【摘要】：湟水河流域水質(zhì)監(jiān)測數(shù)據(jù)的信息挖掘?qū)λ|(zhì)狀況的了解、水污染的綜合治理及水的分類應(yīng)用都很有意義。數(shù)據(jù)可視化通過圖形形式,將數(shù)據(jù)信息表達(dá)出來,形象直觀生動(dòng)地反映出湟水河流域水質(zhì)監(jiān)測數(shù)據(jù)表達(dá)出的信息。本文對(duì)國內(nèi)外水質(zhì)監(jiān)測數(shù)據(jù)的分析模型及可視化研究現(xiàn)狀作了綜述。根據(jù)湟水河流域的水文資料及環(huán)境特點(diǎn),選取西寧湟水河流域枯水期52個(gè)監(jiān)測點(diǎn),18個(gè)水質(zhì)監(jiān)測指標(biāo)。測得湟水河西寧流域52個(gè)樣本,18個(gè)指標(biāo)的數(shù)據(jù)陣([B]52×18)。主要研究內(nèi)容:1.優(yōu)化布點(diǎn),集中采樣,分析測定。按照西寧湟水河流域的水功能劃分情況、周圍環(huán)境和流域特點(diǎn)。布設(shè)了52個(gè)監(jiān)測點(diǎn),包含了西寧市湟水河干流、甘河工業(yè)園區(qū)、海湖新區(qū)、北川河、南川河和沙塘川河。于2015年11月份,采集水樣。參考國家標(biāo)準(zhǔn)和環(huán)境標(biāo)準(zhǔn)分析檢測了52個(gè)樣品的pH、電導(dǎo)率、濁度、氟化物、全鹽量、COD、BOD、氨氮、亞硝酸鹽氮、六價(jià)鉻、Ca、Fe、Cu、Zn、Mg、K、Na等18個(gè)監(jiān)測指標(biāo),獲得了52個(gè)監(jiān)測點(diǎn),18個(gè)指標(biāo)的監(jiān)測數(shù)據(jù)。2.水質(zhì)綜合評(píng)價(jià)的模型研究。應(yīng)用主成分分析、因子分析、聚類分析等化學(xué)計(jì)量學(xué)方法對(duì)監(jiān)測數(shù)據(jù)進(jìn)行建模分析。得到了西寧湟水河流域的9個(gè)綜合污染因子并用層次分析法對(duì)監(jiān)測點(diǎn)水質(zhì)做了分類。因子模型適用性檢驗(yàn)結(jié)果表明監(jiān)測數(shù)據(jù)不適于因子分析,反映出各指標(biāo)間相關(guān)性比較差。選取4個(gè)指標(biāo),建立了的加權(quán)疊加回歸綜合評(píng)價(jià)模型,與單指標(biāo)評(píng)價(jià)法結(jié)合對(duì)西寧湟水河流域水質(zhì)做了綜合評(píng)價(jià)。3.西寧湟水河流域水質(zhì)綜合評(píng)價(jià)的可視化研究。應(yīng)用ArcGIS軟件的ArcMap模塊,借助全球河網(wǎng)圖層,對(duì)監(jiān)測點(diǎn)位和加權(quán)疊加回歸綜合評(píng)價(jià)模型所得的結(jié)果作了可視化。對(duì)監(jiān)測點(diǎn)位應(yīng)用湟水河河網(wǎng)圖,標(biāo)明了采樣點(diǎn)在湟水河的相對(duì)位置。對(duì)加權(quán)疊加回歸綜合評(píng)價(jià)結(jié)果在谷歌地形圖下,用安全預(yù)警五級(jí)分類顏色和不同的形狀,形象直觀地展示出監(jiān)測點(diǎn)的水質(zhì)分類情況。本文以西寧湟水河流域水質(zhì)綜合評(píng)價(jià)為研究背景,通過布點(diǎn)、采樣、測試、數(shù)據(jù)處理,建立了加權(quán)疊加回歸綜合評(píng)價(jià)模型,對(duì)湟水河的綜合評(píng)價(jià)提供新的思路。利用全球河網(wǎng)圖層,對(duì)監(jiān)測點(diǎn)位和加權(quán)疊加回歸模型所得的結(jié)果作了可視化分析。用預(yù)警五級(jí)分類顏色,形象直觀地展示出監(jiān)測點(diǎn)的水質(zhì)分類情況,為湟水河污染綜合治理提供了水質(zhì)監(jiān)測的可視化信息技術(shù)。
[Abstract]:The information mining of water quality monitoring data in Huangshui River basin is of great significance to the understanding of water quality, the comprehensive treatment of water pollution and the application of water classification. Data visualization is used to express the data information in graphic form, which can directly and vividly reflect the information expressed by the water quality monitoring data in the Huangshui River Basin. In this paper, the analysis model and visualization research status of water quality monitoring data at home and abroad are summarized. According to the hydrological data and environmental characteristics of the Huangshui River Basin, 52 monitoring points and 18 water quality monitoring indexes were selected in the dry season of Xining Huangshui River Basin. The data matrix of 52 samples and 18 indexes in Xining watershed of Huangshui River was obtained ([B] 52 脳 18). The main research content is: 1. Optimization of distribution, centralized sampling, analysis and measurement. According to the water function of Xining Huangshui River basin, the surrounding environment and watershed characteristics. There are 52 monitoring sites, including the main stream of Huangshui River in Xining City, Ganhe Industrial Park, Haihu New area, Beichuan River, Nanchuan River and Shatangchuan River. Water samples were collected in November 2015. The pH, conductivity, turbidity, fluoride, total salt content of COD _ DBOD, ammonia nitrogen, nitrite nitrogen, hexavalent chromium (Cr _ (2) _ (2), CaFeCuFE _ (Zn) mg ~ (2 +) K _ (+) Na were determined in 52 samples with reference to the national and environmental standards. 