农业气象试验站温室土壤温度控制系统

采用８０３１,８２７９,８２５５,ＡＤＣ０８０９,２８６４,６２６４等芯片组成一实用的温室土壤温度控制系统。由键盘输入温室土壤的上,下限温度,通过ＡＤＣ０８０９对温室土壤温度进行采样,并实时显示土壤温度。当土壤温度超越上,下限时,系统报警,并进行自动处理。     

陆面生态过程的一维数值模拟

建立了一个研究大气、植被、土壤相互作用的传播模式。模式是由多层大气模式、多层土壤模式和植被模式通过界面上能量、水汽传输平衡方程耦合而成。对植被和土壤的不同性质,进行了一系列的数值试验。结果表明,不同的植被覆盖以及降水等因子会对大气、植被、地表界面上能量、水汽传输以及热状态产生显著的影响。此模式还可以耦合进中尺度模式用以研究非均匀区域陆面过程和大气的相互作用。     

小麦出苗至抽穗期土壤湿度预报及喷灌量计算

以黑龙江省８５０农场的资料进行分析,５至６月份小麦出苗、拔节至抽穗阶段,经常出现干旱,是需水关键期,对产量影响极大。所以利用麦田土壤湿度资料,建立经验公式,对土壤墒情进行预测预报,从而获得最佳喷灌时间及喷灌量,为节约用水、计划用水提供了可靠依据。     

广武新灌区春小麦土壤水分变化规律研究

通过对广武新灌区春小麦土壤水分的垂直变化、季节变化和时空变化的研究,将广武新灌区０～１００ｃｍ土层划分为活跃层、贮水层、阻隔层和无效水分层,为寻找新灌区节水途径奠定了基础。     

Topographically moderated soil water seasons impact vegetation dynamics in semiarid mountain catchments: Illustrations from the Dry Creek Experimental Watershed,Idaho, USA

Water stored in soils, in part, controls vegetation productivity and the duration of growing seasons in wildland ecosystems. Soil water is the dynamic product of precipitation, evapotranspiration and soil properties, all of which vary across complex terrain making it challenging to decipher the specific controls that soil water has on growing season dynamics. We assess how soil water use by plants varies across elevations and aspects in the Dry Creek Experimental Watershed in southwest Idaho, USA, a mountainous, semiarid catchment that spans low elevation rain to high elevation snow regimes. We compare trends in soil water and soil temperature with corresponding trends in insolation, precipitation and vegetation productivity, and we observe trends in the timing, rate and duration of soil water extraction by plants across ranges in elevation and aspect. The initiation of growth-supporting conditions, indicated by soil warming, occurs 58 days earlier at lower, compared with higher, elevations. However, growth-supporting conditions also end earlier at lower elevations due to the onset of soil water depletion 29 days earlier than at higher elevations. A corresponding shift in peak NDVI timing occurs 61 days earlier at lower elevations. Differences in timing also occur with aspect, with most threshold timings varying by 14–30 days for paired north- and south-facing sites at similar elevations. While net primary productivity nearly doubles at higher elevations, the duration of the warm-wet period of active water use does not vary systematically with elevation. Instead, the greater ecosystem productivity is related to increased soil water storage capacity, which supports faster soil water use and growth rates near the summer solstice and peak insolation. Larger soil water storage does not appear to extend the duration of the growing season, but rather supports higher growing season intensity when wet-warm soil conditions align with high insolation. These observations highlight the influence of soil water storage capacity in dictating ecological function in these semiarid steppe climatic regimes.     

Evaluation of an empirical orthogonal function–based method to downscale soil moisture patterns based on topographical attributes

