粉煤灰充填复垦土壤理化性质分布特征及其对覆土厚度响应
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摘要
以淮南市平圩电厂粉煤灰堆场复垦区为研究对象,采用经典统计和地统计学相结合的方法,从点和区域、水平与垂直等多维角度分析了不同覆土厚度下的复垦土壤主要理化性质分布特征,旨在揭示粉煤灰充填基质下复垦土壤理化性质分布特征及其与覆土厚度之间的响应关系。结果表明,随着覆土厚度的增加,土壤含水量均值呈现先增后减的趋势,各覆土厚度下土壤含水量基本在20%以上,覆土厚度20～30cm的土壤含水量最大,达到31.11%。在一定的覆土厚度下,含水量在粉煤灰重构剖面中间会出现一个突变层次,在土—灰界面将产生土壤水分的聚集。不同覆土厚度下表层土壤的容重出现明显的差异,随着覆土厚度的增加,土壤容重整体呈现上升趋势,覆土厚度40～60 cm时,土壤表层平均土壤容重达到1.75 g·cm-3,复垦后出现了不同程度的板结现象。不同覆土厚度下砂、粉和黏粒含量差异明显,总体上与该地区非重构土壤相似,基本属于粉砂质壤土。粉煤灰充填复垦后土壤颗粒组成由粉煤灰、覆土土源和覆土方式共同决定的,泥浆泵法覆土在不同水平间土壤颗粒组成差异较为明显。随着覆土厚度的增加,不同层次的有机质含量都有不同程度的提升,且提升程度与覆土厚度呈正相关。基于经验贝叶斯克里格法的复垦土壤含水量、容重、粉砂和有机质含量的RMSE分别为1.72、1.01、1.57和0.85;MSDR值分别为2.12、1.32、2.72和0.62,RMSE较小,预测精度较高,MSDR比较接近1,模型拟合效果较好。综合考虑各理化指标对覆土厚度的响应特征,冬小麦-夏玉米种植模式下覆土厚度40～50cm较为合理。经验贝叶斯克里格法比较适合粉煤灰充填复垦土壤理化指标空间预测。
The reclamation area of Pingwei Power Plant in Huainan city was utilized as the research object. The paper analyzed distribution characteristics of the key physical and chemical properties of reclamation soil under different covering thickness from the point and area, horizontal and vertical aspects using classical statistics and empirical Bayes Kriging(EBK) method. The aim of the article was to reveal the distribution characteristics of the key elements of soil fertility under reclamation with fly ash filling and its response to the thickness of covering soil. The results showed that with the increase of soil thickness, the soil moisture content increased first and then decreased, which was above 20% for different covering soil thickness and reached 31.11% for 20-30 cm. Under certain overburden thickness, there will be a mutation level in the middle of the reclaimed profile of fly ash, and the soil moisture will be aggregated at the soil ash interface. With the increase of the soil thickness, soil bulk density increased, soil thickness of 40-60 cm, the average soil bulk density was 1.75 g·cm-3. After reclamation, there were different degrees of knot phenomenon. The difference of sand, silt and clay content was obvious under different soil thickness, which was generally similar to that of the non-reconstructed soil in the area, and basically belongs to silty loam. The composition of soil particles was determined by fly ash, overlying soil source and the way of overlying soil after the reclamation of fly ash. The soil particle composition of soil with mud pump method was more obvious at different levels. With the increase of soil thickness, the organic matter content of different levels had been improved, and the degree of improvement was positively correlated with the thickness of soil cover. The RMSE based on the empirical Bayes Kriging method was 1.72, 1.01, 1.57 and 0.85, respectively, and the MSDR values were 2.12, 1.32, 2.72, 0.62, RMSE were smaller, the prediction accuracy was higher, the MSDR was close to 1, and the model fitting effect was better. Considering the response characteristics of each physical and chemical index to the overburden thickness, the thickness of soil 40-50 cm under winter wheat-summer maize planting pattern was more reasonable. Empirical Bayes Kriging method was more suitable for spatial prediction of physical and chemical indexes of fly ash reclamation soil.
The reclamation area of Pingwei Power Plant in Huainan city was utilized as the research object. The paper analyzed distribution characteristics of the key physical and chemical properties of reclamation soil under different covering thickness from the point and area, horizontal and vertical aspects using classical statistics and empirical Bayes Kriging(EBK) method. The aim of the article was to reveal the distribution characteristics of the key elements of soil fertility under reclamation with fly ash filling and its response to the thickness of covering soil. The results showed that with the increase of soil thickness, the soil moisture content increased first and then decreased, which was above 20% for different covering soil thickness and reached 31.11% for 20-30 cm. Under certain overburden thickness, there will be a mutation level in the middle of the reclaimed profile of fly ash, and the soil moisture will be aggregated at the soil ash interface. With the increase of the soil thickness, soil bulk density increased, soil thickness of 40-60 cm, the average soil bulk density was 1.75 g·cm-3. After reclamation, there were different degrees of knot phenomenon. The difference of sand, silt and clay content was obvious under different soil thickness, which was generally similar to that of the non-reconstructed soil in the area, and basically belongs to silty loam. The composition of soil particles was determined by fly ash, overlying soil source and the way of overlying soil after the reclamation of fly ash. The soil particle composition of soil with mud pump method was more obvious at different levels. With the increase of soil thickness, the organic matter content of different levels had been improved, and the degree of improvement was positively correlated with the thickness of soil cover. The RMSE based on the empirical Bayes Kriging method was 1.72, 1.01, 1.57 and 0.85, respectively, and the MSDR values were 2.12, 1.32, 2.72, 0.62, RMSE were smaller, the prediction accuracy was higher, the MSDR was close to 1, and the model fitting effect was better. Considering the response characteristics of each physical and chemical index to the overburden thickness, the thickness of soil 40-50 cm under winter wheat-summer maize planting pattern was more reasonable. Empirical Bayes Kriging method was more suitable for spatial prediction of physical and chemical indexes of fly ash reclamation soil.
