| LEI Guibin,ZHANG Ying,PAN Delu,WANG Difeng,FU Dongyang.Parameter selection and model research on remote sensing evaluation for nearshore water quality[J].Acta Oceanologica Sinica,2016,35(1):114-117 |
| 近岸水质遥感评价参数的选择及评价模型的研究 |
| Parameter selection and model research on remote sensing evaluation for nearshore water quality |
| 投稿时间：2015-03-19 修订日期：2015-09-08 |
| DOI：10.1007/s13131-016-0802-4 |
| 中文关键词: 主导水质参数 水质参数筛选 水质综合评价模型 雷州半岛近岸海域 |
| 英文关键词:main water quality parameters water quality parameter selection comprehensive water quality evaluation model Leizhou Peninsula nearshore waters |
| 基金项目: |
| 作者 | 单位 | E-mail | | 雷桂斌 | 广东省近海海洋变化与灾害预警重点实验室, 广东海洋大学, 广东湛江 524088 | | | 张莹 | 广东省近海海洋变化与灾害预警重点实验室, 广东海洋大学, 广东湛江 524088
卫星海洋环境动力学国家重点实验室, 国家海洋局第二海洋研究所, 浙江杭州 310012 | zhangying198206@126.com | | 潘德炉 | 卫星海洋环境动力学国家重点实验室, 国家海洋局第二海洋研究所, 浙江杭州 310012 | | | 王迪峰 | 卫星海洋环境动力学国家重点实验室, 国家海洋局第二海洋研究所, 浙江杭州 310012 | | | 付东洋 | 广东省近海海洋变化与灾害预警重点实验室, 广东海洋大学, 广东湛江 524088 | |
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| 中文摘要: |
| 利用遥感技术的水质评价是海洋环境监测的必然趋势,但目前可通过遥感技术反演的水质参数种类远少于《海水水质标准》中的35项,因此遥感监测时必须反演的水质参数有哪些?利用有限的参数该建立怎样的水质评价模型?成为我们关心的问题。本文以雷州半岛海域为研究对象,通过对实测数据的分析得出13种水质参数中的主导参数为总氮(N)、总磷(P)、化学需氧量(COD)、酸度(pH)、溶解氧(DO)这5种;再通过数理统计理论得出这5种参数对水质分类判别能力的大小关系为:COD> DO> P> N> pH,分别建立对应的五参数、四参数、三参数水质评价模型,并确定最优评价模型。即,雷州半岛海域水质遥感评价时必须反演的参数为COD、DO、P和N,水质综合评价模型为四参数模型,为后续其他海域水质的遥感监测提供可借鉴的方法。 |
| 英文摘要: |
| Using remote sensing technology for water quality evaluation is an inevitable trend in marine environmental monitoring. However, fewer categories of water quality parameters can be monitored by remote sensing technology than the 35 specified in GB3097-1997 Marine Water Quality Standard. Therefore, we considered which parameters must be selected by remote sensing and how to model for water quality evaluation using the finite parameters. In this paper, focused on Leizhou Peninsula nearshore waters, we found N, P, COD, PH and DO to be the dominant parameters of water quality by analyzing measured data. Then, mathematical statistics was used to determine that the relationship among the five parameters was COD >DO >P >N >pH. Finally, five-parameter, fourparameter and three-parameter water quality evaluation models were established and compared. The results showed that COD, DO, P and N were the necessary parameters for remote sensing evaluation of the Leizhou Peninsula nearshore water quality, and the optimal comprehensive water quality evaluation model was the fourparameter model. This work may serve as a reference for monitoring the quality of other marine waters by remote sensing. |
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