本文關(guān)鍵詞：黃河三角洲典型地區(qū)土壤水鹽動態(tài)規(guī)律、影響因素與預(yù)測模型　出處：《山東農(nóng)業(yè)大學(xué)》2017年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 黃河三角洲 土壤鹽漬化 時空變異規(guī)律 影響因子 預(yù)測模型

【摘要】：隨著全球的經(jīng)濟(jì)快速發(fā)展和人口激增,人地矛盾越來越突出,耕地資源的開發(fā)保護(hù)和土地退化的治理逐漸成為全球高度關(guān)注的熱點問題。作為土地退化主要類型之一,土壤鹽堿退化也已經(jīng)成為一個全球性的生態(tài)問題。黃河三角洲是我國乃至世界造陸速度最快的河口三角洲之一,具有豐富的土地資源,是我國重要的后備土地資源區(qū),然而,近50%的土地存在不同程度的鹽漬化現(xiàn)象。目前,該區(qū)土壤鹽漬化問題的系統(tǒng)研究尚較缺乏,仍需進(jìn)一步的探討。本文選取黃河三角洲典型地區(qū)墾利縣、無棣縣和“渤海糧倉”樣板區(qū)作為研究區(qū),在春、夏、秋、冬季典型時相,采用野外調(diào)查法采集0-15 cm、15-30 cm、30-45 cm、45-60cm土層土壤含鹽量數(shù)據(jù)和0-15 cm土層土壤含水量數(shù)據(jù)。通過樣點數(shù)據(jù)統(tǒng)計分析和GIS空間插值分析,研究土壤水鹽含量的空間分異規(guī)律;構(gòu)建土壤鹽漬化動態(tài)變化模型,研究土壤水鹽含量的時間變異規(guī)律;采用定性分析、定量分析和灰色關(guān)聯(lián)度法,研究土壤鹽漬化的主要影響因素;采用多元線性回歸分析法,篩選主要影響因子,構(gòu)建不同土層土壤含鹽量預(yù)測模型;從縣域、區(qū)域和微域尺度提出了土壤鹽漬化防治和改良利用措施。得到以下主要結(jié)論:(1)研究區(qū)土壤水鹽時空變異規(guī)律墾利縣、無棣縣和樣板區(qū)土壤含水量均為中等變異強(qiáng)度。墾利縣含水量較高的土壤主要分布于縣域西南部黃河南岸和東部濱海區(qū);無棣縣含水量較高的土壤主要分布于縣域北部濱海區(qū)。自2月至次年5月,樣板區(qū)土壤含水量呈先升高再降低的月際性變化規(guī)律。墾利縣和無棣縣土壤含水量均表現(xiàn)為夏季最高,春秋次之,冬季最低,而年際間差異不顯著。墾利縣、無棣縣和樣板區(qū)土壤含鹽量分別以2.0-5.0 g·kg-1、2.0-4.5 g·kg-1和2.0-6.0g·kg-1為主。垂直方向上,土壤剖面鹽分特征均為底聚型。水平方向上,墾利縣土壤含鹽量自縣域西部至東部逐漸升高,無棣縣和樣板區(qū)則自西南至東北逐漸升高。樣板區(qū)表層土壤含鹽量和土壤鹽漬化的月際性差異較強(qiáng),而隨土層深度增加,月際性差異逐漸趨弱。墾利縣夏季土壤含鹽量最低,春秋次之,冬季最高,但僅稍高0.1-0.3 g·kg-1;土壤鹽漬化程度表現(xiàn)為夏季向西北大幅減輕,秋季向東南大幅加重,冬季向東北小幅加重,次年春季向西南略有減輕。無棣縣土壤含鹽量則為夏季最低,冬季次之,春秋相近且最高;土壤鹽漬化程度表現(xiàn)為冬季向東北略有減輕,春季向西南略有加重,夏季向東南大幅減輕,次年秋季向西北大幅加重。另外,墾利縣和無棣縣土壤含鹽量和土壤鹽漬化程度均存在年際間差異,但差異不顯著,且隨土層深度增加,年際間差異逐漸趨弱�？h域各時期表層土壤含水量和含鹽量均呈正相關(guān),但并不顯著;春秋季相關(guān)系數(shù)大于夏冬季。(2)土壤鹽漬化影響因素分析黃河三角洲地區(qū)土壤鹽漬化的主要影響因素為氣候條件(蒸降比)、植被類型(植被覆蓋度)、離渤海(黃河)遠(yuǎn)近、地形地貌(相對高程)、表層質(zhì)地和土體構(gòu)型(土體粘粒含量)、潛水埋深、地下水礦化度和人類活動。其中,蒸降比和地下水礦化度與土壤含鹽量呈顯著正相關(guān);植被覆蓋度、離渤海遠(yuǎn)近、相對高程、土體粘粒含量和潛水埋深與土壤含鹽量呈顯著負(fù)相關(guān)。同時,土壤含鹽量受距路邊遠(yuǎn)近、不同耕作措施、地形部位等因素影響表現(xiàn)出微域規(guī)律性和復(fù)雜性。在不同土層中,各影響因子對土壤鹽漬化的作用強(qiáng)度均表現(xiàn)為地下水礦化度植被覆蓋度潛水埋深土體粘粒含量離海遠(yuǎn)近相對高程。(3)土壤鹽漬化預(yù)測模型構(gòu)建及改良利用墾利縣不同土層土壤含鹽量的主要影響因子均為地下水礦化度、植被覆蓋度、潛水埋深和土體粘粒含量。以這四個影響因子為自變量構(gòu)建了不同土層土壤含鹽量的多元線性回歸預(yù)測模型,模型的調(diào)整決定系數(shù)分別為0.7632,0.8216,0.8156和0.7727,預(yù)測值與實測值的擬合精度均大于0.78,預(yù)測分布圖的精度均大于75%,模型的精度較高,擬合效果較好,能較好的反映墾利縣春季不同土層土壤含鹽量的空間分布特征。在縣域尺度上,分別劃分了墾利縣和無棣縣的土壤鹽漬化改良利用分區(qū),根據(jù)各分區(qū)自然狀況及存在的問題,提出相應(yīng)的改良利用措施。在區(qū)域尺度上,根據(jù)“渤海糧倉”樣板區(qū)土壤水鹽運動規(guī)律,提出了不同時期土壤水鹽運動的調(diào)節(jié)模式。在微域尺度上,提出了加強(qiáng)土壤耕作管理、培肥改良土壤和改善農(nóng)田生態(tài)環(huán)境三個方面的措施。本文系統(tǒng)研究了黃河三角洲典型地區(qū)土壤鹽漬化問題,摸清了土壤水鹽動態(tài)規(guī)律及其影響因素,初步提出了土壤鹽漬化預(yù)測模型,為土壤鹽漬化的可持續(xù)利用和管理提供科學(xué)依據(jù)和技術(shù)支撐。采用野外調(diào)查、GIS與定量模型構(gòu)建相結(jié)合的方法,為鹽漬土的定量化分析提供了有效地手段。最后,根據(jù)不同尺度土壤鹽漬化的特點,提出了針對性的改良利用措施,對研究區(qū)鹽漬土的改良利用具有參考價值和指導(dǎo)意義。
[Abstract]:With the rapid development of the global economy and population growth, the contradiction between people and land become more and more prominent, the exploitation of the land resources protection and land degradation has become a hot issue of global concern. As the main types of land degradation, soil degradation has become a global ecological problem. The Yellow River Delta is one of delta China and the world's fastest reclamation, has rich land resources, is our country's important reserve land resources in the District, however, nearly 50% of the land has different degree of salinization phenomenon. At present, the system research the problem of soil salinization is