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作 者:齐凌艳 张帅 熊爱玲 黄佳聪[4] 贾蔡 支俊俊 吴凤文 QI Lingyan;ZHANG Shuai;XIONG Ailing;HUANG Jiacong;JIA Cai;ZHI Junjun;WU Fengwen(Engineering Technology Research Center of Resources Environment and GIS,Wuhu 241003;Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze-Huaihe River Basin,Wuhu 241003;School of Geography and Tourism,Anhui Normal University,Wuhu 241003;Nanjing Institute of Geography and Limnology,Key Laboratory of Watershed Geographic Sciences,Chinese Academy of Sciences,Nanjing 210008)
机构地区:[1]资源环境与地理信息工程安徽省工程技术研究中心,芜湖241003 [2]江淮流域地表过程与区域响应安徽省重点实验室,芜湖241003 [3]安徽师范大学地理与旅游学院,芜湖241003 [4]中国科学院南京地理与湖泊研究所,中国科学院流域地理学重点实验室,南京210008
出 处:《环境科学学报》2022年第12期156-170,共15页Acta Scientiae Circumstantiae
基 金:国家自然科学基金项目(No.42001087,1971138);安徽省自然科学基金项目(No.1908085QD151);中国科学院青年创新促进会项目(No.2019313)。
摘 要:长江流域平原区水网密布、渔业发达,养殖池塘造成的氮磷污染问题突出,是河湖富营养化的重要污染源之一;从大空间尺度,精细化估算养殖池塘的氮磷污染负荷,对水污染的精准防控具有重要意义.以长江流域为研究区,依托Google Earth Engine遥感大数据平台,构建了基于机器学习算法的养殖池塘识别模型,精细化识别了长江流域养殖池塘的分布与类型;梳理养殖坑塘的氮磷污染研究案例,针对长江流域养殖坑塘的特征,构建氮磷污染负荷的估算方法,评估氮磷污染负荷的时空分布.研究结果表明:2021年,长江流域养殖池塘总面积为14567km^(2),包括鱼塘5820 km^(2)、虾蟹塘8747 km^(2)、氮磷排放量分别为95059、16224 t;中部地区的氮磷污染负荷最大,东部地区次之,西部地区最小.本研究是遥感大数据在大尺度污染负荷定量分析的尝试应用,方法适用于其它类型污染负荷的估算.In the lowland areas of the Yangtze River Basin,dense river networks result in wide distribution of aquaculture ponds.These aquaculture ponds with considerable nitrogen(N)and phosphorus(P)discharge partially caused lake and river eutrophication.To control eutrophication in a quantitative manner,it is extremely important to quantify N&P loading from aquaculture ponds at a large area.This study selected the Yangtze River Basin as the study area,and a machine learning-based model was developed to identify aquaculture ponds based on the big data platform,Google Earth Engine,to generate the spatial distribution and types of aquaculture ponds.N&P loading from these aquaculture ponds were estimated mainly based on the publications of previous case studies.Our investigation results revealed that:In 2021,aquaculture ponds in the Yangtze River Basin had a total area of 14567 km^(2),including fish ponds(5820 km^(2))and shrimp-crab ponds(8747 km^(2)).These aquaculture ponds resulted in a N&P loss of 95059 t and 16224 t,respectively.The N&P loading of aquaculture ponds were most severe in the central region,followed by the eastern region and the western region.This study was an attempt of applying remote sensing big data in quantifying nutrient loss at a large scale.The developed model is transferable to other case studies.
分 类 号:X52[环境科学与工程—环境工程]
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