. 2001—2010年榆林市土壤侵蚀动态变化趋势[J]. 干旱区研究, 32(5): 918−925.
[47] 李天宏, 郑丽娜. 2012. 基于RUSLE模型的延河流域2001—2010年土壤侵蚀动态变化[J]. 自然资源学报, 27(7): 1164−1175. doi: 10.11849/zrzyxb.2012.07.008
[48] 李智广, 符素华, 刘宝元. 2012. 我国水力侵蚀抽样调查方法[J]. 中国水土保持科学, 10(1): 77−81. doi: 10.3969/j.issn.1672-3007.2012.01.013
[49] 刘国彬, 上官周平, 姚文艺, 等. 2017. 黄土高原生态工程的生态成效[J]. 中国科学院院刊, 32: 11−19.
[50] 刘英, 魏嘉莉, 岳辉, 等. 2022. 神东矿区土壤侵蚀时空特征及驱动力分析[J]. 测绘科学, 47(1): 142−153.
[51] 覃杰香, 王兆礼. 2011. 基于GIS和RUSLE的从化市土壤侵蚀量预测研究[J]. 人民珠江, 32(2): 37−41. doi: 10.3969/j.issn.1001-9235.2011.02.012
[52] 陶鸿斌, 汪文飞. 2018. 基于GIS分析土壤侵蚀过程中氮磷流失分布-以定西市安定区为例[J]. 绿色科技, (24): 15−17,19.
[53] 汪邦稳, 杨勤科, 刘志红, 等. 2007. 基于DEM和GlS的修正通用土壤流失方程地形因子值的提取[J]. 中国水土保持科学, 5(2): 18−23. doi: 10.3969/j.issn.1672-3007.2007.02.004
[54] 王大浩, 方亚宏, 李金龙, 等. 2022. 榆林地区降水特征分析及降水量预测[J]. 人民黄河, 44(5): 30−34. doi: 10.3969/j.issn.1000-1379.2022.05.007
[55] 王万忠, 焦菊英. 1996. 中国的土壤侵蚀因子定量评价研究[J]. 水土保持通报, (5): 1−20.
[56] 王泽宇, 陈旭阳, 马彩诗, 等. 2021. 陕北榆林市退耕还林前后土壤侵蚀及生态服务价值变化[J]. 西北林学院学报, 36(3): 59−67. doi: 10.3969/j.issn.1001-7461.2021.03.09
[57] 魏健美, 李常斌, 武磊, 等. 2021. 基于USLE的甘南川西北土壤侵蚀研究[J]. 水土保持学报, 35(2): 31−37,46.
[58] 徐云环, 李景宜, 任冲, 等. 2020. 陕西省榆林市土壤侵蚀动态演变及预测[J]. 安徽农业科学, 48(13): 63−69,77. doi: 10.3969/j.issn.0517-6611.2020.13.019
[59] 杨嵘, 李颖超. 2013. 陕北煤炭资源开发生态补偿标准研究——以榆林市为例[J]. 西安石油大学学报(社会科学版), 22(2): 1−6.
[60] 张翀, 任志远. 2011. 黄土高原地区植被覆盖变化的时空差异及未来趋势[J]. 资源科学, 33(11): 2143−2149.
[61] 张恩伟, 彭双云, 冯华梅. 2020. 基于GIS和RUSLE的滇池流域土壤侵蚀敏感性评价及其空间格局演变[J]. 水土保持学报, 34(2): 115−122.
[62] 周璐红, 王盼婷, 曹瑞超. 2022. 2000—2020年延安市土壤侵蚀驱动因素分析及生态安全评价[J]. 生态与农村环境学报, 38(4): 512−520.
[63] 邹亚东, 何亮, 张晓萍, 等. 2021. 基于GEE数据平台的北洛河流域1970—2019年土地利用结构变化特征[J]. 水土保持通报, 41(6): 209−219. doi: 10.3969/j.issn.1000-288X.2021.6.stbctb202106028
[64] 张科利, 蔡永明, 刘宝元, 等. 2001. 黄土高原地区土壤可蚀性及其应用研究[J]. 生态学报, 21(10): 1687−1695. doi: 10.3321/j.issn:1000-0933.2001.10.018
[65] 中华人民共和国水利部. 2007. 土壤侵蚀分类分级标准SL190—2007[S]. 中华人民共和国水利部.
[66] 朱启明, 王宁, 刘俊娥, 等. 2023. 陕北生态脆弱区土壤水蚀变化及驱动因子——以榆林市为例[J]. 水土保持研究, 30(5): 41−51,60.
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