本文關(guān)鍵詞： 空間變異 尺度效應(yīng) 多重分形 HYDRUS模型 灌水模式　出處：《內(nèi)蒙古農(nóng)業(yè)大學》2017年碩士論文　論文類型：學位論文

【摘要】：在河套灌區(qū)引黃水量大幅減少的背景下,對河套灌區(qū)土壤空間變異性及水鹽模擬進行研究,對工農(nóng)業(yè)經(jīng)濟發(fā)展、水資源利用及生態(tài)環(huán)境等各個方面都具有重大的現(xiàn)實意義。本文以河套灌區(qū)永濟灌域和隆勝試驗區(qū)兩個尺度為背景,分析土壤顆粒組成、含水率、EC值及有機質(zhì)含量的空間變異性,進而通過土壤水鹽運移模型模擬土壤水鹽運移過程,揭示不同質(zhì)地土壤水鹽動態(tài)變化規(guī)律,優(yōu)化灌水調(diào)控模式,研究結(jié)果可為灌區(qū)管理決策提供理論依據(jù)。研究表明,兩個尺度下,各指標的變異系數(shù)介于15.56%～133.05%之間,除隆盛試驗區(qū)尺度的40～60cm 土層的粘粒含量和0～100cm所有土層的砂粒含量呈強變異性外,其它屬中等變異性;在同一尺度下,土壤粘粒含量、粉粒含量及有機質(zhì)含量的空間變異性隨著土層深度的增加而增加,砂粒含量、含水率及EC值則反之;在不同尺度的同一土層深度,土壤含水率及有機質(zhì)含量的空間變異性為永濟灌域尺度大于隆勝試驗區(qū)尺度,其它則反之。地統(tǒng)計結(jié)果顯示,永濟灌域尺度20～40cm 土層的粉粒含量、砂粒含量不存相關(guān)性,其余不同尺度各個土層的土壤粘粒、粉粒、砂粒含量、含水率及有機質(zhì)含量屬強烈的空間相關(guān)性和中等空間相關(guān)性。土壤EC值在隆勝試驗區(qū)尺度呈較強烈的空間相關(guān)性,在永濟灌域尺度呈弱空間相關(guān)性,40～60cm 土層無空間相關(guān)性。各指標的空間相關(guān)距離皆隨著研究尺度的增大而增大。多重分形分析結(jié)果表明,各指標不同尺度不同土層均具明顯的多重分形特征;土壤粘粒含量在隆勝試驗區(qū)尺度全部土層及永濟灌域尺度40～60cm 土層的空間分布是以小數(shù)值數(shù)據(jù)為主,其它土層反之;土壤粉粒和砂粒含量在兩個尺度不同土層的空間分布均以大數(shù)值數(shù)據(jù)為主;含水率在永濟灌域尺度0～20cm、20～40cm、40～60cm及80～100cm 土層及隆勝試驗區(qū)尺度0～20cm、20～40cm 土層的空間分布以大數(shù)值數(shù)據(jù)為主,而其它土層反之;EC值在隆勝試驗區(qū)尺度80～100cm 土層及永濟灌域尺度20～40cm 土層的空間分布以大數(shù)值數(shù)據(jù)為主,其它土層反之;有機質(zhì)含量僅在隆勝試驗區(qū)尺度上0～20cm、20～40cm及80～100cm 土層的空間分布以小數(shù)值數(shù)據(jù)為主,其它土層和永濟灌域尺度全部土層均反之。數(shù)值模擬結(jié)果表明,砂壤土的適宜灌水量在玉米生育期為300 mm,秋澆期為150mm;粉砂壤土的適宜灌水量在玉米生育期為330 mm,秋澆期為180mm;粉土的適宜灌水量在玉米生育期為360mm,秋澆期為210mm。
[Abstract]:The spatial variability of soil and the simulation of water and salt in Hetao Irrigation area were studied under the background of large reduction of water diversion from the Yellow River in Hetao Irrigation area, and the economic development of industry and agriculture was also studied. The utilization of water resources and ecological environment are of great practical significance. Based on the two scales of Yongji Irrigation region and Longsheng Experimental area in Hetao Irrigation District, this paper analyzes the composition of soil particles and water content. The spatial variability of EC value and organic matter content, and then simulate the process of soil water and salt migration through soil water and salt migration model, reveal the dynamic changes of soil water and salt in different texture, and optimize irrigation control model. The results can provide a theoretical basis for the management decision of irrigation district. The results show that the coefficient of variation of each index is between 15.56% and 133.05%. Except for the strong variability of clay content in 40cm-60cm soil layer and the sand content in all soil layers of 0 ~ 100cm, the others belong to moderate variability. At the same scale, the spatial variability of soil clay content, silt content and organic matter content increased with the increase of soil depth, while the sand content, moisture content and EC value were reversed. At the same soil depth of different scales, the spatial variability of soil moisture content and organic matter content is that the scale of Yongji irrigation area is larger than the scale of Longsheng experimental area, and the other is the opposite. The geostatistical results show that. There is no correlation between the silt content and the sand content in the irrigation area of Yongji irrigation area, but the clay, silt and sand content in the other soil layers of different scales. Soil EC values showed strong spatial correlation in the scale of Longsheng experimental area and weak spatial correlation in the scale of Yongji irrigation area. There is no spatial correlation in 400-60cm soil layer. The spatial correlation distance of each index increases with the increase of research scale. Multifractal analysis results show that. Each index has obvious multifractal characteristics in different scales and different soil layers. The spatial distribution of soil clay content in all soil layers in Longsheng experimental area and in 4060 cm soil layer in Yongji irrigation area is dominated by small numerical data, whereas the other soil layers are not. The spatial distribution of soil silt and sand content in two different soil layers is dominated by large numerical data. The water content is at the scale of 0 ~ 20 cm, 20 ~ 40 cm, 40 ~ 60 cm and 80 ~ 100 cm soil layer in Yongji irrigation area, and the scale is 0 ~ 20 cm in Longsheng experimental area. The spatial distribution of 20 ~ 40cm soil layer is dominated by large numerical data, while other soil layers are not. The spatial distribution of EC value in the scale of 80 ~ 100cm soil layer in Longsheng experimental area and 204cm soil layer in Yongji irrigation area is dominated by large numerical data, whereas the other soil layers are inversely distributed. The spatial distribution of organic matter content on the scale of 0 ~ (20) cm ~ (20) ~ (20) cm ~ (20) ~ (40) cm and 80 ~ (100) cm soil layer is dominated by small numerical data. The numerical simulation results showed that the suitable irrigation amount of sandy loam was 300 mm in maize growth period and 150 mm in autumn. The suitable irrigation amount of silty loam was 330 mm in maize growth period and 180 mm in autumn period. The suitable irrigation amount of silt was 360 mm in maize growth period and 210 mm in autumn.
【學位授予單位】：內(nèi)蒙古農(nóng)業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：S156.4;S274

