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机构地区:[1]土肥资源高效利用国家工程实验室,国家缓控释肥工程技术研究中心,山东农业大学资源与环境学院,山东泰安271018 [2]国土资源部土地整治重点实验室,北京100035
出 处:《土壤》2015年第4期812-818,共7页Soils
基 金:国家科技支撑计划项目(2009BAC55B07,2011BAD11B01,2011BAD11B02);国家“948”重点项目(2011-G30)资助
摘 要:针对饱和泥浆调制时饱和点的不确定性及其电导率测定的不稳定性等问题,为了统一和准确地表征暗管改碱的盐碱土盐渍化程度,采用室内化验与统计分析的方法,系统比较研究了饱和泥浆所需水量与饱和土壤溶液所需水量及其电导率和全盐与土水比1︰5、1︰2.5、1︰1、1︰0.5系列的相关和换算关系。研究结果表明:在黄河三角洲盐碱土(氯化物类型)区,可采用通过计算土壤孔隙度得到的饱和土壤溶液含水量来定量确定原来定性判定饱和点的饱和泥浆含水量,以饱和土壤溶液电导率可完全代替饱和泥浆电导率;饱和泥浆电导率数值和全盐含量均不是土水比1︰5、1︰2.5、1︰1、1︰0.5系列中的最高值,但均与其存在极显著的相关关系,饱和泥浆电导率与土水比1︰5土壤浸提液的电导率、饱和泥浆全盐含量与土水比1︰0.5全盐含量相关性最高,可分别用最佳拟合回归函数模型进行换算:一元线性函数模型Ece=2.042 8×EC1︰5+0.089 5、一元二次函数模型Tse=0.064 1×(TS1︰0.5)2?0.059×TS1︰0.5+0.397 9。To overcome the uncertainty of the saturation point and the measurement instability of the electrical conductivity of saturated soil paste and to represent consistently and accurately the salinity degree of saline soil improved by subsurface drainage, this study systematically compared that the water demand between saturated soil paste and saturated soil solution, the correlation and conversion of electrical conductivity (EC) and soil total salt content (TS) between saturated soil paste and saturated soil solutions under different soil/water ratios (1 : 5, 1 : 2.5, 1 : 1 and 1 : 0.5) with chemical analysis and statistical analysis. The results showed that the water demand of saturated soil paste whose saturated point was qualitatively determined originally could be quantitatively determined by calculating soil porosity for the water demand of saturated soil solution of saline-alkali soils (chloride type soil) in the Yellow River delta. EC of saturated soil paste could be replaced completely with EC of saturated soil solution. Neither EC nor TS was the highest value in the series of different soil/water ratios, but there was significant correlation between them. EC correlation were highest between saturated soil paste and saturated soil solution under 1 : 5 soil/water ratio as well as TS correlation between saturated soil paste and saturated soil solution under 1 : 0.5 soil/water ratio, which could be respectively converted with the best-fit regression function models: ECe = 2.042 8× EC1: 5 + 0.089 5 and TSe = 0.064 1 ×(TS1: 0.5)2- 0.059 ×TS1:0.5 + 0.397 9.
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