still deficient, still need further discussion. This paper selects a typical Kenli county the Yellow River Delta, Wudi county and the "Bohai granary" model area as the study area, in the spring, summer, autumn and winter, the typical phase, using field survey collection 0-15 cm, 15-30 cm 30-45, cm, 45-60cm soil salinity data and 0-15 cm soil moisture data. Through sample data, statistical analysis and GIS spatial interpolation analysis, variation of soil water and salt content in model space; change dynamic of soil salinization, the time variations of soil water and salt content; qualitative analysis the quantitative analysis, and grey correlation method, the main influence factors of soil salinization; using multiple linear regression analysis, selecting the main influence factors, build soil salinity forecasting model; from the county, region and micro scale and puts forward some measures for prevention and improvement of saline soil. The main conclusions are as follows: (1) variability of soil water salt spatial in Kenli County, Wudi county and the model area of soil moisture are moderate variation. The strength of Kenli county with high water content of the soil is mainly distributed in the West The coastal area of southern the Yellow River and South Eastern Wudi County; high moisture content of the soil is mainly distributed in the northern coastal area. From February to May of the following year, yangbanqu soil moisture increased monthly variation and then decreased. Soil moisture in Kenli county and Wudi county were the highest in summer, spring and autumn time the lowest in winter, while no significant inter annual difference. Kenli County, Wudi County, the soil salt content and sample area respectively by 2.0-5.0 G - kg-1,2.0-4.5 G - kg-1 and 2.0-6.0g - kg-1. The vertical direction, soil salinity characteristics were poly type. The horizontal direction, soil salinity from Kenli county the west to the east gradually increased, Wudi county and sample area from southwest to northeast gradually increased. The difference monthly model of surface soil salinity and soil salinization is strong, and with the increase of soil depth, the monthly difference gradually weakening. The Kenli County summer Quaternary soil salt content is lowest, and highest in winter, but only slightly higher 0.1-0.3 g kg-1; soil salinization in summer to the northwest to the southeast fall sharply reduces sharply increased in winter to the northeast, slightly increased, the following spring slightly to reduce Wudi county. Soil salt content was the lowest in summer in winter, spring and autumn are similar, and the highest degree of soil salinization; winter to the northeast is slightly reduced, increased slightly to spring, summer to the southeast to the northwest the next year fall sharply reduces sharply increased. In addition, Kenli county and Wudi County, the soil salt content and soil salinization there were interannual differences, but the difference is not obviously, and with the increase of soil depth, the inter annual difference gradually weakening. The county during the period of surface soil moisture and salt content were positively correlated, but not significant; in spring and autumn than in summer and winter. The correlation coefficient (2) saline soil The main influence factors of influencing