Question

请帮忙翻译下面文章 拜托很急

A process-based preferential flow transport model was implemented in a geographic information system to locate areas
in the landscape with high risk of contamination by agrochemicals, especially pesticides. Protecting ground water resources
necessitates a reliable ground water quality monitoring strategy. It is valuable to be able to focus monitoring on areas with
the highest risk of contamination because monitoring ground water is an expensive activity, especially at the landscape scale.
The objective of this project was to develop a tool that quantifiably estimates distributed ground water contamination risk in
order to develop reliable, cost-effective ground water observation networks. The tool is based on a mechanistic model of
chemical movement via preferential flow and uses land cover data, information about chemical properties, and modeled
recharge to estimate the concentration of chemical reaching the ground water at each point in the landscape. The distributed
risk assessment tool was tested by comparing the model-predicted risk with observed concentrations from 40 sampling wells
in Cortland County, New York, for atrazine (pesticide) and nitrate, the latter assumed to be an indicator of agricultural pollution.
The tool predictions agreed well with observed nitrate concentrations and pesticide detections. An Internet-based version
of this tool is currently being developed for ready application to New York State.

Answer 1

请帮忙翻译下面文章 拜托很急
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A process-based preferential flow transport model was implemented in a geographic information system to locate areas
in the landscape with high risk of contamination by agrochemicals, especially pesticides. Protecting ground water resources
necessitates a reliable ground water quality monitoring strategy. It is valuable to be able to focus monitoring on areas with
the highest risk of contamination because monitoring ground water is an expensive activity, especially at the landscape scale.
The objective of this project was to develop a tool that quantifiably estimates distributed ground water contamination risk in
order to develop reliable, cost-effective ground water observation networks. The tool is based on a mechanistic model of
chemical movement via preferential flow and uses land cover data, information about chemical properties, and modeled
recharge to estimate the concentration of chemical reaching the ground water at each point in the landscape. The distributed
risk assessment tool was tested by comparing the model-predicted risk with observed concentrations from 40 sampling wells
in Cortland County, New York, for atrazine (pesticide) and nitrate, the latter assumed to be an indicator of agricultural pollution.
The tool predictions agreed well with observed nitrate concentrations and pesticide detections. An Internet-based version