时域反射仪(TDR)测定土壤含水量标定曲线评价与方案推荐

时域反射仪(Time Domain Reflectometry)可用于室内和田间快速、准确、自动测定土壤含水量,是目前应用最广泛的土壤含水量测定方法之一。适宜的土壤含水量标定曲线(即土壤表观介电常数和土壤含水量之间的关系)是TDR准确测定土壤含水量的关键。目前文献中存在大量的土壤含水量标定曲线,但尚未有研究对这些标定曲线进行系统的验证和分析评价。因此,它们的准确性和适用范围尚不明晰,严重影响到与土壤含水量测定相关的研究。通过查阅大量国内外文献,收集整理了一系列土壤含水量标定曲线的经验公式(19个)和半经验半物理模型(5个),并利用大量的文献实测数据对其进行综合评价。同时运用均方根差(RMSE),平均误差(AD),纳什效率系数(NSE)等三个指标对比分析和评价这些标定曲线的准确性和可靠性。研究结果表明:经验公式中Topp、Roth(1992)2、Jacobosen、Yoshikawa2、Alharathi模型和半经验模型中Malicki1公式及其修订模型综合性能较好。研究成果可为利用TDR准确测定土壤含水量及土壤含水量标定曲线的选择提供参考和指导。

一种新的土壤冻融特征曲线模型

土壤冻融特征曲线(SFTC)可以描述冻融过程中未冻水含量随负温的变化关系。准确刻画土壤冻融特征曲线对土壤的冻融过程及相关的水热耦合运移研究至关重要。以往研究中土壤冻融特征曲线适用范围较窄,无法满足实际需要。通过类比水分特征曲线,考虑初始含水量和溶质浓度对未冻水含量的影响,提出了一种新的冻融特征曲线模型,经广泛的文献数据验证表明,新模型能准确拟合观测数据,平均纳什效率系数高于0.95。与另外五种土壤冻融特征曲线模型相比,新模型在不同质地、初始含水量、溶质含量的土壤中表现良好。此外,敏感性分析显示,影响模型性能的主要因素为土壤自身物理特性、土壤溶质浓度以及残余水含量。新模型及研究结果有助于更好地理解土壤冻融过程中的水热传输过程,可为气候变化条件下冻融区生产建设和环境研究奠定坚实的理论基础,并为寒区工程相关数值模拟提供参考。

The effects of aerated irrigation on soil respiration, oxygen, and porosity

To ameliorate soil oxygen deficiencies around subsurface drip irrigation(SDI) drippers, aerated irrigation(AI) was introduced to supply aerated water to the soil through venturi installed in the SDI pipeline. The objectives of this study were to assess the effects of AI on soil respiration(SR), air-filled porosity(AFP), soil temperature(ST), and oxygen concentrations(OCC). Total soil respiration(TSR), biological activity temperature index(BAT), and soil oxygen consumption(OCS) based on SR, ST, and OCC, respectively, were subsequently calculated to explore the relationships between TSR, BAT, OCS, OCC, and AFP. Greenhouse-based experiments included two treatments: AI and unaerated SDI(CK), during the tomato growing season in the fall of 2015. The results showed that compared with CK, AI treatment significantly increased OCC and AFP(by 16 and 7.4%, respectively), as well as TSR and OCS(by 24.21 and 22.91%, respectively)(P<0.05). Mean fruit yield with AI treatment was also 23% higher(P<0.05) than that with CK. When BAT was controlled, partial correlations between TSR, OCS, OCC, and AFP were all significant in the AI treatment but not in the CK treatment. TSR was more sensitive to the interaction effects of OCC, OCS, AFP, and BAT under the AI treatment. Thus, the significantly increased TSR with AI appeared to be due to the favorable soil aeration conditi ons(higher OCC and AFP). Furthermore, the improvements in soil aeration conditions and respiration with AI appeared to facilitate the improvement in fruit yields, which also suggests the economic benefits of AI.

Determination of critical nitrogen dilution curve based on leaf area index for winter wheat in the Guanzhong Plain, Northwest China

Excessive use of nitrogen (N) fertilizers in agricultural systems increases the cost of production and risk of environmental pollution. Therefore, determination of optimum N requirements for plant growth is necessary. Previous studies mostly established critical N dilution curves based on aboveground dry matter (DM) or leaf dry matter (LDM) and stem dry matter (SDM), to diagnose the N nutrition status of the whole plant. As these methods are time consuming, we investigated the more rapidly determined leaf area index (LAI) method to establish the critical nitrogen (Nc) dilution curve, and the curve was used to diagnose plant N status for winter wheat in Guanzhong Plain in Northwest China. Field experiments were conducted using four N fertilization levels (0, 105, 210 and 315 kg ha?1) applied to six wheat cultivars in the 2013–2014 and 2014–2015 growing seasons. LAI, DM, plant N concentration (PNC) and grain yield were determined. Data points from four cultivars were used for establishing the Nc curve and data points from the remaining two cultivars were used for validating the curve. The Nc dilution curve was validated for N-limiting and non-N-limiting growth conditions and there was good agreement between estimated and observed values. The N nutrition index (NNI) ranged from 0.41 to 1.25 and the accumulated plant N deficit (Nand) ranged from 60.38 to –17.92 kg ha?1 during the growing season. The relative grain yield was significantly affected by NNI and was adequately described with a parabolic function. The Nc curve based on LAI can be adopted as an alternative and more rapid approach to diagnose plant N status to support N fertilization decisions during the vegetative growth of winter wheat in Guanzhong Plain in Northwest China.

