金沙江中游水电站对植被时空变化的影响

张家铮; 朱大明; 王德智; 戴祚敏

doi:10.13870/j.cnki.stbcxb.2025.01.015

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金沙江中游水电站对植被时空变化的影响

更新时间：2025-03-14

- 金沙江中游水电站对植被时空变化的影响
- Effects of Hydropower Station on the Temporal and Spatial Changes of Vegetation in the Middle Reaches of the Jinsha River
- 水土保持学报 2025年39卷第1期页码：326-337
- 作者机构：
  
  1. 昆明理工大学国土资源工程学院,昆明,650093
  2. 中国科学院武汉植物园, 中国科学院水生植物与流域生态重点实验室,武汉,430074
  3. 中国科学院丹江口湿地生态系统野外科学观测研究站,武汉,430074
- 作者简介：
  
  [ "张家铮(2000—), 男, 硕士研究生, 主要从事生态遥感研究。E-mail: 2263591693@qq.com" ]
- 基金信息：
  
  国家自然科学基金重点项目(32030069);国家自然科学基金青年基金项目(32101525)
- DOI：10.13870/j.cnki.stbcxb.2025.01.015
  中图分类号： Q948.1
- 纸质出版：2025
- 稿件说明：
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张家铮, 朱大明, 王德智, 等. 金沙江中游水电站对植被时空变化的影响[J]. 水土保持学报, 2025,39(1):326-337.

ZHANG Jiazheng, ZHU Daming, WANG Dezhi, et al. Effects of Hydropower Station on the Temporal and Spatial Changes of Vegetation in the Middle Reaches of the Jinsha River[J]. 2025, 39(1): 326-337.
张家铮, 朱大明, 王德智, 等. 金沙江中游水电站对植被时空变化的影响[J]. 水土保持学报, 2025,39(1):326-337. DOI： 10.13870/j.cnki.stbcxb.2025.01.015.

ZHANG Jiazheng, ZHU Daming, WANG Dezhi, et al. Effects of Hydropower Station on the Temporal and Spatial Changes of Vegetation in the Middle Reaches of the Jinsha River[J]. 2025, 39(1): 326-337. DOI： 10.13870/j.cnki.stbcxb.2025.01.015.

摘要

目的探究水电站群对植被时空变化的影响，阐明植被变化对水电站建设和气候因子的响应关系，为区域可持续发展和水电站可持续运营提供可靠的科学依据。方法利用归一化植被指数(NDVI)来反映植被变化，以谷歌地球引擎(GEE)为运算平台，耦合ModTrendr算法、Theil Sen-MK、贡献度分析、偏相关分析方法探究2000—2022年金沙江中游水电站对植被时空变化的影响，并分析气候在其中的效应。结果1) 负向突变集中于2011—2014年，突变区域集中于集水区。正向突变集中于2015年和2017年，突变区域集中于河岸5 km缓冲区范围内。植被产生积极响应的时间为蓄水后1~4 a，突变强度沿河岸向外逐渐减弱；2) 各水电站周边植被NDVI整体呈上升趋势(0.000 2~0.002 8/a)，在建设前、建设中、运营后呈升(平缓)-降-升趋势；3) 区域植被变化主要受到人类活动(水电站建设)与气候变化的共同作用，可解释度达69.12%，人类活动的贡献度远高于气候变化的贡献度。4) 温度、降水与NDVI偏相关系数分别为-0.28和-0.29，温度、降水在水电站不同阶段偏相关系数差别较大，表明水电站影响区域气候。结论水电站在修建期间对植被造成消极影响，运营后对植被产生积极影响，水电站建设对植被的影响高于气候变化的影响，且水电站的修建可能影响局部气候，温度和降水与植被NDVI整体相关性降低。

Abstract

ObjectiveTo explore the effects of hydropower stations on the temporal and spatial changes of vegetation

clarify the response relationship of vegetation changes to hydropower station construction and climate factors

and provide a reliable scientific basis for regional sustainable development and sustainable operation of hydropower stations.MethodsNormalized vegetation index (NDVI) was used to reflect the vegetation change. Google Earth Engine (GEE) was used as the computing platform

coupled with ModTrendr algorithm

Theil Sen-MK

contribution degree analysis and partial correlation analysis methods to explore the effects of hydropower stations in the middle reaches of the Jinsha River on the spatial and temporal changes of vegetation during 2000—2022

and the effects of climate it were analyzed.Results1) The negative mutations were concentrated from 2011 to 2014

and the mutation area was concentrated in the catchment area. The forward mutation was concentrated in 2015 and 2017

