干旱区水电站建设运营生态环境影响遥感监测

doi:10.13866/j.azr.2023.09.13

摘要/Abstract

摘要：

水力发电是我国重要的清洁能源，然而水电站建设和运营周期长，其对生态系统的长期影响过程还不明确。尤其是干旱地区，因其特殊的地理位置与干旱少雨的气候条件，生态系统自我调节能力差，当地生态环境遭到破坏后往往难以修复。本文以我国干旱区典型水电站——龙羊峡水电站为例，利用Landsat系列卫星数据及陆地遥感产品，应用缓冲区分析、趋势性分析等方法，监测2000—2021年水电站周边生态环境并分析其对周边区域生态环境的影响。结果表明：（1） 2000—2021年龙羊峡水电站周边土地利用的格局并未发生明显改变，草地面积相对占比轻微上升，其他类型土地利用占比轻微下降。（2） 2000—2021年，龙羊峡水电站周边湿地面积显著增加。（3）龙羊峡水电站周边区域近20 a植被生长状况良好，植被覆盖度高值区域面积占比增大。（4）水电站周边区域植被固碳能力提升，随着湿地面积增速放缓，植被生产力逐渐恢复。

关键词: 水电站, 生态环境影响, 植被覆盖度, 土地利用类型, 遥感监测

Abstract:

Hydropower is an important clean energy source in China. However, the construction and operation cycles of hydropower stations are long, and their long-term impact on the ecosystem is unclear. In arid areas, with their unique geographical location and dry climate, ecosystems often have limited self-regulation abilities, making restoring the local ecological environment after damage challenging. This study focuses on Longyangxia Hydropower Station, a representative hydropower station in an arid region of China, and uses Landsat series satellite data and land remote sensing products to monitor the ecological environment surrounding the hydropower station from 2000 to 2021. The study employs buffer zone and trend analyses to assess the impact on the ecological environment arounding the Hydropower. The results indicate the following: (1) The land use pattern around Longyangxia Hydropower Station did not change significantly from 2000 to 2021. However, the proportion of grasslands increased slightly, while that of other land use types decreased slightly. (2) During the same period, the wetland area around Longyangxia Hydropower Station increased significantly. (3) The vegetation in the surrounding area of Longyangxia Hydropower Station showed good growth over the past two decades, with an increase in the proportion of areas with high vegetation coverage. (4) The carbon sequestration capacity of vegetation in the vicinity of the hydropower station improved, and vegetation productivity gradually recovered as the growth rate of the wetland area decreased.

Key words: hydropower stations, ecological environment impact, vegetation coverage, land use types, remote sensing, monitoring

马瑶瑶, 史培军, 徐伟, 张钢锋. 干旱区水电站建设运营生态环境影响遥感监测[J]. 干旱区研究, 2023, 40(9): 1498-1508.

MA Yaoyao, SHI Peijun, XU Wei, ZHANG Gangfeng. Remote sensing monitoring of the ecological environment of hydropower station construction and operation in arid areas： A case study of Longyangxia Hydropower Station[J]. Arid Zone Research, 2023, 40(9): 1498-1508.

