Development and evaluation of the SoilClim model for water balance and soil climate estimates

The newly developed SoilClim model is introduced as a tool for estimates of reference (ETo) and actual (ETa) evapotranspiration, presence of snow cover, soil temperature at 0.5 m depth and the soil moisture course within two defined layers. It enables one to determine the soil moisture and temperature regimes according to the United States Department of Agriculture (USDA) soil taxonomy. SoilClim works with daily time steps and requires maximum and minimum air temperature, global solar radiation, precipitation, vapor pressure and wind speed as meteorological inputs as well as basic information about the soil properties and vegetation cover. The behavior of SoilClim was assessed using observations at 5 stations in central Europe and 15 stations in the central U.S. The modeled ETo was compared with atmometers so that the coefficient of determination (R²) was 0.91 and root mean square error (RMSE) was 0.53 mm. The estimated ETa was compared against eddy-covariance and Bowen ratio measurements (R² varied from 0.74 to 0.80; RMSE varied from 0.49 to 0.58 mm). The soil temperature (at 0.5 m depth) was estimated with good accuracy (R² varied from 0.94 to 0.97; RMSE varied from 1.23 °C to 2.95 °C). The ability of the SoilClim model to mimic the observed soil water dynamics was carefully investigated (relative root mean square error rRMSE varied from 2.8% to 34.0%). The analysis conducted showed that SoilClim gives reasonable estimates of evaluated parameters at a majority of the included stations. Finally, a spatial analysis of soil moisture and temperature regimes (according to USDA) within the region of the Czech Republic and the northern part of Austria under present conditions was conducted and diagnosed the appearance of Perudic, Subhumid Udic, Dry Tempudic (the highest frequency), Wet Tempustic and Typic Tempustic. The simulated mean soil temperature (0.5 m depth) varied from less than 7.0 °C to 11.0 °C throughout this region. Based on these results, the SoilClim model is a useful and suitable tool for water balance and soil climate assessment on local and regional scales.     

Comparison of three dielectric moisture sensors for measurement of water in saline sandy soil

The number of sensor types available for measuring soil water content has increased but investigations to compare their performance in saline soils needs clarification. In this study the performance of commercially available, low-cost soil moisture sensors [time domain reflectometry (TDR), PR1 and WET], all measuring changes in the dielectric constant of the soil water, was evaluated under laboratory conditions in a saline sandy soil. The three sensors were also tested in the same sandy soil growing drip irrigated sorghum ( Sorghum bicolor L. cv. Moench) in a greenhouse. Plants were irrigated daily with either saline water (ECw: 9.4 dS/m) or fresh water (0.11 dS/m). The volume of irrigation was equivalent to 100% of the pan evaporation. The results showed that measurement accuracy was strongly dependent on the salinity of the soil. The PR1 sensor overestimated volumetric water content ( θ ) when the salinity level exceeded 4 dS/m [root mean square of the standard error (RMSE) = 0.009 cm³/cm³]. The WET sensor significantly overestimated θ irrespective of the salinity level (RMSE = 0.014 cm³/cm³). The TDR sensor estimated θ with more accuracy (RMSE = 0.007   cm³/cm³) and thus can be considered as more reliable than the other two sensors. The calibrations were strongly affected by the salinity level of the water, so we recommend that calibration equations are modified to take account of salinity.     