and the mutation area was concentrated within the 5 km buffer zone of the riverbank. The time for vegetation to produce positive response was 1—4 years after the water was impounded

and the mutation intensity gradually weakened along the riverbank. 2) The vegetation NDVI around each hydropower station presented an overall upward trend (0.000 2—0.002 8/a)

and an upward (gentle)-downward-upward trend before

during and after hydropower station construction. 3) Regional vegetation change was mainly caused by the joint action of human activities (hydropower station construction) and climate change

and the explanation degree was 69.12%. The contribution of human activities was much higher than that of climate change. 4) The partial correlation coefficients of temperature

precipitation and NDVI were -0.28 and -0.29

respectively. The partial correlation coefficients of temperature and precipitation differed greatly in different stages of hydropower stations

indicating that hydropower stations would affect regional climate.ConclusionHydropower stations have a negative impact on vegetation during construction and a positive impact on vegetation after operation. The impact of hydropower station construction on vegetation is higher than that of climate change

and the construction of hydropower stations may affect local climate

leading to a decrease in the overall correlation between temperature and precipitation and vegetation NDVI.

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Keywords

references

LI Y Y, CUI Q, LI C H, et al. An improved multi-objective optimization model for supporting reservoir operation of China's South-to-North Water Diversion Project[J]. Science of the Total Environment, 2017, 575: 970-981.

XU R R, ZENG Z Z, PAN M, et al. A global-scale framework for hydropower development incorporating strict environmental constraints[J]. Nature Water, 2023, 1: 113-122.

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: e115063.

ZHANG S N, YE L P, HUANG C Q, et al. Evolution of vegetation dynamics and its response to climate in ecologically fragile regions from 1982 to 2020: A case study of the Three Gorges Reservoir area[J]. Catena, 2022, 219: e106601.

YAO T C, LU H W, FENG W, et al. Evaporation abrupt changes in the Qinghai-Tibet Plateau during the last half-century[J]. Scientific Reports, 2019, 9: e20181.

ZHONG X Z, WANG J L, DENG Y C, et al. Spatio-temporal variation and driving forces of vegetation cover in the Nujiang-Salween River Basin[J]. Acta Ecologica Sinica, 2023, 43(24): 10182-10201. 钟旭珍, 王金亮, 邓云程, 等. 怒江-萨尔温江流域植被覆盖时空变化趋势及驱动力[J]. 生态学报, 2023, 43(24): 10182-10201.

YU J, LIU J L, ZHANG Q Y. Study on vegetation cover change in Xiluudu Reservoir area[J]. Yangtze River, 2019, 50(S2): 46-50. 于江, 刘佳丽, 张茜彧. 溪洛渡库区植被覆盖变化研究[J]. 人民长江, 2019, 50(S2): 46-50.

ZHANG X H, HE Y H, HU Y T. Evolution and causes of vegetation and wind erosion at reservoir edge in arid sandstorm area[J]. Bulletin of Soil and Water Conservation, 2020, 40(6): 1-7. 张晓虹, 何有华, 胡彦婷. 干旱风沙区水库边缘植被-风力侵蚀的变化及成因[J]. 水土保持通报, 2020, 40(6): 1-7.

QU S, WANG L C, LIN A W, et al. What drives the vegetation restoration in Yangtze River Basin, China: Climate change or anthropogenic factors?[J]. Ecological Indicators, 2018, 90: 438-450.

KENNEDY R E, YANG Z Q, COHEN W B. Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr-Temporal segmentation algorithms[J]. Remote Sensing of Environment, 2010, 114(12): 2897-2910.

DEVRIES B, DECUYPER M, VERBESSELT J, et al. Tracking disturbance-regrowth dynamics in tropical forests using structural change detection and Landsat time series[J]. Remote Sensing of Environment, 2015, 169: 320-334.

ZHU Z, WOODCOCK C E. Continuous change detection and classification of land cover using all available Landsat data[J]. Remote Sensing of Environment, 2014, 144: 152-171.

OUYANG W, HAO F H, ZHAO C, et al. Vegetation response to 30years hydropower cascade exploitation in upper stream of Yellow River[J]. Communications in Nonlinear Science and Numerical Simulation, 2010, 15(7): 1928-1941.

LIU Y L, LU H W, TIAN P P, et al. Evaluating the effects of dams and meteorological variables on riparian vegetation NDVI in the Tibetan Plateau[J]. The Science of the Total Environment, 2022, 831: e154933.