图/表 12

图1

图2

图3

表1

图4

图5

图6

图7

图8

图9

表2

表3

参考文献 33

[1]	曹霞. 碳达峰碳中和背景下我国新能源产业发展与升级[J]. 中国市场, 2022, 29(34): 60-62.
	[Cao Xia. The development and upgrading of China’s new energy industry under the background of carbon peak carbon neutrality[J]. China Market, 2022, 29(34): 60-62.]
[2]	Lu Y C, Dai J Q, Wang L N, et al. The impact of the energy transition on China’s economy under the carbon peaking and carbon neutrality goals[J]. Thermal Science, 2022, 26(5): 4043-4056. doi: 10.2298/TSCI2205043L
[3]	龚围, 李丽, 柳钦火, 等. “一带一路”区域水电站工程生态环境影响遥感监测[J]. 地球信息科学学报, 2020, 22(7): 1424-1436. doi: 10.12082/dqxxkx.2020.200008
	[Gong Wei, Li Li, Liu Qinhuo, et al. Remote sensing monitoring of ecological environment impact of hydropower station project in ‘Belt and Road’ region[J]. Journal of Geo-information Science, 2020, 22(7): 1424-1436.] doi: 10.12082/dqxxkx.2020.200008
[4]	Wang W Q, Wang H M, Liu G, et al. Analysis of the trade-off between hydroelectricity generation and ecological protection from the perspective of eco-efficiency in Southwest China[J]. Journal of Environmental Management, 2022, 315: 115063. doi: 10.1016/j.jenvman.2022.115063
[5]	Costea G, Pusch M T, Banaduc D, et al. A review of hydropower plants in Romania: Distribution, current knowledge, and their effects on fish in headwater streams[J]. Renewable & Sustainable Energy Reviews, 2021, 145: 111003.
[6]	Kuriqi A, Pinheiro A N, Sordo-Ward A, et al. Ecological impacts of run-of-river hydropower plants—Current status and future prospects on the brink of energy transition[J]. Renewable & Sustainable Energy Reviews, 2021, 142: 110833.
[7]	Gan S, Yuan X, He D. Study on aplication of remote sensing monitoring vegetation cover around the manwan Hydropower Station[J]. Journal of Soil and Water Conservation, 2002, 16(3): 60-63.
[8]	Lin Z H, Qi J G. A new remote sensing approach to enrich Hydropower Dams’ information and assess their impact distances: A case study in the Mekong River Basin[J]. Remote Sensing, 2019, 11(24): rs11243016.
[9]	Mohamed M M, Elmahdy S I. Remote sensing of the Grand Ethiopian Renaissance Dam: A hazard and environmental impacts assessment[J]. Geomat Nat Hazards Risk, 2017, 8(2): 1225-1240. doi: 10.1080/19475705.2017.1309463
[10]	Pang Z G, Ge D X, Fu J E. Eco-environment evolvement analysis of Ertan reservoir catchment based on remote sensing[J]. Science China Technological Sciences, 2011, 54: 95-100.
[11]	Wan H, Xie Y, Li B, et al. An integrated method to identify and evaluate the impact of hydropower development on terrestrial ecosystem. Environmental impact assessment review[J]. Environmental Impact Assessment Review, 2023, 99: 107042. doi: 10.1016/j.eiar.2023.107042
[12]	唐克旺, 王研, 王芳, 等. 西北地区生态环境现状和演化规律研究[J]. 干旱区地理, 2002, 25(2): 132-138.
	[Tang Kewang, Wang Yan, Wang Fang, et al. Analysis on the present situation and evolution of the ecological environment in Northwest China[J]. Arid Land Geography, 2002, 25(2): 132-138.]
[13]	韩辉邦, 马明国, 马守存, 等. 近30 a青海省植被变化及其气候驱动因子分析[J]. 干旱区研究, 2017, 34(5): 1164-1174.
	[Han Huibang, Ma Mingguo, Ma Shoucun, et al. Analysis of vegetation change and its climate driving factors in Qinghai Province in recent 30 years[J]. Arid Zone Research, 2017, 34(5): 1164-1174.]
[14]	张永荥, 张生鹏, 贡宝扎西, 等. 基于BDS及InSAR的龙羊峡水电站库区地表形变研究[J]. 全球定位系统, 2021, 46(6): 25-29, 43.
	[Zhang Yongxing, Zhang Shengpeng, Gongbao Zhaxi, et al. Study on surface deformation of Longyangxia hydropower station reservoir area based on BDS and InSAR[J]. GNSS World of China, 2021, 46(6): 25-29, 43.]
[15]	徐新良, 刘纪远, 张树文, 等. 中国多时期土地利用遥感监测数据集(CNLUCC)[DB/OL]. 资源环境科学数据注册与出版系统, 2018. doi: 10.12078/2018070201.
	[Xu Xinliang, Liu Jiyuan, Zhang Shuwen, et al. Remote sensing data set of multi-period land use monitoring in China (CNLUCC)[DB/OL]. Resource and Environmental Science Data Registration and Publication System, 2018. doi: 10.12078/2018070201.]
[16]	McFeeters S K. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features[J]. International Journal of Remote Sensing, 2007, 17(7): 1425-1432. doi: 10.1080/01431169608948714
[17]	Chen Q, Liu G. Research on irregular buffer generation algorithm with constraint conditions[J]. Geological Science and Techology Information, 2014, 33(4): 213-218.
[18]	段晋芳, 郭青霞, 解鸿志. 基于GIS的山西永定河植被生态需水管理系统的研建[J]. 水土保持研究, 2011, 18(1): 254-258.
