Accumulated effects on landscape pattern by hydroelectric cascade exploitation in the Yellow River basin from 1977 to 2006

被引:28
作者
Ouyang, Wei [1 ,2 ]
Skidmore, Andrew K. [2 ]
Hao, Fanghua [1 ]
Toxopeus, A. G. [2 ]
Abkar, Ali [2 ]
机构
[1] Beijing Normal Univ, Sch Environm, State Key Lab Water Environm Simulat, Beijing 100875, Peoples R China
[2] Int Inst Geoinformat Sci & Earth Observat ITC, NL-7500 AA Enschede, Netherlands
基金
中国国家自然科学基金;
关键词
Landscape accumulated effects; Metrics modeling; Hydroelectric cascade exploitation (HCE); Yellow River basin; ENVIRONMENTAL-IMPACT; METRICS; HYDROPOWER; INDICATOR; QUALITY; MODELS; REGION; LEVEL; GIS;
D O I
10.1016/j.landurbplan.2009.07.001
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
The accumulated impacts of hydroelectric cascade exploitation (HCE) on the landscape are greater than the simple sum of the impacts from a single dam. The spatial-temporal landscape characteristics resulting from the accumulated impacts of HCE from 1977 to 2006 in Longliu Watershed, a part of the Yellow River basin, were investigated. In this innovative approach, the FRAGSTATS model was employed to calculate landscape indices, which characterized landscape in term of its fragmentation, shape and diversity. Three fragmentation indicators and four shape indicators were analyzed at patch scale for each land use type in period of 1977-2006. The diversity simulators were calculated also at landscape scale. Furthermore, two hydroelectric cascade exploitation indicators, summed dam heights and hydroelectric generator capacities, were used to explore the correlated impact with landscape pattern. The analysis revealed that landscape fragmentation variations are strongly dependent on the magnitude of exploitation. The correlation coefficients ranged from 0.65 to 0.95. Except for PAFRAC value of Water area, all other shape metric variations were closely linked to the level of HCE and the correlation coefficients ranged from 0.5267 to 0.9514. This study also demonstrated that landscape diversity changes were exponentially related to hydro-exploitation parameters, with correlation coefficients arranging from 0.7487 to 0.9856. The correlation analysis also demonstrated that HCE a critical factor determining regional landscape variation. It is concluded that these correlation analysis assist in predicting landscape variation about future HCE. The findings will also be helpful for regional environmental management and for the understanding expected landscape transformations. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:163 / 171
页数:9
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