本文關(guān)鍵詞：廣州市農(nóng)業(yè)表層土壤重金屬污染及其與景觀格局的多尺度關(guān)系　出處：《廣州大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 農(nóng)業(yè)土壤 重金屬 景觀格局 多尺度 廣州市

【摘要】：隨著快速城市化和工業(yè)化,我國(guó)農(nóng)業(yè)土壤污染尤其重金屬污染問(wèn)題日益突出。人類活動(dòng)干擾下的土壤污染極其復(fù)雜,具有點(diǎn)源和非點(diǎn)源污染特征。重金屬遷移擴(kuò)散并累積到土壤的過(guò)程往往受到從樣點(diǎn)到區(qū)域一系列尺度上景觀要素時(shí)空配置的影響,將兩者聯(lián)系起來(lái)有助于理解土壤污染機(jī)制,但目前研究多局限于單一尺度。鑒于土壤和景觀特征的空間異質(zhì)性,亟待從多尺度角度探討土壤重金屬污染分布及其與景觀格局的關(guān)系。本文以廣州市農(nóng)業(yè)表層土壤為研究對(duì)象,基于2005年641個(gè)重金屬(Cd、Pb、As、Cr、Ni)樣點(diǎn)數(shù)據(jù)、土地利用/覆蓋圖,采用多尺度嵌套模型、Pearson/Spearman相關(guān)分析、地理加權(quán)回歸和偏冗余分析方法,揭示土壤重金屬污染特征及其多尺度空間結(jié)構(gòu),并在此基礎(chǔ)上疊加不同景觀格局因子,解析不同尺度上景觀格局與土壤重金屬污染的關(guān)系,識(shí)別特定尺度起決定作用的景觀格局因子。主要結(jié)論如下:(1)廣州市農(nóng)業(yè)土壤多處于安全水平,只有5-18%的土壤受到Ni、Cds和A污染,并且以輕度污染為主。不同農(nóng)業(yè)用地類型上重金屬污染水平多按照農(nóng)藥化肥施用量遞減:果園/菜地水田/旱地林地,但是多數(shù)情況下不同地類間的差異并不顯著,可能與本研究區(qū)土壤重金屬元素主要受到成土母質(zhì)的影響有關(guān)。(2)農(nóng)業(yè)土壤重金屬的空間變異具有尺度依賴性,多尺度嵌套模型較單尺度的普通克里格插值,更能充分地挖掘和利用土壤Cd和Pb的空間變異結(jié)構(gòu),插值精度明顯優(yōu)于粗粒度和中粒度尺度,但與細(xì)粒度尺度相當(dāng)。多尺度嵌套模型插值結(jié)果顯示,廣州市農(nóng)業(yè)土壤Cd和Pb含量普遍高于廣東省土壤背景值,但多數(shù)未超過(guò)中國(guó)農(nóng)業(yè)土壤最大允許標(biāo)準(zhǔn),Cd污染區(qū)主要位于中心城區(qū),少量位于從化區(qū)、南沙區(qū)以及花都區(qū)與白云區(qū)交界,可能與交通活動(dòng)釋放、污水灌溉和過(guò)量施肥有關(guān)。(3)Pearson/Spearman相關(guān)分析、地理加權(quán)回歸(GWR)和偏冗余分析顯示,土壤重金屬污染與景觀格局的關(guān)系因重金屬元素和空間尺度而異。調(diào)整的決定系數(shù)、校正的赤池信息準(zhǔn)則(AICc)和模型殘差的自相關(guān)性檢驗(yàn)(Moran’s I)顯示,GWR模型相比OLS模型能更好地揭示土壤重金屬污染與景觀格局的關(guān)系,且最佳分析尺度為5km×5km。GWR模型和相關(guān)分析結(jié)果顯示,3個(gè)尺度上土壤重金屬污染與景觀格局的關(guān)系存在空間變異性,兩者的關(guān)系可正可負(fù),多數(shù)土壤重金屬污染水平與成土母質(zhì)組成(沉積物或花崗巖的比例)和土地利用格局(土地利用類型的比例,尤其是水體的比例)呈顯著相關(guān),顯著相關(guān)區(qū)域主要位于白云區(qū)、番禺區(qū)和南沙區(qū),表明成土母質(zhì)、污染物隨水體遷移或者污水灌溉可能是土壤重金屬輸入的主要途徑。而偏冗余分析表明,景觀格局可解釋土壤重金屬污染變異的12.8-29.1%,解釋力度隨尺度遞增:10km×10km5km×5km2km×2km。不同尺度上,三組景觀格局因子(成土母質(zhì),距離-密度變量,土地利用)對(duì)土壤重金屬污染變異的貢獻(xiàn)不盡相同,50%以上可解釋的土壤污染變異是由兩組或兩組以上的景觀格局因子共同決定。總體上,成土母質(zhì)和距離-密度變量對(duì)土壤污染的影響隨研究尺度增加,而土地利用的影響則隨研究尺度遞減。
[Abstract]:With the rapid city and industrialization of agricultural soil pollution in China especially heavy metal pollution problems have become increasingly prominent. Soil pollution under the interference of human activities is extremely complex, with point source and non-point source pollution characteristics of heavy metal migration diffusion and accumulated into the soil samples from the process is often subject to regional scale on a series of temporal and spatial distribution of landscape elements effect of linking the two help to understand the mechanism of soil pollution, but the current research is limited to a single scale. In view of the spatial heterogeneity of soil and landscape features, to investigate the soil heavy metals pollution distribution and its relationship with the landscape pattern from the multi-scale perspective. Based on the agricultural soil surface in Guangzhou city as the research object, in 2005 641 based on the heavy metals (Cd, Pb, As, Cr, Ni) sample data, land use / land cover map, using multi-scale nested model, Pearson/Spearman correlation analysis, geographical weighted back Return and partial redundancy analysis method, and reveals the multi scale spatial structure characteristics of heavy metal pollution in soil, and the factors of different landscape pattern based on the superposition relation analysis on different scales of landscape pattern and soil heavy metal pollution, identify the specific scale determining factor of landscape pattern effect. The main conclusions