	[Duan Jinfang, Guo Qingxia, Xie Hongzhi. Research and construction of vegetation ecological water requirement management system of Shanxi Yongding River based on GIS[J]. Research of Soil and Water Conservation, 2011, 18(1): 254-258.]
[19]	Qiao W, Sheng Y, Fang B, et al. Land use change information mining in highly urbanized area based on transfer matrix: A case study of Suzhou, Jiangsu Province[J]. Geographical Research, 2013, 32(8): 1497-1507.
[20]	李春娥, 马静, 何芷. 伊犁河谷天然植被覆盖度的变化特征分析[J]. 地理空间信息, 2022, 20(2): 84-88.
	[Li Chun’e, Ma Jing, He Zhi. Analysis of variation characteristics of natural vegetation coverage in Yili River Valley[J]. Geospatial Information, 2022, 20(2): 84-88.]
[21]	方精云, 柯金虎, 唐志尧, 等. 生物生产力的“4P”概念、估算及其相互关系[J]. 植物生态学报, 2001, 47(4): 414-419.
	[Fang Jingyun, Ke Jinhu, Tang Zhiyao, et al. The concept, estimation and relationship of ‘4P’ of biological productivity[J]. Chinese Journal of Plant Ecology, 2001, 47(4): 414-419.]
[22]	徐勇, 黄雯婷, 郑志威, 等. 基于空间尺度效应的西南地区植被NPP影响因子探测[J]. 环境科学, 2023, 44(2): 900-911.
	[Xu Yong, Huang Wenting, Zheng Zhiwei, et al. Detection of vegetation NPP influencing factors in Southwest China based on spatial scale effect[J]. Environmental Science, 2023, 44(2): 900-911.]
[23]	曹云, 张称意, 孙应龙, 等. 2000—2020年华北地区植被固碳能力的时空变化特征及其气象影响分析[J]. 生态学报, 2023, 43(9): 3488-3499.
	[Cao Yun, Zhang Chengyi, Sun Yinglong, et al. Spatio-temporal variation characteristics of vegetation carbon sequestration capacity and its meteorological influence in North China from 2000 to 2020 were analyzed[J]. Acta Ecologica Sinica, 2023, 43(9): 3488-3499.]
[24]	戴声佩, 张勃, 王海军, 等. 中国西北地区植被覆盖变化驱动因子分析[J]. 干旱区地理, 2010, 33(4): 636-643.
	[ Dai Shengpei, Zhang Bo, Wang Haijun, et al. Driving factors analysis of vegetation cover change in Northwest China[J]. Arid Land Geography, 2010, 33(4): 636-643.]
[25]	代子俊, 赵霞, 李冠稳, 等. 基于GIMMS NDVI 3 g.v1的近34年青海省植被生长季NDVI时空变化特征[J]. 草业科学, 2018, 35(4):713-725.
	[ Dai Zijun, Zhao Xia, Li Guanwen, et al. Based on GIMMS NDVI 3g. v1, the spatial and temporal variation characteristics of NDVI in vegetation growing season in Qinghai Province in recent 34 years were analyzed.[J]. Pratacultural Science, 2018, 35(4): 713-725.]
[26]	李璠, 徐维新. 2000—2015年青海省不同功能区NDVI时空变化分析[J]. 草地学报, 2017, 25(4): 701-710. doi: 10.11733/j.issn.1007-0435.2017.04.003
	[Li Fan,Xu Weixin. Analysis of spatial and temporal variation of NDVI in different functional areas of Qinghai Province from 2000 to 2015[J]. Acta Agrestia Sinica, 2017, 25(4): 701-710.] doi: 10.11733/j.issn.1007-0435.2017.04.003
[27]	尹振良, 冯起, 王凌阁, 等. 2000—2019年中国西北地区植被覆盖变化及其影响因子[J]. 中国沙漠, 2022, 42(4): 11-21. doi: 10.7522/j.issn.1000-694X.2021.00200
	[Yin Zhenliang, Feng Qi, Wang Lingge, et al. Vegetation cover change and its influencing factors in Northwest China from 2000 to 2019[J]. Journal of Desert Research, 2022, 42(4): 11-21.] doi: 10.7522/j.issn.1000-694X.2021.00200
[28]	隋欣, 杨志峰. 青藏高原东部龙羊峡水库气候效应的变化趋势分析[J]. 山地学报, 2005, 23(3): 280-287.
	[Sui Xin,Yang Zhifeng. Trend analysis of climate effect of Longyangxia Reservoir in eastern Qinghai-Tibet Plateau[J]. Mountain Research, 2005, 23(3): 280-287.]
[29]	牟乐, 芦奕晓, 杨惠敏, 等. 1981—2015年中国西北牧区植被覆盖的时空变化[J]. 干旱区研究, 2018, 35(3): 615-623.
	[Mou Le, Lu Yixiao, Yang Huimin, et al. Spatio-temporal changes of vegetation coverage in pastoral areas of Northwest China from 1981 to 2015[J]. Arid Zone Research, 2018, 35(3): 615-623.]
[30]	马昊翔, 陈长成, 宋英强, 等. 青海省近10年草地植被覆盖动态变化及其驱动因素分析[J]. 水土保持研究, 2018, 25(6): 137-145.
	[Ma Haoxiang, Chen Changcheng, Song Yingqiang, et al. Analysis of dynamic changes and driving factors of grassland vegetation coverage in Qinghai Province in recent 10 years[J]. Research of Soil and Water Conservation, 2018, 25(6): 137-145.]
[31]	左文波, 黎杰俊, 欧阳园兰, 等. 江西官山国家级自然保护区水电站的生态影响及其修复治理[J]. 江西科学, 2019, 37(6): 943-947.
	[Zuo Wenbo, Li Jiejun, OuYang Yuanlan, et al. Ecological impact and restoration of hydropower station in Guanshan National Nature Reserve of Jiangxi Province[J]. Jiangxi Science, 2019, 37(6): 943-947.]
[32]	Mueller M, Knott J, Pander J, et al. Experimental comparison of fish mortality and injuries at innovative and conventional small hydropower plants[J]. Journal of Applied Ecology, 2022, 59(9): 2360-2372. doi: 10.1111/jpe.v59.9
[33]	Lange K, Meier P, Trautwein C, et al. Basin-scale effects of small hydropower on biodiversity dynamics[J]. Frontiers in Ecology and the Environment, 2018, 16(7): 397-404. doi: 10.1002/fee.2018.16.issue-7