52 monitoring points and 18 monitoring data were obtained for the determination of pH, conductivity, turbidity, fluoride, total salt content, ammonia nitrogen, nitrite nitrogen and hexavalent chromium. Study on the Model of Comprehensive Evaluation of Water quality. The principal component analysis, factor analysis, cluster analysis and other chemometrics methods are used to model and analyze the monitoring data. Nine comprehensive pollution factors in Xining Huangshui River basin were obtained and the water quality of monitoring points was classified by analytic hierarchy process (AHP). The test results of the applicability of the factor model show that the monitoring data is not suitable for factor analysis, which reflects the poor correlation among the indicators. The comprehensive evaluation model of weighted superposition regression was established by selecting four indexes, and the water quality of Xining Huangshui River basin was evaluated by combining with single index evaluation method. Visualization study on Water quality Comprehensive Evaluation in Xining Huangshui River Basin. By using ArcMap module of ArcGIS software and with the help of global river network layer, the results of monitoring points and weighted superposition regression comprehensive evaluation model are visualized. The relative position of the sampling points in the Huangshui River is indicated by the application of the Huangshui River network map to the monitoring points. The results of comprehensive evaluation of weighted superposition regression under the Google topographic map, the color and different shapes of the five levels of safety warning are used to visualize the water quality classification of the monitoring points. Based on the comprehensive evaluation of water quality in Xining Huangshui River basin, a comprehensive evaluation model of weighted superposition regression is established through placement, sampling, testing and data processing, which provides a new idea for comprehensive evaluation of Huangshui River. Based on the global river network layer, the results of monitoring points and weighted superposition regression model are analyzed visually. By using the color classification of the five levels of early warning, the water quality classification of the monitoring points is displayed visually and visually, which provides visual information technology for the comprehensive control of the pollution of the Huangshui River.
【學(xué)位授予單位】：青海師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：X832

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相關(guān)期刊論文 前10條

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本文編號(hào)：2139143