are as follows: (1) Guangzhou City Agricultural Soil in the security level, only 5-18% of the soil by Ni, Cds and A pollution, and light pollution. Different types of agricultural land on the heavy metal pollution level in accordance with the amount of chemical fertilizer pesticide decline: Orchard / vegetable / paddy upland forest, but not significantly difference between different land types in most cases, may be related to soil heavy metals the elements in the study area are mainly affected by soil parent materials. (2) the spatial variability of heavy metals in agricultural soils with scale dependent, multi-scale nested model with single scale The ordinary Kriging interpolation, to fully excavate and utilize the soil Cd and Pb spatial structures, the interpolation accuracy is better than the coarse grain size and scale, but the scale is quite fine-grained and multi-scale nested model interpolation. The results showed that Guangzhou agricultural soil Cd and Pb content is higher than the general background values of soils in Guangdong Province, but most did not exceed the maximum allowable standard of agricultural soil Chinese, Cd pollution areas are mainly located in the city center is located in Conghua District, a small, at the junction of Nansha District and Huadu District and Baiyun District, may release and transport activities, sewage irrigation and excessive fertilizer. (3) Pearson/Spearman correlation analysis, geographical weighted regression (GWR) and partial redundancy analysis show that the relationship between soil heavy metal pollution and landscape pattern due to heavy metals and different spatial scales. The adjusted coefficient of determination, Akaike information criterion (AICc) self correlation correction and model residuals (Moran s I) test showed that the GWR model compared with the OLS model can better reveal the relationship between soil heavy metal pollution and landscape pattern analysis, and the best scale of 5km * 5km.GWR model and correlation analysis showed that the 3 scale relationship between soil heavy metal pollution and landscape pattern in the spatial variability of the relationship between the two can be positive or negative, most of the soil heavy metal pollution level and soil composition (sediment or granite ratio) and land use pattern (land use type proportion, especially water ratio) were significantly correlated, significant correlation area mainly located in Baiyun District, Panyu District and Nansha District, shows that soil parent material, with water pollutant migration or sewage irrigation may be the main way of soil heavy metal input. And partial redundancy analysis showed that the landscape pattern can explain the variation of 12.8-29.1% of soil heavy metal pollution, interpretation efforts with scale of delivery Add: 10km * 10km5km * 5km2km * 2km. three groups of different scale, landscape pattern factor (soil, distance and density variables, land use) of soil heavy metal pollution variation contribution is not the same, the soil pollution variation of more than 50% can be explained is decided jointly by two or more than two groups of landscape factors overall, soil density and distance variables on the soil pollution research with the scale increasing, and the influence of land use along with the scale of decline.

【學(xué)位授予單位】：廣州大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：X53;P901

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本文編號(hào)：1363965