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For spatial crop and agro-systems modelling, there is often a discrepancy between the scale of measured driving data and the target resolution. Spatial data aggregation is often necessary, which can introduce additional uncertainty into the simulation results. Previous studies have shown that climate data aggregation has little effect on simulation of phenological stages, but effects on net primary production (NPP) might still be expected through changing the length of the growing season and the period of grain filling. This study investigates the impact of spatial climate data aggregation on NPP simulation results, applying eleven different models for the same study region (∼34,000 km2), situated in Western Germany. To isolate effects of climate, soil data and management were assumed to be constant over the entire study area and over the entire study period of 29 years. Two crops, winter wheat and silage maize, were tested as monocultures. Compared to the impact of climate data aggregation on yield, the effect on NPP is in a similar range, but is slightly lower, with only small impacts on averages over the entire simulation period and study region. Maximum differences between the five scales in the range of 1–100 km grid cells show changes of 0.4–7.8% and 0.0–4.8% for wheat and maize, respectively, whereas the simulated potential NPP averages of the models show a wide range (1.9–4.2 g C m−2 d−1 and 2.7–6.1 g C m−2 d−1 for wheat and maize, respectively). The impact of the spatial aggregation was also tested for shorter time periods, to see if impacts over shorter periods attenuate over longer periods. The results show larger impacts for single years (up to 9.4% for wheat and up to 13.6% for maize). An analysis of extreme weather conditions shows an aggregation effect in vulnerability up to 12.8% and 15.5% between the different resolutions for wheat and maize, respectively. Simulations of NPP averages over larger areas (e.g. regional scale) and longer time periods (several years) are relatively insensitive to climate data aggregation. However, the scale of climate data is more relevant for impacts on annual averages of NPP or if the period is strongly affected or dominated by drought stress. There should be an awareness of the greater uncertainty for the NPP values in these situations if data are not available at high resolution. On the other hand, the results suggest that there is no need to simulate at high resolution for long term regional NPP averages based on the simplified assumptions (soil and management constant in time and space) used in this study. 相似文献
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不同空间粒度下地表水体分布格局多样性研究 总被引:1,自引:0,他引:1
选取河南省北部、中部和南部典型研究样区,将空间粒度方法引入并应用于地表水体多样性的研究中。在总结前人研究水体多样性测度方法的基础上,提出新的方法——空间分布长度指数(MSHDLI),并在1 km×1 km网格尺度下研究MSHDLI、水网密度(RD)和空间分布面积指数(MSHDAI)的粒度效应、相关性和相关系数的粒度响应、尺度效应关系及回归模型。结果表明:随着粒度的增加,MSHDLI、RD和MSHDAI的粒度响应曲线均为下降型;MSHDLI与RD和MSHDAI有显著的相关关系,平均相关系数r分别为0.997和0.878(P0.01),且MSHDLI与RD、MSHDAI相关系数的粒度效应属于显著正相关关系;MSHDLI与RD的拟合度函数均是对数函数,MSHDLI与MSHDAI的拟合度函数均是多项式函数;由三者的多元线性回归模型可知MSHDLI与RD、MSHDAI线性相关且对它们的解释程度达到95%以上。MSHDLI可以将RD描述水资源广度和MSHDAI描述水资源空间分布离散性的优势结合起来。 相似文献
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砂壤质褐土水力特性与物理性质的空间尺度效应——消除趋势波动分析法 总被引:1,自引:0,他引:1
土壤水力特性与物理性质的空间异质性及其之间的关系在不同尺度上会有不同表现。采用消除趋势波动分析法对土壤水力特性(田间持水量、萎蔫系数和饱和导水率)和物理性质(机械组成、容重和有机碳含量)进行尺度分析。结果表明,只有在一定尺度范围内才能进行土壤水力特性空间变异分析和尺度转换(外推)。过小的尺度范围内不能摆脱空间相关的束缚,尺度太大时不能抓住主要控制因子,因此无法进行尺度外推。所研究砂壤质褐土田间持水量、饱和导水率、容重和有机碳含量可外推尺度范围较大,分别为55~155、50~125、50~125和50~135 m;砂粒、粉粒和黏粒含量的可外推尺度范围较小,为50~85 m,因此在进行空间尺度转换前应先确定其尺度外推范围。 相似文献
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为放大常规喷动床,提出了“旋转导向管喷动床”新概念,设计并安装了两种旋转导向管喷动床。以小麦为原料,测定了旋转导向管新型喷动床的空气动力学特性,包括不同导向管在相同导喷距下风速与床层压降关系、导喷距对风速与床层压降关系的影响和旋转导向管喷动床的循环量等性能。研究结果表明:采用旋转导向管后物料可洒布在整个床层截面上,因此可放大喷动床的直径;在喷动发生后,旋转导向管新型喷动床的床层压降与普通导向管喷动床的床层压降差异较小;导喷距影响最大床层压降,采用调节导向管安装高度的方法,可不考虑最大喷动压强,而根据正常喷动时的压降选用风机。 相似文献
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Sander Janssen Ioannis N. AthanasiadisIrina Bezlepkina Rob KnapenHongtao Li Ignacio Pérez DomínguezAndrea Emilio Rizzoli Martin K. van Ittersum 《Computers and Electronics in Agriculture》2011,76(2):148-160