引文
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[21]朱祖祥.土壤学[M].北京:农业出版社, 1983.
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[24]张世文,王胜涛,刘娜,等.土壤质地空间预测方法比较[J].农业工程学报, 2011, 27(1):332-339.
[25]徐良骥,许善文,严家平,等.基于粉煤灰基质充填覆土复垦的最佳覆土厚度[J].煤炭学报, 2012, 37(z2):485-488.
[26]王长垒,严家平,陈孝杨.粉煤灰场复垦地肥力状况及对土壤理化性质的影响[J].湖北农业科学,2013,52(6):1273-1276.
[27]杨修芳.粉煤灰复垦地土壤养分及重金属分布影响因素分析[D].淮南:安徽理工大学, 2011.
[2]SHUKLA M K, LAL R, UNDERWOOD J, et al. Physical and hydrological characteristics of reclaimed minesoils in southeasternohio[J].SoilSciSocAmJ,2004,68(4):1352-1359.
[3]HINOJOSAMB,CARREIRAJA,GARCíA-RUíZR,et al. Soil moisture pre-treatment effects on enzyme activities asindicatorsofheavymetal-contaminatedandreclaimed soils[J]. Soil Biol Biochem, 2004, 36(10):1559-1568.
[4]KRüMMELBEINJ,RAABT.Developmentofsoil physicalparametersinagriculturalreclamationafter brown coal mining within the first four years[J]. Soil Till Res, 2012, 125:109-115.
[5]卞正富,张国良.矿山复垦土壤生产力指数的修正模型[J].土壤学报, 2000, 37(1):124-130.
[6]胡振琪,付梅臣,何中伟.煤矿沉陷地复田景观质量评价体系与方法[J].煤炭学报, 2005, 30(6):695-700.
[7]何书金,苏光全.矿区废弃土地复垦潜力评价方法与应用实例[J].地理研究, 2000, 19(2):165-171.
[8]胡振琪,赵艳玲,姜晶,等.土地整理复垦项目验收方案研究[J].农业工程学报, 2005, 21(6):59-63.
[9]樊文华,白中科,李慧峰,等.复垦土壤重金属污染潜在生态风险评价[J].农业工程学报, 2011, 27(1):348-354.
[10]徐良骥,许善文,杨秀芳,等.粉煤灰充填复垦地理化特性与重金属分布特征研究:以淮南洛河电厂粉煤灰复垦地为例[J].农业环境科学学报,2012,31(12):2352-2360.
[11]张世文,叶回春,王来斌,等.景观高度异质区土壤有机质时空变化特征分析[J].农业机械学报,2013,44(12):105-113.
[12]胡振琪,戚家忠,司继涛.粉煤灰充填复垦土壤理化性状研究[J].煤炭学报, 2002, 27(6):639-643.
[13]樊雯.基于粉煤灰充填复垦土地的复垦效应研究[D].淮南:安徽理工大学, 2010.
[14]GRIBOVA,KRIVORUCHKOK.Newflexiblenon-parametricdatatransformationfortrans-GaussianKriging[M]//GRIBOVA,KRIVORUCHKO K.Geostatistics Oslo2012.Dordrecht:Springer Netherlands, 2012:51-65.
[15]ERDEMG,?A?DA?SA?IR,CANO?LUMC,etal.Comparison of empirical Bayesian Kriging and geo-anfis methodsforinterpolatinghydraulicheadinakarstalluvium[C]//International Congress on Environmental Modelling and Software. Toulouse:2016.
[16]MWENDA K M. Quantifying uncertainty of spatial interpolationoffineparticulatematterinsmallregionsusingempiricalBayesianKriging[C]//4thInternationalChemicaland EnvironmentalConference(ICEEC2013-14).KualaLumpur:2014.
[17]KRIVORUCHKOK.Spatialstatisticaldataanalysisfor GIS users[M]. Redlands:Esri Press, 2011.
[18]COBURN T C. Geostatistics for natural resources evaluation[M]. Oxford:Oxford University Press, 2000:437-438.
[19]ABZALOV M. Introduction to Geostatistics[M]//DILEK Y,PIRAJNOF,WINDLEYBF.ModernApproachesin SolidEarthSciences.NewYork:SpringerInternational Publishing, 2016:233-237.
[20]ZHANGSW,SHENCY,CHENXY,etal.SpatialinterpolationofsoiltextureusingcompositionalKriging andregressionKrigingwithconsiderationofthecharacteristicsofcompositionaldataandenvironmentvariables[J]. J Integr Agr, 2013, 12(9):1673-1683.
[21]朱祖祥.土壤学[M].北京:农业出版社, 1983.
[22]徐建明.土壤质量指标与评价[M].科学出版社, 2010.
[23]李志洪,王淑华.土壤容重对土壤物理性状和小麦生长的影响[J].土壤通报, 2000, 31(2):55-57.
[24]张世文,王胜涛,刘娜,等.土壤质地空间预测方法比较[J].农业工程学报, 2011, 27(1):332-339.
[25]徐良骥,许善文,严家平,等.基于粉煤灰基质充填覆土复垦的最佳覆土厚度[J].煤炭学报, 2012, 37(z2):485-488.
[26]王长垒,严家平,陈孝杨.粉煤灰场复垦地肥力状况及对土壤理化性质的影响[J].湖北农业科学,2013,52(6):1273-1276.
[27]杨修芳.粉煤灰复垦地土壤养分及重金属分布影响因素分析[D].淮南:安徽理工大学, 2011.