利用时域反射仪测定饱和砂土中非水相液体

利用时域反射技术,以饱和砂土和菜籽油、机油为研究对象,室内模拟研究了非水相液体(NAPLs,nonaqueous phase liquids)污染土壤的介电常数和电导率的变化规律,确定了饱和砂土中NAPLs含量的预测模型。研究表明:1饱和砂土中体积含油量在0~0.05 cm~3/cm~3时,土壤介电常数并无显著变化;随着NAPLs体积含量的进一步增加,介电常数呈线性减小趋势;土壤体积质量和NAPLs类型对相同饱和度的土壤介电常数未产生影响。2饱和土壤的电导率与NAPLs含量存在良好的线性负相关关系(R2=0.96);土壤体积质量对相同饱和度的土壤电导率未产生影响。3混合介电模型(a=0.5)高估了饱和砂土中NAPLs含量,平均RMSE为0.038 cm~3/cm~3;参数a调整为0.52后,混合介电模型提高了预测精度,比原混合介电模型(a=0.5)预测精度可以提高23.2%。本研究结果表明可利用时域反射技术监测污染土壤的介电常数与电导率并测定饱和土壤中NAPLs的含量。     

TDR法、中子法、重量法测定土壤含水量的比较研究

对用ＴＤＲ法、中子法和重量法测得的土壤水分含量观测值的比较结果表明,随着土壤深度和测量时间的变化,中子法的平均测定误差为３．７６％,ＴＤＲ法为３．５９％。并且这２种方法的土壤水含量观测值的时空变化和重量法具有相同的趋势。因此,用ＴＤＲ法测定土壤含水量与用中子法是同样可靠的。     

扬州地区TDR法田间测定不同土壤含水量的标定

使用美国Spectrum TDR 100便携式水分测定仪,在扬州地区不同土壤,找出TDR法和烘干法测定土壤含水量之间的关系。通过试验证明,容重在1.3 g/cm3处TDR测定值接近真实值,容重越小或越大,其偏差就越大。粘粒含量为0~200 g/kg,砂粒含量在300~500 g/kg范围内,TDR测定值接近于烘干法。利用TDR测定土壤水分,砂土和壤土可以不用调整,而粘壤土和粘土要进行系数换算,粘壤土的测定结果要除以1.18,粘土的测定结果要除以1.44。     

TDR在测量农田土壤水分中的室内标定

给出了一种较简便、准确的时域反射仪(TDR)室内标定方法,该方法工作量小,克服了田间土壤水分空间变异的影响,更适用于粘壤土质的TDR标定。通过对昆山地区粘壤土质的实例标定发现,TDR测量值较烘干法明显偏低,绝对偏差范围0.02~0.09 cm3/cm3,相对偏差随着土壤含水量的减小有增加趋势。但TDR的测量值与真实值之间有较高的相关性(R2=0.9837,P<0.001),可以用一个简单的线形函数进行校正,校正后的TDR测量值中将有98.4%的值接近土壤含水量真实值,说明该校正公式可以作为昆山地区进行TDR校正的参考。     

晋西黄土区土壤水分空间异质性的地统计学分析

土壤水分的空间分布存在着一定的随机性和结构性特征,而对不同尺度土壤水分空间变异规律的研究是土壤水分研究中的热点问题.该文通过2004—2005年对山西吉县蔡家川小流域不同取样尺度（20 m×20 m、2 m×2 m） 391个样点土壤水分的测定（TDR土壤水分测定法）,使用地统计学方法进行土壤水分的空间异质性分析,以区域化变量理论为基础,以变异函数为主要工具,以克立格法为基本方法进行土壤水分异质性研究.结果表明:研究区土壤水分的理论变异模型为球状模型,20 m×20 m网格取样变程为494.16 m,2 m×2 m网格取样变程为27.4 m,试验区土壤水分的变异属于中等程度的变异;通过克立格插值估计,整个研究区坡面土壤水分平均值为10.94%（0～30 cm）和11.88%(30～60 cm).      

土壤水分时域反射仪(TDR)自制探头的校正与应用

根据TDR工作原理制作了TDR探头,并对其进行了室内标定,结果表明,介电常数的平方根(Ka)与体积含水量(,θ%)有良好的线性相关(R2=0.995)。并在田间与中子仪测定结果进行了对比,结果表明,平均绝对偏差为0.17%,平均相对偏差为8.58%,说明TDR自制探头可以在黄土高原地区推广应用。