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1.
Forests in the Southeastern United States are predicted to experience future changes in seasonal patterns of precipitation inputs as well as more variable precipitation events. These climate change‐induced alterations could increase drought and lower soil water availability. Drought could alter rooting patterns and increase the importance of deep roots that access subsurface water resources. To address plant response to drought in both deep rooting and soil water utilization as well as soil drainage, we utilize a throughfall reduction experiment in a loblolly pine plantation of the Southeastern United States to calibrate and validate a hydrological model. The model was accurately calibrated against field measured soil moisture data under ambient rainfall and validated using 30% throughfall reduction data. Using this model, we then tested these scenarios: (a) evenly reduced precipitation; (b) less precipitation in summer, more in winter; (c) same total amount of precipitation with less frequent but heavier storms; and (d) shallower rooting depth under the above 3 scenarios. When less precipitation was received, drainage decreased proportionally much faster than evapotranspiration implying plants will acquire water first to the detriment of drainage. When precipitation was reduced by more than 30%, plants relied on stored soil water to satisfy evapotranspiration suggesting 30% may be a threshold that if sustained over the long term would deplete plant available soil water. Under the third scenario, evapotranspiration and drainage decreased, whereas surface run‐off increased. Changes in root biomass measured before and 4 years after the throughfall reduction experiment were not detected among treatments. Model simulations, however, indicated gains in evapotranspiration with deeper roots under evenly reduced precipitation and seasonal precipitation redistribution scenarios but not when precipitation frequency was adjusted. Deep soil and deep rooting can provide an important buffer capacity when precipitation alone cannot satisfy the evapotranspirational demand of forests. How this buffering capacity will persist in the face of changing precipitation inputs, however, will depend less on seasonal redistribution than on the magnitude of reductions and changes in rainfall frequency.  相似文献   
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Soil water dynamics are central in linking and regulating natural cycles in ecohydrology, however, mathematical representation of soil water processes in models is challenging given the complexity of these interactions. To assess the impacts of soil water simulation approaches on various model outputs, the Soil and Water Assessment Tool was modified to accommodate an alternative soil water percolation method and tested at two geographically and climatically distinct, instrumented watersheds in the United States. Soil water was evaluated at the site scale via measured observations, and hydrologic and biophysical outputs were analysed at the watershed scale. Results demonstrated an improved Kling–Gupta Efficiency of up to 0.3 and a reduction in percent bias from 5 to 25% at the site scale, when soil water percolation was changed from a threshold, bucket-based approach to an alternative approach based on variable hydraulic conductivity. The primary difference between the approaches was attributed to the ability to simulate soil water content above field capacity for successive days; however, regardless of the approach, a lack of site-specific characterization of soil properties by the soils database at the site scale was found to severely limit the analysis. Differences in approach led to a regime shift in percolation from a few, high magnitude events to frequent, low magnitude events. At the watershed scale, the variable hydraulic conductivity-based approach reduced average annual percolation by 20–50 mm, directly impacting the water balance and subsequently biophysical predictions. For instance, annual denitrification increased by 14–24 kg/ha for the new approach. Overall, the study demonstrates the need for continued efforts to enhance soil water model representation for improving biophysical process simulations.  相似文献   
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作为重要的土壤物理性质,膨胀性在影响土壤导水性、持水性、抗蚀性以及土壤结构的形成和发育等方面发挥着重要作用。为了探讨生物土壤结皮(BSCs)土壤的膨胀特性及其主要影响因素,针对黄土高原风沙土和黄绵土两种典型土壤,利用膨胀仪测定并比较了有、无藓结皮及其在不同因素(初始含水量、干湿循环、冻融循环、温度)下膨胀率的差异,分析了BSCs对土壤膨胀性的影响及其与环境因素和BSCs性质的关系。结果显示:风沙土上藓结皮的膨胀率为1.93%,较无结皮增加了8.65倍;而黄绵土上藓结皮的膨胀率为2.05%,与无结皮相比降低了76.68%。藓结皮的生物量和厚度与其膨胀率在风沙土上均呈线性正相关关系(P < 0.05),在黄绵土上分别呈二次函数(P=0.02)和线性正相关关系(P=0.02)。初始含水量同时影响了土壤最大膨胀率和稳定膨胀时间,影响程度风沙土远大于黄绵土(包括藓结皮和无结皮);干湿循环次数对无结皮土壤膨胀率的影响程度大于藓结皮土壤,其中风沙土和黄绵土上无结皮的膨胀率分别是50.00%~620.00%和-2.28%~10.81%,而两种土壤上藓结皮的膨胀率分别是-5.70%~10.88%和-10.24%~-21.46%;冻融循环下4种土壤的膨胀率均有不同程度的降低,降幅为0~18.54%。黄绵土无结皮的膨胀率受温度影响程度较大,50℃下黄绵土无结皮的膨胀率分别是25℃和35℃下的1.17倍和1.21倍。BSCs显著地改变了风沙土和黄绵土表层的膨胀性,其影响的程度和方向取决于土壤类型。同时,BSCs的膨胀性受含水量、温度、干湿以及冻融循环等关键因素影响。  相似文献   
5.
本文以成矿地质模型为依据,对观驾山—黑山岛一带的化探、物探、遥感及地质等信息变量进行了详细的分析,选取了10个信息变量24个标志状态;在此基础上,运用信息量法对研究区内458个单元的信息量值进行计算,并由此确定了研究范围内的成矿远景区。事实表明,研究区信息量成矿预测是非常有效的  相似文献   
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We present a quantitative star formation history derivation of the four suspected tidal dwarf galaxies in the M 81 group: Holmberg IX, BK3N,Arp-loop (A0952+69) and Garland using HST/WFPC2 images of these galaxies. We construct a library of synthetic Colour-Magnitude Diagrams(CMDs) based on theoretical isochrones and data-derived determinations of photometric errors. These synthetic CMDs were combined linearly andχ2-compared to observed photometry. All the galaxies show continuous star formation between about 20 and 200 Myr ago with star formation rates between 7.5⋅10-3 M/yr and 7.67⋅10-4 M/yr. The metallicity of the detected stars is spanning rather a wide range, being lower than solar abundance. We suppose, that all the galaxies were formed out of material from metal-poor outer part of the giant spiral galaxy M81after tidal interaction about 200 Myr ago. However, this suggestion requires significantly more deep color-magnitude diagrams to be sure with the scenario of the galaxy evolution. This revised version was published online in July 2006 with corrections to the Cover Date.  相似文献   
9.
Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS‐2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring–summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat‐ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   
10.
This paper proposes a multi‐level parallelized substructuring–frontal combined algorithm for the analysis of the problem of thermo/hydraulic/mechanical behaviour of unsaturated soil. Temperature, displacement, pore water pressure and pore air pressure are treated as the primary variables in a non‐linear analysis. Details are given firstly of the substructuring–frontal combined approach. The incorporation of the algorithm in a multi‐level parallel strategy is then discussed. The parallel processing can thus be carried out at different substructural levels. The method thus developed impacts, in a positive way, on both computer storage requirement and execution time. Copyright © 2003 John Wiley & Sons, Ltd.  相似文献   
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