土壤水分特征曲线模型模拟性能评价

土壤水分特征曲线模型作为实验测定土壤水分特征数据的一种替代方法,因其具有计算方便快捷和便于嵌入数值模拟程序的优点,开始受到越来越广泛的关注。虽然文献中存在众多的土壤水分特征曲线模型,但是这些模型的适用范围及拟合性能尚不明确。为了获得更加准确适用的土壤水分特征曲线,在实际应用中通常需要花费大量时间和精力去测试各种模型。为了解决上述问题,在国内外研究成果的基础上收集整理了12种典型的土壤水分特征曲线模型,并利用包含不同质地、有机质含量及容重的8种土壤的实测土壤水分特征数据来评估比较这些模型的模拟性能。模型性能通过均方根误差(RMSE)、平均偏差(AD)、AIC准则(Akaike Information Criterion)和纳什效率系数(NSE)4个指标评估。研究结果表明:大部分的模型能够提供比较接近于实际的拟合结果,评价指标值也比较相近。其中,KCGS2006(包含3个参数)和K1999模型(包含2个参数)拟合效果最好,而Gregson1987(包含1个参数)的拟合效果最差。该研究可以深入了解各种土壤水分特征曲线模型的适用性与局限性,更好地为生态环境建设和农业可持续发展研究中土壤水力参数的选取提供依据和参考。

Enhanced detection of freeze‒thaw induced landslides in Zhidoi county(Tibetan Plateau,China)with Google Earth Engine and image fusion

Freeze‒thaw induced landslides(FTILs)in grasslands on the Tibetan Plateau are a geological disaster leading to soil erosion.These landslides reduce biodiversity and intensify landscape fragmentation,which in turn are strengthen by the persistent climate change and increased anthropogenic activities.However,conventional techniques for mapping FTILs on a regional scale are impractical due to their labor-intensive,costly,and time-consuming nature.This study focuses on improving FTILs detection by implementing image fusion-based Google Earth Engine(GEE)and a random forest algorithm.Integration of multiple data sources,including texture features,index features,spectral features,slope,and vertical‒vertical polarization data,allow automatic detection of the spatial distribution characteristics of FTILs in Zhidoi county,which is located within the Qinghai‒Tibet Engineering Corridor(QTEC).We employed statistical techniques to elucidate the mechanisms influencing FTILs occurrence.The enhanced method identifies two schemes that achieve high accuracy using a smaller training sample(scheme A:94.1%;scheme D:94.5%)compared to other methods(scheme B:50.0%;scheme C:95.8%).This methodology is effective in generating accurate results using only~10%of the training sample size necessitated by other methods.The spatial distribution patterns of FTILs generated for 2021 are similar to those obtained using various other training sample sources,with a primary concentration observed along the central region traversed by the QTEC.The results highlight the slope as the most crucial feature in the fusion images,accounting for 93%of FTILs occurring on gentle slopes ranging from 0°to 14°.This study provides a theoretical framework and technological reference for the identification,monitoring,prevention and control of FTILs in grasslands.Such developments hold the potential to benefit the management of grassland ecosystem,reduce economic losses,and promote grassland sustainability.

Greenhouse area detection in Guanzhong Plain,Shaanxi,China:spatio-temporal change and suitability classification

The extensive use of greenhouses has brought soared economic benefits for farming practitioners in China and an overview of the spatio-temporal distribution of greenhouses is of great interest to agricultural practitioners and decision-makers.In this study,Landsat image based greenhouse maps in Guanzhong Plain,Shaanxi,China were made using random forest classification algorithm through visual interpretation on the Google Earth Engine.The 7-year's changes in greenhouse areas were investigated(i.e.2000,2003,2006,2010,2013,2015 and 2019)with yearly overall accuracy more than 90%.The results showed that the total area of greenhouses in Guanzhong Plain demonstrated an increasing trend,from 5.92 km2 in 2000 to 194.42 km2 in 2019 with a considerable growth between 2010 and 2015.The dominant drivers for the increase are largely attributed to the government policy as well as economic profitability.The distribution of greenhouse shifts to central and eastern regions of Guanzhong Plain.Greenhouses preferentially expand to the area near to rural roads,main rivers,and high elevation,with more than 45%greenhouses distributed within 1 km of the county rural road.The principal component analysis based suitability evaluation showed that a total of 38.44%of the area was suitable for greenhouse.