Effects of Hydropower Station on the Temporal and Spatial Changes of Vegetation in the Middle Reaches of the Jinsha River

ZHANG Jiazheng; ZHU Daming; WANG Dezhi; DAI Zuomin

doi:10.13870/j.cnki.stbcxb.2025.01.015

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Effects of Hydropower Station on the Temporal and Spatial Changes of Vegetation in the Middle Reaches of the Jinsha River

更新时间：2025-03-14

- Effects of Hydropower Station on the Temporal and Spatial Changes of Vegetation in the Middle Reaches of the Jinsha River
- Vol. 39, Issue 1, Pages: 326-337(2025)
- 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：
- 基金信息：
- DOI：10.13870/j.cnki.stbcxb.2025.01.015
  CLC： Q948.1
- Published：2025
- 稿件说明：
移动端阅览
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：

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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