年份	不同等级植被覆盖度占比/%
年份	0%~10%	10%~20%	20%~40%	40%~60%	60%~80%	80%~100%
2000	2.18	18.11	49.85	20.45	6.11	3.37
2005	1.76	14.99	53.19	18.37	6.2	5.6
2010	1.28	3.91	45.02	29.45	12.1	8.35
2015	0.92	0.2	31.35	43.35	17.14	7.11
2020	0.14	0.03	0.56	37.43	40.41	21.46

土地利用类型	面积占比/%
土地利用类型	2000年	2005年	2010年	2015年	2020年
耕地	3.34	3.48	3.66	3.56	1.97
林地	0.22	0.11	0.09	0.09	0.17
草地	42.73	41.46	46.3	45.07	45.55
水域	33.69	35.17	28.99	31.48	32.36
未利用土地	20.02	19.78	20.96	19.8	19.95

2000年	2020年
2000年	草地	耕地	林地	水域	未利用土地	2000年转出
草地	303.15	8.2	0.86	35.34	47.47	91.87
耕地	6.12	8.46	0	9.93	6.49	22.54
林地	1	0	0.98	0.02	0	1.02
水域	11.61	0.04	0	294.03	7.16	18.81
未利用土地	39.1	1.83	0.15	27.65	107.98	68.73
2020转入	57.83	10.06	1.02	72.94	61.13