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Changes And Influencing Factors Of Surface Water Bodies In The Yellow River Basin Based On GEE

Posted on:2024-07-21Degree:MasterType:Thesis
Country:ChinaCandidate:Z K ZhaoFull Text:PDF
GTID:2530307121968889Subject:Soil and Water Conservation and Desertification Control
Abstract/Summary:
Under the combined impact of climate change and human activities,there is a prominent contradiction between water resources supply and demand in the Yellow River Basin.Conducting dynamic monitoring of surface water bodies can help explore the distribution status of water resources in the basin.Traditional methods of water body extraction have heavy workloads,poor real-time performance,and difficult comprehensiveness in reflecting the characteristics of surface water bodies with spatial and temporal changes.Therefore,based on the Google Earth Engine cloud platform and Landsat time-series image dataset,coupled with the Hydro LAKES and China Reservoir dataset,this paper used the Hybrid Index algorithm to achieve automatic extraction of surface water bodies,construct a full-time evolution chart of surface water bodies,analyze the spatial differentiation and changing laws of surface water body area in the Yellow River Basin,and explain the contribution of various factors to the change of surface water body area from the aspects of climate change and human activities.The results provide a scientific basis for refined management and optimized allocation of water resources in the Yellow River Basin and promoting high-quality development of the region.The results show that:(1)The hybrid index algorithm,which was constructed based on both the vegetation index and the water body index,successfully avoids the randomness and chance of artificially determining the threshold value of water body index.In comparison with existing methods,the time-series data of surface water bodies in the Yellow River Basin,which were constructed in this study,exhibit increased accuracy.(2)The spatial distribution of surface water bodies in the Yellow River basin is uneven,and the spatial and temporal variation of surface water body area are evident.The total area of surface water bodies is 9424.4 km~2,with the largest annual average area located between Lanzhou and Toudaoquan,accounting for 31.9%of the total area of water bodies in the basin.The total area of lakes and reservoirs in the basin is 2578.8 km~2 and 1481.27 km~2,respectively.From 1986 to 2021,the total area of water bodies,lakes,and reservoirs in the basin expanded by 2983.8 km~2(40.4%),281.1 km~2(11.5%),and 1017.6 km~2(101.7%),respectively.Water bodies in the endorheic zone showed a decreasing trend,while the area of water bodies in the other zones showed an expansion trend.(3)102 lakes in the Yellow River basin expanded in area while 23 shrank.The expanded lakes are mainly concentrated in the area above Longyangxia and between Lanzhou and Toudaojia,while the shrunken lakes are predominantly situated in the in-stream zone.The area of 204 reservoirs in the basin expanded,and 77 reservoirs shrank.The expanded reservoirs are primarily located in the area between Lanzhou and Toudaojia and between Longmen and Sanmenxia.Most lakes and reservoirs underwent area changes of less than 5km~2 and are small in size,with an area of less than 10 km~2.(4)Precipitation and water surface evaporation contribute positively to the long-term change trend of the entire basin’s water area,with relative contribution rates of 47%and 4.4%,respectively;temperature shows a negative contribution with a relative contribution rate of16%.The increase in temperature has accelerated the melting of glaciers,snow cover,and permafrost in the Yellow River source region,thereby increasing the inflow into the lake and supplementing the natural water area of the Yellow River source region.The long-term change trend of the basin’s water area due to reservoir construction shows a positive contribution with a contribution rate of 32.6%.
Keywords/Search Tags:Remote sensing cloud, Surface water bodies, Yellow River basin, Lakes and reservoirs, Influencing factors
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