基于gis的美国佛罗里达州印第安河泻湖潜在径流系数和径流深度测定方法

Philip W. Bellamy, H. J. Cho
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引用次数: 1

摘要

印第安河泻湖系统(IRL),横跨佛罗里达东海岸约40%,是美国最大和最具生物多样性的河口之一。2011年,IRL发生了一次超级藻华事件,总氮和磷水平超过了历史水平。科学家们怀疑,通过地表径流产生的非点源污染可能对最近反复出现的藻华产生了重大影响。利用数字高程模型、土地覆盖/土地利用和土壤数据计算了IRL流域的径流系数。降雨数据用于计算研究区域2006-2016年间的径流深度。当2011年的月径流深度数据与之前对2011年泻湖超级藻华的研究进行比较时,高径流区域在视觉上与叶绿素a浓度较高的区域相匹配。土地开发是决定径流深度的重要变量(p < 0.0001),虽然用于得出径流深度,但降水的影响是边际显著的(p = 0.06)。土地开发与径流深度之间存在显著的空间自相关性(p < 0.0001)。产出将有助于就雨水管理作出决定,以促进更可持续的土地发展规划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A GIS-Based Approach for Determining Potential Runoff Coefficient and Runoff Depth for the Indian River Lagoon, Florida, USA
The Indian River Lagoon system (IRL), spanning ~40% of Florida’s east coast, is one of the nation’s biggest and most biodiverse estuaries. In 2011, a super algal bloom event occurred in the IRL with total nitrogen and phosphorus levels that exceeded historical levels. Scientists suspect that nonpoint source pollution through surface runoff may have had a significant impact on the recent recurring algal blooms. Digital Elevation Model, land cover/land use, and soil data were used to calculate a runoff coefficient for the IRL drainage basin. Rainfall data were used to calculate runoff depth for the study area between the years of 2006–2016. When the monthly runoff depth data for 2011 were compared to a previous study on the 2011 super algal bloom in the lagoon, areas with high runoff visually matched the areas with higher chlorophyll a concentrations. Land development was a significant variable for determining runoff depth ( p < 0.0001), and although used to derive runoff depths, the influence of precipitation was marginally significant ( p = 0.06). Significant spatial autocorrelation indicated local trends between land development and runoff depth ( p < 0.0001). Outputs will aid with decisions on stormwater management to more sustainable land development planning.
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