factors of soil salinization in the Yellow River Delta as the climatic conditions (evaporation precipitation ratio), vegetation types (vegetation coverage), from Bohai (the Yellow River) and topography (relative elevation), surface texture and soil (soil clay content), groundwater depth, groundwater salinity and human activities. Among them, evaporation precipitation ratio and groundwater mineralization and soil salt content showed a significant positive correlation; vegetation coverage, distance from Bohai, relative elevation, soil clay content and groundwater depth and soil salinity has significant negative correlation. At the same time, the soil salt content under different distance from the side of the road, farming measures, factors affecting the topographic position showed the micro domain regularity and complexity. In different soil, effects of these influencing factors on soil salinization showed groundwater mineralization degree of vegetation coverage of phreatic water from the sea near the soil clay content The relative elevation (3). Soil salinization forecast model and modified factor utilization in Kenli County Soil mainly affects the soil salinity are the mineralization degree of groundwater, vegetation coverage, groundwater depth and soil clay content. With these four factors as independent variables to construct a linear soil salt content in different layers of regression prediction model, adjustment coefficient of determination of model 0.7632,0.8216,0.8156 and 0.7727 respectively, the predictive value of the fitting precision and the measured value is greater than 0.78, the prediction accuracy of distribution was greater than 75%, the model precision is high, the fitting effect is good, can better reflect the Kenli County in the spring soil salinity distribution in spatial characteristics. The county scale, the author divided the improvement of soil salinization in Kenli county and Wudi County by partition, each partition according to the natural conditions and the existing problems, put forward corresponding improvement measures by At the regional scale, according to the movement of soil water and salt Bohai granary "model area, puts forward the regulation mode of soil water and salt movement in different periods. In micro scale, put forward to strengthen the management of soil tillage, fertilization and soil improvement of farmland ecological environment measures in three aspects. This paper studies in the Yellow River delta soil salinization problems, find out the factors of the dynamic rule of soil water and salt and its influence, proposed soil salinization forecast model, provide scientific basis and technical support for the sustainable utilization of soil salinization and management. Based on the field investigation, the construction method of the combination of GIS and quantitative model, provides effective means for quantitative analysis of saline soil. Finally, according to the characteristics of soil salinization in different scale, proposed the use of measures for improvement, improvement of saline soil in the study area with ginseng The value and guiding significance of the examination.

【學(xué)位授予單位】：山東農(nóng)業(yè)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2017
【分類號】：S156.4
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本文編號：1376035