The ex-ante assessment of the likely impacts of policy changes and technological innovations on agriculture can provide insight into policy effects on land use and other resources and inform discussion on the desirability of such changes. Integrated assessment and modeling (IAM) is an approach that can be used for ex-ante assessment. It may combine several quantitative models representing different processes and scales into a framework for integrated assessment to allow for multi scale analysis of environmental, economic and social issues. IAM is a challenging task as models from different disciplines have a different representation of data, space and time. The aim of this paper is to describe our strategy to conceptually, semantically and technically integrate a chain of models from different domains to assess land use changes. The models that were linked are based on different modeling techniques (e.g. optimization, simulation, estimation) and operate on different time and spatial scales. The conceptual integration to ensure consistent linkage of simulated processes and scales required modelers representing the different models to clarify the data exchanged and interlinking of modeling methodologies across scales. For semantic integration, ontologies provided a way to rigorously define conceptualizations that can be easily shared between various disciplines. Finally, for technical integration, OpenMI was used and supplemented with the information from ontologies. In our case, explicitly tackling the challenge of semantic, conceptual and technical integration of models forced researchers to clarify the assumptions of their model interfaces, which helped to document the model linkage and to efficiently run models together. The linked models can now easily be used for integrated assessments of policy changes, technological innovations and societal and biophysical changes. 相似文献
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陈明亮 《华中农业大学学报》1986,(4)
土壤性质的空间变异性对于土壤改良和作物高产都是重要的。本文就土壤饱和水力传导度的空间变异性、孔性数值与饱和水力传导度的相关分析和用大孔隙度标定饱和水力传导度的空间变异性进行了研究。研究结果表明土壤饱和水力传导度的半方差图体现了该土性的空间结构;土壤饱和水力传导度主要通过大孔隙度来表征,二者的关系可以用直线函数和幂函数的关系式来表示;可以从大孔隙度的分布导出和表征饱和水力传导度标定因子的频率分布,作为他和水力传导度的空间分布的度量。 相似文献
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Long-term (1992–2002) effects of climate changes on soil Collembola in Scots pine Pinus sylvestris forests in North Vidzeme Biosphere Reserve (northern Latvia) are investigated. The study was carried out in three forest stands of different age, young (30–40 years), middle aged (50–70 years), and old (150–200 years). One hundred soil samples were collected within each sampling site once a year in autumn over a period of 11 years. In total, 66 species of Collembola were found. Species richness varied between 47 and 56 and density of Collembola from 7300 to 8300 ind m−2. A statistically significant increase in the sums of positive air temperatures (4 °C) was recorded during the period of investigation. Precipitation and thereby soil moisture showed considerable year-to-year fluctuations. Non-metric Multidimensional Scaling of the data yielded two axes explaining 48.6% and 38.6% of the variation. Axis 1 coincided with the trend of sums of positive air temperature (r=0.66). Axis 1 corresponded best with the negative impact of warming of climate on Collembola, mainly on the euedaphic species inhabiting the deeper layers of the organic soil horizon. Axis 2 was considered reflecting the effect of soil moisture fluctuations (correlation with moisture r=-0.62) on litter dwelling, mostly hemiedaphic Collembola. Species richness tended to decrease gradually in all forest sites during the study period from 29–36 to 13–26 species. Correlation between axes (r=0.455) indicated interaction effects between positive air temperatures and soil moisture. Forest age showed no substantial effect on the community structure, therefore the changes observed cannot be explained by ecological succession. 相似文献