【參考文獻】

相關(guān)期刊論文 前10條

1 解雪峰;濮勵杰;朱明;許艷;王小涵;徐彩瑤;;土壤水鹽運移模型研究進展及展望[J];地理科學;2016年10期

2 任杰;沈振中;楊杰;李琛亮;高金強;;基于HYDRUS模型低溫水入滲下土壤水熱運移模擬[J];干旱區(qū)研究;2016年02期

3 程光遠;史海濱;李瑞平;王成剛;王智超;于洪;王佐奎;;基于ISAREG模型的大豆半固定噴灌灌溉制度優(yōu)化研究[J];灌溉排水學報;2015年12期

4 徐存東;聶俊坤;劉輝;連海東;翟星;;基于HYDRUS?2D的田間土壤水鹽運移過程研究[J];節(jié)水灌溉;2015年09期

5 屈忠義;楊曉;黃永江;杜斌;楊俊林;;基于Horton分形的河套灌區(qū)渠系水利用效率分析[J];農(nóng)業(yè)工程學報;2015年13期

6 張劉東;王慶明;;咸水非充分灌溉對土壤鹽分分布的影響及SWAP模型模擬[J];節(jié)水灌溉;2015年07期

7 馬金慧;楊樹青;史海濱;丁雪華;韓文光;杜麗云;;鹽漬化灌區(qū)水鹽田間尺度時空分布及關(guān)聯(lián)分析[J];西北農(nóng)林科技大學學報(自然科學版);2015年08期

8 郝遠遠;徐旭;任東陽;黃權(quán)中;黃冠華;;河套灌區(qū)土壤水鹽和作物生長的HYDRUS-EPIC模型分布式模擬[J];農(nóng)業(yè)工程學報;2015年11期

9 范嚴偉;黃寧;馬孝義;;層狀土垂直一維入滲土壤水分運動數(shù)值模擬與驗證[J];水土保持通報;2015年01期

10 李遠;鄭旭榮;王振華;張金珠;姜國軍;孟憲磊;;基于Hydrus-1D的土壤水鹽運移數(shù)值模擬[J];中國農(nóng)學通報;2014年35期

相關(guān)博士學位論文 前4條

1 張娜;鹽漬化灌區(qū)多尺度土壤水力特征參數(shù)空間變異規(guī)律及轉(zhuǎn)換技術(shù)研究[D];內(nèi)蒙古農(nóng)業(yè)大學;2016年

2 馬金慧;基于農(nóng)田水土環(huán)境限制因子的河套灌區(qū)引黃水量閾值模擬研究[D];內(nèi)蒙古農(nóng)業(yè)大學;2014年

3 李亮;基于遙感技術(shù)與HYDRUS-1D模型河套灌區(qū)鹽荒地水鹽運移規(guī)律研究[D];內(nèi)蒙古農(nóng)業(yè)大學;2011年

4 魏占民;干旱區(qū)作物—水分關(guān)系與田間灌溉水有效性的SWAP模型模擬研究[D];內(nèi)蒙古農(nóng)業(yè)大學;2003年

相關(guān)碩士學位論文 前7條

1 余永富;土壤—作物系統(tǒng)水動力學數(shù)值模擬[D];浙江大學;2016年

2 李彥;節(jié)水灌溉條件下河套灌區(qū)土壤水鹽動態(tài)的SWAP模型分布式模擬預(yù)測[D];內(nèi)蒙古農(nóng)業(yè)大學;2012年

3 張志杰;河套灌區(qū)灌溉入滲補給地下水系數(shù)及引黃水量閾值初步研究[D];內(nèi)蒙古農(nóng)業(yè)大學;2011年

4 葉志剛;河套灌區(qū)區(qū)域微咸水灌溉模式的研究[D];內(nèi)蒙古農(nóng)業(yè)大學;2009年

5 寇薇;內(nèi)蒙古河套灌區(qū)土壤水鹽空間變異性研究[D];西北師范大學;2008年

6 舒建英;中大尺度下丘陵區(qū)土壤肥力因子的空間表達研究[D];四川農(nóng)業(yè)大學;2006年

7 高海霞;多重分形的算法研究及應(yīng)用[D];成都理工大學;2004年

，

本文編號：1477506