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   水面蒸发 在 计算机软件及计算机应用 分类中 的翻译结果: 查询用时:0.09秒
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  water surface evaporation
Using the water-balance method, the authors studied the water consumption of tomato (Lycopersicon esculentum Mill.) and the relationship between evapotranspiration and water surface evaporation measured with 20?cm pan.
      
The accumulative value of evapotranspiration is approximately equal to the accumulative value of water surface evaporation measured using 20?cm pan.
      
Evaporation may be approximated using the mean monthly pan evaporation or free water surface evaporation data.
      
It was also established that there was a corresponding increase in open water surface evaporation during this period.
      


On the basis of numerous experimental data and practical experiences obtained from extensive evaporation Investigation of different types of water regions in China,a formula of evaporation coefficient which could be universally used in China is developed and recommended.The formula,simple in form,not only reflects closely the real picture of the mass transfer at air-water interface,but takes care of the mechanism of free and forced convection in a single expression both in form and function.The new formula has...

On the basis of numerous experimental data and practical experiences obtained from extensive evaporation Investigation of different types of water regions in China,a formula of evaporation coefficient which could be universally used in China is developed and recommended.The formula,simple in form,not only reflects closely the real picture of the mass transfer at air-water interface,but takes care of the mechanism of free and forced convection in a single expression both in form and function.The new formula has been satisfactorily compared with some well-known relevant formulas and evaporation data measured directly from various water bodies.

着重介绍我国水面蒸发-散热系数研究的一项成果─—水面蒸发系数公式的计算结果与实际情况的对比,证明公式的可靠性和在全国范围内的可用性。

The spatial distribution of yearly mean pan evaporation and the relationships between it and DEM & other factors extracted from DEM are analyzed using pan evaporation dataset of 117 pan evaporation stations in Guangdong province,monthly 1980-2000.By means of DEM&GIS technology,this paper provides a new method based on the Back Propagation model of Neural Network for spatial interpolation(BPNNSI) of yearly mean pan evaporation.It is assumed that the spatial distribution of yearly mean pan evaporation is the result...

The spatial distribution of yearly mean pan evaporation and the relationships between it and DEM & other factors extracted from DEM are analyzed using pan evaporation dataset of 117 pan evaporation stations in Guangdong province,monthly 1980-2000.By means of DEM&GIS technology,this paper provides a new method based on the Back Propagation model of Neural Network for spatial interpolation(BPNNSI) of yearly mean pan evaporation.It is assumed that the spatial distribution of yearly mean pan evaporation is the result of the interaction of various factors and can be modeled as a complex non-linear function.So,through the BPNNSI model,we can use those factors as input parameters to simulate the spatial distribution of yearly mean pan evaporation,and the expectant output will be the values of yearly mean pan evaporation.The results of application in Guangdong province reveal that: ①The highest value of relative difference is-11.6%,the lowest value is 0.36% and the average value is 3.15%;Correlation coefficient between the observed values and modeling values is 0.93.②Compared with other models generally used(such as IDW and KRIGING),the BPNNSI model shows the highest modeling and prediction precision because of its complex capabilities of nonlinear mapping.The BPNNSI method not only can be applied to surface interpolation of yearly mean pan evaporation,but also can be used for generating high spatial resolution data sets.If can better reflect regional and spatial features of pan evaporation and explain the quantitative relation between pan evaporation and its affecting factors.

以广东省117个蒸发站点为基础数据,分析了多年平均水面蒸发量的空间分布特征及其与经度、纬度、海拔高度、坡度、坡向、太阳天文辐射、植被指数的内在关系,提出了一种基于DEM与GIS技术并利用BP神经网络模型进行插值的新方法(BPNNSI)。用没有参与建模的24个站点进行验证,结果表明,该方法由于综合考虑水面蒸发量的各种影响因素,明显的优于IDW、KRIGING方法。因而该方法不仅能够用于水面蒸发量的空间插值,而且依此获取的高精度、高分辨率蒸发量数据,对与其相关领域的研究具有重要意义,还对降雨、平均气温等的空间插值有借鉴意义。

 
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