Soil moisture influences many hydrologic applications including agriculture, land management and flood prediction. Most remote‐sensing methods that estimate soil moisture produce coarse resolution patterns, so methods are required to downscale such patterns to the resolutions required by these applications (e.g. 10‐ to 30‐m grid cells). At such resolutions, topography is known to affect soil moisture patterns. Although methods have been proposed to downscale soil moisture based on topography, they usually require the availability of past high‐resolution soil moisture patterns from the application region. The objective of this article is to determine whether a single topographic‐based downscaling method can be used at multiple locations without relying on detailed local observations. The evaluated downscaling method is developed on the basis of empirical orthogonal function (EOF) analysis of space–time soil moisture data at a reference catchment. The most important EOFs are then estimated from topographic attributes, and the associated expansion coefficients are estimated on the basis of the spatial‐average soil moisture. To test the portability of this EOF‐based method, it is developed separately using four data sets (Tarrawarra, Tarrawarra 2, Cache la Poudre and Satellite Station), and the relationships that are derived from these data sets to estimate the EOFs and expansion coefficients are compared. In addition, each of these downscaling methods is applied not only for the catchment where it was developed but also to the other three catchments. The results suggest that the EOF downscaling method performs well for the location where it is developed, but its performance degrades when applied to other catchments. Copyright © 2011 John Wiley & Sons, Ltd.     

Development of a continuous soil moisture accounting procedure for curve number methodology and its behaviour with different evapotranspiration methods

The curve number (CN) method is widely used for rainfall–runoff modelling in continuous hydrologic simulation models. A sound continuous soil moisture accounting procedure is necessary for models using the CN method. For shallow soils and soils with low storage, the existing methods have limitations in their ability to reproduce the observed runoff. Therefore, a simple one‐parameter model based on the Soil Conservation Society CN procedure is developed for use in continuous hydrologic simulation. The sensitivity of the model parameter to runoff predictions was also analysed. In addition, the behaviour of the procedure developed and the existing continuous soil moisture accounting procedure used in hydrologic models, in combination with Penman–Monteith and Hargreaves evapotranspiration (ET) methods was also analysed. The new CN methodology, its behaviour and the sensitivity of the depletion coefficient (model parameter) were tested in four United States Geological Survey defined eight‐digit watersheds in different water resources regions of the USA using the SWAT model. In addition to easy parameterization for calibration, the one‐parameter model developed performed adequately in predicting runoff. When tested for shallow soils, the parameter is found to be very sensitive to surface runoff and subsurface flow and less sensitive to ET. Copyright © 2007 John Wiley & Sons, Ltd.     

Process identification at a slow‐moving landslide in the Vorarlberg Alps

A fine‐grained slope that exhibits slow movement rates was investigated to understand how geohydrological processes contribute to a consecutive development of mass movements in the Vorarlberg Alps, Austria. For that purpose intensive hydrometeorological, hydrogeological and geotechnical observations as well as surveying of surface movement rates were conducted during 1998–2001. Subsurface water dynamics at the creeping slope turned out to be dominated by a three‐dimensional pressure system. The pressure reaction is triggered by fast infiltration of surface water and subsequent lateral water flow in the south‐western part of the hillslope. The related pressure signal was shown to propagate further downhill, causing fast reactions of the piezometric head at 5·5 m depth on a daily time scale. The observed pressure reactions might belong to a temporary hillslope water body that extends further downhill. The related buoyancy forces could be one of the driving forces for the mass movement. A physically based hydrological model was adopted to model simultaneously surface and subsurface water dynamics including evapotranspiration and runoff production. It was possible to reproduce surface runoff and observed pressure reactions in principle. However, as soil hydraulic functions were only estimated on pedotransfer functions, a quantitative comparison between observed and simulated subsurface dynamics is not feasible. Nevertheless, the results suggest that it is possible to reconstruct important spatial structures based on sparse observations in the field which allow reasonable simulations with a physically based hydrological model. Copyright © 2004 John Wiley & Sons, Ltd.     

Least‐square support vector machine applied to settlement of shallow foundations on cohesionless soils

This paper examines the potential of least‐square support vector machine (LSVVM) in the prediction of settlement of shallow foundation on cohesionless soil. In LSSVM, Vapnik's ε‐insensitive loss function has been replaced by a cost function that corresponds to a form of ridge regression. The LSSVM involves equality instead of inequality constraints and works with a least‐squares cost function. The five input variables used for the LSSVM for the prediction of settlement are footing width (B), footing length (L), footing net applied pressure (P), average standard penetration test value (N) and footing embedment depth (d). Comparison between LSSVM and some of the traditional interpretation methods are also presented. LSSVM has been used to compute error bar. The results presented in this paper clearly highlight that the LSSVM is a robust tool for prediction of settlement of shallow foundation on cohesionless soil. Copyright © 2008 John Wiley & Sons, Ltd.