Improving crop water productivity is necessary for ensuring food security. To quantify the water utilization in grain production from multiple perspectives, gross inflow water productivity(WPg), generalized agricultur...Improving crop water productivity is necessary for ensuring food security. To quantify the water utilization in grain production from multiple perspectives, gross inflow water productivity(WPg), generalized agricultural water productivity(WPa), evapotranspiration water productivity(WPET) and irrigation water productivity(WPI) were examined in this study. This paper calculated and analyzed the temporal and spatial variation in these water productivity(WP) indices in the irrigated land of Heilongjiang Province. The results showed that almost all of the municipal WP indices increased from 2007 to 2015. The four indices showed large differences in scientific connotation and numerical performance, and their degrees of spatial variation were ranked as WPI>WPa>WPg>WPET. The spatial patterns of WP indices in different years were similar; the central and southern regions on the Songnen Plain and the eastern region had high WP values, while those of the northern region were low. Each WP index was used to evaluate the relationship between the input of water resources and the output of grain between different regions. Most cities had the potential to improve WP by reducing the input of irrigation water. Furthermore, the results provided recommendations to decision makers to plan for efficient use of water resources in different cities.展开更多
A variation pixels identification method was proposed aiming at depressing the effect of variation pixels, which dilates the theoretical hyperspectral data simplex and misguides volume evaluation of the simplex. With ...A variation pixels identification method was proposed aiming at depressing the effect of variation pixels, which dilates the theoretical hyperspectral data simplex and misguides volume evaluation of the simplex. With integration of both spatial and spectral information, this method quantitatively defines a variation index for every pixel. The variation index is proportional to pixels local entropy but inversely proportional to pixels kernel spatial attraction. The number of pixels removed was modulated by an artificial threshold factor α. Two real hyperspectral data sets were employed to examine the endmember extraction results. The reconstruction errors of preprocessing data as opposed to the result of original data were compared. The experimental results show that the number of distinct endmembers extracted has increased and the reconstruction error is greatly reduced. 100% is an optional value for the threshold factor α when dealing with no prior knowledge hyperspectral data.展开更多
为了寻求合理简化的流域地形指数水文模型TOPMODEL(Topographic Index model)用于大尺度的陆面模式,推导了土壤表层饱和导水率k0、衰减因子f和地下水补给速率R空间都可变的扩展的TOPMODEL,并将f空间非均匀分布的TOPMODEL与陆面模式SSiB...为了寻求合理简化的流域地形指数水文模型TOPMODEL(Topographic Index model)用于大尺度的陆面模式,推导了土壤表层饱和导水率k0、衰减因子f和地下水补给速率R空间都可变的扩展的TOPMODEL,并将f空间非均匀分布的TOPMODEL与陆面模式SSiB4耦合(SSiB4/GTOP)。通过耦合模型在f空间非均匀条件下进行实际流域的水文模拟,分析f空间非均匀对流域土壤湿度、蒸散发、地表径流、基流和总径流的影响。主要结论有:(1)k0和R的空间变化并不改变经典TOPMODEL原有关系式,只要定义新的地形指数,k0和R空间非均匀TOPMODEL与空间均匀的TOPMODEL并无区别;(2) f空间变化条件下由于局地的地下水埋深还与局地的f值有关,地形指数相同的区域具有水文相似性这一结论不再成立;(3)与f空间均匀的模拟结果相比较,f随海拔高度h i增加而线性减小使模拟的流域土壤湿度、地表径流和流域蒸散减小但使基流和总径流增加;(4) f空间非均匀对流域水文模拟结果有影响,但其影响明显小于流域地形因子的影响。展开更多
基金Supported by National Natural Science Foundation of China(51479032)National Key R&D Plan(2017YFC0406002)
文摘Improving crop water productivity is necessary for ensuring food security. To quantify the water utilization in grain production from multiple perspectives, gross inflow water productivity(WPg), generalized agricultural water productivity(WPa), evapotranspiration water productivity(WPET) and irrigation water productivity(WPI) were examined in this study. This paper calculated and analyzed the temporal and spatial variation in these water productivity(WP) indices in the irrigated land of Heilongjiang Province. The results showed that almost all of the municipal WP indices increased from 2007 to 2015. The four indices showed large differences in scientific connotation and numerical performance, and their degrees of spatial variation were ranked as WPI>WPa>WPg>WPET. The spatial patterns of WP indices in different years were similar; the central and southern regions on the Songnen Plain and the eastern region had high WP values, while those of the northern region were low. Each WP index was used to evaluate the relationship between the input of water resources and the output of grain between different regions. Most cities had the potential to improve WP by reducing the input of irrigation water. Furthermore, the results provided recommendations to decision makers to plan for efficient use of water resources in different cities.
基金Projects(61571145,61405041)supported by the National Natural Science Foundation of ChinaProject(2014M551221)supported by the China Postdoctoral Science Foundation,China+3 种基金Project(LBH-Z13057)supported by the Heilongjiang Postdoctoral Science Found,ChinaProject(ZD201216)supported by the Key Program of Heilongjiang Natural Science Foundation,ChinaProject(RC2013XK009003)supported by the Program of Excellent Academic Leaders of Harbin,ChinaProject(HEUCF1508)supported by the Fundamental Research Funds for the Central Universities,China
文摘A variation pixels identification method was proposed aiming at depressing the effect of variation pixels, which dilates the theoretical hyperspectral data simplex and misguides volume evaluation of the simplex. With integration of both spatial and spectral information, this method quantitatively defines a variation index for every pixel. The variation index is proportional to pixels local entropy but inversely proportional to pixels kernel spatial attraction. The number of pixels removed was modulated by an artificial threshold factor α. Two real hyperspectral data sets were employed to examine the endmember extraction results. The reconstruction errors of preprocessing data as opposed to the result of original data were compared. The experimental results show that the number of distinct endmembers extracted has increased and the reconstruction error is greatly reduced. 100% is an optional value for the threshold factor α when dealing with no prior knowledge hyperspectral data.