YANG Y J, ZHOU X C, HE Z G, et al. Research on multi-temporal digital twin landslide deformation monitoring method and application: A case study of Baige landslide in Jinshajiang River[J]. Hydrogeology Engineering Geology, 2019, 51(2): 132-143. 杨云建, 周学铖, 何中海, 等. 多时相数字孪生滑坡变形监测方法与应用研究: 以金沙江白格滑坡为例[J]. 水文地质工程地质, 2024, 51(2): 132-143.

YANG H Y, HAN R. Effect of the Jinsha River hydropower development on population viability of Coreius guichenoti based on the Vortex model[J]. Acta Ecologica Sinica, 2024, 44(9): 3984-3998. 杨红义, 韩瑞. 基于Vortex模型分析金沙江水电开发对圆口铜鱼种群生存力的影响[J]. 生态学报, 2024, 44(9): 3984-3998.

YANG J, HUANG X. The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019[J]. Earth System Science Data, 2021, 13(8): 3907-3925.

YIN Q D, LIU C X, TIAN Y. Detecting dynamics of vegetation disturbance in forest natural reserve using Landsat imagery and LandTrendr algorithm: The case of Chaisong and Taibaishan Natural Reserves in Shaanxi, China[J]. Acta Ecologica Sinica, 2020, 40(20): 7343-7352. 殷崎栋, 柳彩霞, 田野. 基于Landsat时序影像和LandTrendr算法的森林保护区植被扰动研究: 以陕西柴松和太白山保护区为例[J]. 生态学报, 2020, 40(20): 7343-7352.

KENNEDY R E, YANG Z Q, GORELICK N, et al. Implementation of the LandTrendr algorithm on google earth engine[J]. Remote Sensing, 2018, 10(5): e691.

WANG S, WANG S S, FAN F L. Change patterns of NDVI(1985—2018) in the Yarlung Zangbo River Basin of China based on time series segmentation algorithm[J]. Acta Ecologica Sinica, 2020, 40(19): 6863-6871. 王塞, 王思诗, 樊风雷. 基于时间序列分割算法的雅鲁藏布江流域NDVI(1985—2018)变化模式研究[J]. 生态学报, 2020, 40(19): 6863-6871.

CHEN Y P, ZHOU X, CHEN Y, et al. Identification of key areas for ecological protection and restoration in national land space by integrating time-series remote sensing analysis[J]. Transactions of the Chinese Society for Agricultural Machinery, 2023, 54(10): 161-170. 陈元鹏, 周旭, 陈妍, 等. 融合时序遥感分析的国土空间生态保护修复关键区识别[J]. 农业机械学报, 2023, 54(10): 161-170.

WANG F, GE Q S, WANG S W, et al. A new estimation of urbanization's contribution to the warming trend in China[J]. Journal of Climate, 2015, 28(22): 8923-8938.

JIN K, WANG F, HAN J Q, et al. Contribution of climatic change and human activities to vegetation NDVI change over China during 1982—2015[J]. Acta Geographica Sinica, 2020, 75(5): 961-974. 金凯, 王飞, 韩剑桥, 等. 1982—2015年中国气候变化和人类活动对植被NDVI变化的影响[J]. 地理学报, 2020, 75(5): 961-974.

ZHU L F, XIE S Y, YANG H, et al. Relative effects of climate change and human activities on vegetation coverage change in Sichuan[J]. Journal of West China Forestry Science, 2022, 51(6): 8-16. 朱林富, 谢世友, 杨华, 等. 气候变化与人类活动在四川植被覆盖度变化中的相对作用[J]. 西部林业科学, 2022, 51(6): 8-16.

WU H, BAI J, LI J L, et al. Study of spatio-temporal variation in fractional vegetation cover and its influencing factors in Xinjiang, China[J]. Chinese Journal of Plant Ecology, 2024, 48(1): 41-55. 吴瀚, 白洁, 李均力, 等. 新疆地区植被覆盖度时空变化及其影响因素分析[J]. 植物生态学报, 2024, 48(1): 41-55.

ABDUL AZIZ O I, BURN D H. Trends and variability in the hydrological regime of the Mackenzie River Basin[J]. Journal of Hydrology, 2006, 319(1/2/3/4): 282-294.

WAN H, XIE Y L, LI B, et al. An integrated method to identify and evaluate the impact of hydropower development on terrestrial ecosystem[J]. Environmental Impact Assessment Review, 2023, 99: e107042.

YI Y J, ZHOU Y, SONG J, et al. The effects of cascade dam construction and operation on riparian vegetation[J]. Advances in Water Resources, 2019, 131: e103206.

YANG Y, WANG Y H, CONG N, et al. Impacts of the Three Gorges Dam on riparian vegetation in the Yangtze River Basin under climate change[J]. The Science of the Total Environment, 2024, 912: e169415.

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