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喀斯特槽谷区土壤侵蚀时空演变及未来情景模拟
引用本文:操玥,王世杰,白晓永,李汇文,陈飞,王明明,吴路华,许燕,李琴,田诗琪,杨钰杰,李朝君,胡泽银,邓元红,路茜,习慧鹏,陈欢,王金凤,冉晨,罗旭玲.喀斯特槽谷区土壤侵蚀时空演变及未来情景模拟[J].生态学报,2019,39(16):6061-6071.
作者姓名:操玥  王世杰  白晓永  李汇文  陈飞  王明明  吴路华  许燕  李琴  田诗琪  杨钰杰  李朝君  胡泽银  邓元红  路茜  习慧鹏  陈欢  王金凤  冉晨  罗旭玲
作者单位:中国科学院地球化学研究所环境地球化学国家重点实验室;中国科学院大学;中国科学院普定喀斯特生态系统观测研究站;中国科学院第四纪科学与全球变化卓越创新中心;贵州师范学院贵州省流域地理国情监测重点实验室
基金项目:国家重点研发计划(2016YFC0502300,2016YFC0502102);“西部之光”人才培养计划(A类)([2018]X);贵州省科技计划(2017-2966)
摘    要:以中国南方喀斯特槽谷区为研究对象,基于改进的喀斯特地区土壤侵蚀算法,定量分析了槽谷区土壤侵蚀时空演变特征,并利用CA-Markov模型对土壤侵蚀状况的未来情景进行预测。结果表明:(1)喀斯特槽谷区2000—2015年土壤侵蚀总量由61.86×10~7 t/a减少至2.97×10~7 t/a,区域年平均侵蚀模数由21.61 t hm~(-2) a~(-1)降低至1.04 t hm~(-2) a~(-1),轻度及轻度以下侵蚀等级的面积增加了76.13×10~5 hm~2,重度及重度以上侵蚀面积减少了46.90×10~5 hm~2,侵蚀状况明显减轻;(2)不同地貌类型之间的土壤侵蚀状况存在一定差异,平原地区侵蚀模数最小,盆地地区侵蚀模数最大,达到平原地区侵蚀模数的近4倍;(3) 2000—2015年间,槽谷区轻度及轻度以上侵蚀等级都逐渐向微度侵蚀等级转移,土壤侵蚀等级由高等级向低等级转移率达到了98%以上,总体呈现出好转的趋势;(4)基于CA-Markov模型模拟槽谷区2020年土壤侵蚀等级的未来演变趋势,其总体Kappa系数达到了0.9788,一致性最佳;(5)到2020年,槽谷区土壤侵蚀等级基本为微度和轻度侵蚀,土壤侵蚀状况将进一步改善。本研究的结果可为喀斯特槽谷区当前土壤侵蚀治理成效的评价以及未来的防治提供理论和数据方面的参考。

关 键 词:土壤侵蚀  喀斯特  时空格局  CA-Markov模型  槽谷
收稿时间:2019/3/30 0:00:00
修稿时间:2019/6/3 0:00:00

Spatial-temporal evolution processes and simulation of future soil erosion scenario in the karst valley of Southern China
CAO Yue,WANG Shijie,BAI Xiaoyong,LI Huiwen,CHEN Fei,WANG Mingming,WU Luhu,XU Yan,LI Qin,TIAN Shiqi,YANG Yujie,LI Chaojun,HU Zeyin,DENG Yuanhong,LU Qian,XI Huipeng,CHEN Huan,WANG Jinfeng,RAN Chen and LUO Xuling.Spatial-temporal evolution processes and simulation of future soil erosion scenario in the karst valley of Southern China[J].Acta Ecologica Sinica,2019,39(16):6061-6071.
Authors:CAO Yue  WANG Shijie  BAI Xiaoyong  LI Huiwen  CHEN Fei  WANG Mingming  WU Luhu  XU Yan  LI Qin  TIAN Shiqi  YANG Yujie  LI Chaojun  HU Zeyin  DENG Yuanhong  LU Qian  XI Huipeng  CHEN Huan  WANG Jinfeng  RAN Chen and LUO Xuling
Institution:State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China;University of Chinese Academy of Sciences, Beijing 100049, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China;Puding Karst Ecosystem Observation and Research Station, Chinese Academy of Sciences, Anshun 562100, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China;Chinese Academy of Sciences Center for Excellence in Quaternary Science and Global Change, Xi''an 710061, China;Guizhou Provincial Key Laboratory of Geographic State Monitoring of Watershed, Guizhou Education University, Guiyang 550018, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China;University of Chinese Academy of Sciences, Beijing 100049, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China;University of Chinese Academy of Sciences, Beijing 100049, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China;University of Chinese Academy of Sciences, Beijing 100049, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China;University of Chinese Academy of Sciences, Beijing 100049, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China;University of Chinese Academy of Sciences, Beijing 100049, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China;University of Chinese Academy of Sciences, Beijing 100049, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China;University of Chinese Academy of Sciences, Beijing 100049, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China;University of Chinese Academy of Sciences, Beijing 100049, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China,State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China and State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China
Abstract:Based on an improved soil erosion algorithm for the karst area of Southern China, we quantitatively analyzed the spatial-temporal evolution processes of soil erosion, and used the CA-Markov model to predict the future situation of soil erosion in the karst valley in Southern China. Our major findings are as follows:(1) The total amount of soil erosion in the karst valley decreased from 61.86×107 t/a to 2.97×107 t/a from 2000 to 2015, and the annual average erosion modulus of the area reduced from 21.61 t hm-2 a-1 to 1.04 t hm-2 a-1. The area of erosion corresponding to the grades mild and below mild increased by 76.13×105 hm2, while that corresponding to the grades strong and above strong decreased by 46.90×105 hm2, indicating that the erosion situation reduced significantly. (2) There are some differences in soil erosion between different geomorphological types. The erosion modulus in the plain area was the smallest, while that in the basin area was the largest, nearly four times the erosion modulus in the plains. (3) From 2000 to 2015, the mild and above mild erosion levels in the karst valley gradually shifted to the level of micro-erosion, and the rate of shift in soil erosion grade from the high to low grade reached more than 98%, showing a general trend of improvement. (4) We simulated the future trend of the soil erosion grade evolution in the trough valley in 2020 based on the CA-Markov model. The overall Kappa coefficient reached 0.9788, and the consistency was the best. (5) By 2020, the soil erosion level in the trough area would be micro-degree i.e., mild erosion and the soil erosion condition would be further improved. The results of this study could provide theoretical and data references for the evaluation of current soil erosion control strategies and future prevention and control measures in the karst valley.
Keywords:soil erosion  karst  spatial-temporal pattern  CA-Markov model  valley
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