神东矿区煤炭开采对植被净初级生产力的影响  

Effect of coal mining on net primary productivity of vegetation in Shendong Mining Area

作　　者：牛鸿波 田少国 祖鹏举 曹满红 曲少东 董起广 李冰倩 姜泽玉 毕银丽 岳辉[4,5] NIU Hongbo;TIAN Shaoguo;ZU Pengju;CAO Manhong;QU Shaodong;DONG Qiguang;LI Bingqian;JIANG Zeyu;BI Yinli;YUE Hui(Shannxi Coalbed Methane Develpoment Co.,Ltd,Xi’an 710119,China;Shaanxi Ecological Industry Co.,Ltd,Xi’an 710061,China;College of Geology and Environment,Xi’an University of Science and Technology,Xi’an 710054,China;College of Geomatics,Xi’an University of Science and Technology,Xi’an 710054,China;Institute of Ecological Environment Restoration in Mine Areas of West China,Xi’an University of Science and Technology,Xi’an 710054,China)

机构地区：[1]陕西省煤层气开发利用有限公司,陕西西安710119 [2]陕西生态产业有限公司,陕西西安710061 [3]西安科技大学地质与环境学院,陕西西安710054 [4]西安科技大学测绘科学与技术学院,陕西西安710054 [5]西安科技大学西部矿山生态环境修复研究院,陕西西安710054

出　　处：《煤炭科学技术》2024年第7期267-277,共11页Coal Science and Technology

基　　金：陕西煤业化工集团科研资助项目(2022SMHKJ-B-J-54)。

摘　　要：神东矿区煤炭开采对当地生态环境,特别是植被生长,产生了重要影响。为了定量描述这种影响,该研究利用区域蒸散模型,计算神东矿区潜在净初级生产力(Potential Net Primary Productivity,P_(NP),p),并利用MODIS17A3数据集(2001—2022年)表征实际净初级生产力(Actual Net Primary Productivity,P_(NP,a)),同时结合中国陆地生态系统逐月净初级生产力栅格数据集(P_(NP,al),1988—2015年),采用地理加权回归(Geographically weighted regression,GWR)模型构建校正方法,对P_(NP,al)进行校正获取1988—2000年的P_(NP,a)数据,以二者之差(Human Net Primary Productivity)P_(NP,h)表征煤炭开采的影响,评估了神东矿区煤炭开采对植被P_(NP)的影响。结果表明:①利用GWR模型校正的P_(NP,al)数据精度约为0.76,校正后的P_(NP,al)数据与MODIS17A3数据集具有较强的空间相关性,说明了校正模型精度的可靠性;②神东矿区的整体上P_(NP,a)和P_(NP,h)表现为先下降后逐渐恢复的趋势,但植被净初级生产力(Net Primary Productivity,P_(NP))并未恢复至采矿前水平。采矿前P_(NP,h)均值和采矿后P_(NP,h)均值分别为21.50 g/m^(2)、-60.20 g/m^(2),P_(NP,h)<0表明矿区P_(NP)植被生长受到采矿活动的干扰,发生退化的矿井主要分布在高强度开采区域(以C计,下同);③1996—2022年神东矿区P_(NP)值的变化主要受气候变化和人类活动的共同影响,人类活动和气候变化对生态退化的占比分别为35.7%、8.2%,1996—2015年人类活动贡献率指数(Relative Contribution Index,I_(RC))主要集中在0.5左右,表明煤炭开采对植被退化占主导作用,2016年后光伏电站建设对P_(NP)的影响表现出促进作用。该研究有助于理解煤炭开采对植被净初级生产力动态变化的影响,并为神东矿区的植被恢复和高质量发展提供科学依据。Coal mining in Shendong Mining area has an important impact on the local ecological environment,especially the growth of vegetation.In order to describe this effect quantitatively,this study uses a regional evapotranspiration model to calculate the Potential Net Primary Productivity(P_(NP),p)of the Shendong mining area.MODIS17A3 dataset(2001-2022)was used to characterize the Actual Net Primary Productivity(P_(NP,a)),and combined with the monthly net primary productivity raster dataset of terrestrial ecosystems in China(P_(NP,al),1988-2015),using GWR model construction correction method to correct P_(NP,al)to obtain 1988-2000 P_(NP,a)data,and using the dif-ference between the two P_(NP,h)to characterize the impact of coal mining.The effect of coal mining on vegetation P_(NP)in Shendong mining area was evaluated.The results show that:①the accuracy of P_(NP,al)data corrected by GWR model is about 0.76,and the corrected P_(NP,al)data has a strong spatial correlation with the MODIS17A3 dataset,which indicates the reliability of the accuracy of the corrected model;②The overall P_(NP,a)and P_(NP,h)of Shendong mining area showed a trend of decreasing first and then recovering gradually,but the P_(NP)of vegetation did not recover to the pre-mining level.The mean values of P_(NP,h)before mining and P_(NP,h)after mining are 21.50 g/m^(2)and-60.20 g/m^(2),re-spectively.P_(NP,h)<0 indicates that P_(NP)vegetation growth in mining areas is disturbed by mining activities,and the degraded mines are mainly distributed in high-intensity mining areas(calculated in C,the same below).③The change of P_(NP)value in Shendong mining area from 1996 to 2022 is mainly influenced by climate change and human activities.The proportion of human activities and climate change to ecological degradation is 35.7%and 8.2%,respectively.The I_(RC)from 1996 to 2015 is mainly about 0.5,indicating that coal mining plays a leading role in vegetation degradation.After 2016,the impact of photovoltaic power plant construction on P_(NP)showed a promoting

关 键 词：矿区生态环境 净初级生产力 煤炭开采 光伏环境效应 贡献率指数 地理加权回归模型 

分 类 号：X171[环境科学与工程—环境科学]