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An Introduction to Identifying Nonpoint Sources of Water Pollution Using a Modified Land Use Conflict Analysis Identification Strategy (LUCIS) Model, Non-point Source Identification Strategy: NPSIS

机译:使用改良的土地利用冲突分析识别策略(LUCIS)模型识别水源面源的介绍,非面源源识别策略:NPSIS

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摘要

This paper examines the Non-Point Source Identification Strategy (NPSIS); a modification of the Land Use Conflict Identification Strategy (LUCIS): NPSIS is a raster model useful for identifying non-point sources of water pollution from three known contributors (agriculture, domestic, and natural background). By using a standard operating procedure, developers are able to create standardized datasets useful for identifying non-point sources of water pollution throughout the contiguous United States. The NPSIS model process requires the use of three “non-point source water pollution” contributors. A contributor is termed as a Non-Point Category (NPC) that contains collective elements (i.e. nutrient applications for agricultural purposes and urban runoff from highly developed areas). Using a survey, water resource professionals familiar with chosen study areas rank each NPC element according to potential impact to water quality. Following the survey, raster datasets that represent each NPC and impact to water quality are created using a lowest to highest (“1-9”) ordinal rank system derived from survey results after which each dataset is normalized using a (“1-3”) ordinal rank. Finally, the normalized NPC datasets are combined into one final model useful for identifying each dominant NPC by rank and location within a specified USGS watershed. In conclusion, the modifications to the LUCIS method yields results beneficial for identifying non-point source loads of water pollution.
机译:本文研究了非点源识别策略(NPSIS);土地使用冲突识别策略(LUCIS)的修改:NPSIS是一种栅格模型,可用于识别来自三个已知贡献者(农业,家庭和自然背景)的非点源水污染。通过使用标准的操作程序,开发人员可以创建标准化的数据集,这些数据集可用于识别整个美国附近的​​非点源水污染源。 NPSIS模型过程要求使用三个“非点源水污染”贡献者。贡献者被称为非点源类别(NPC),其中包含集体要素(即,用于农业目的的养分应用和高度发达地区的城市径流)。使用一项调查,熟悉选定研究领域的水资源专业人员根据对水质的潜在影响对每个NPC要素进行排名。调查之后,使用从调查结果中得出的最低到最高(“ 1-9”)顺序等级系统创建代表每个NPC和对水质的影响的栅格数据集,然后使用(“ 1-3” )顺序等级。最后,将归一化的NPC数据集合并为一个最终模型,该模型可用于通过指定USGS分水岭内的等级和位置来识别每个主要NPC。总之,对LUCIS方法的修改产生了有益于识别水污染的非点源负荷的结果。

著录项

  • 作者

    Cziesch Jarrett;

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  • 年度 2015
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  • 原文格式 PDF
  • 正文语种 en_US
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