在农田管理中,土壤水分是极其重要的因素.为了对黑河中上游土壤水分进行合理评估,利用黑河流域中游自动气象站数据,采用BBH(Bucket with a Bottom Hole)模型,计算得到位于黑河中游盈科灌区农田的表层土壤水分,并与实测数据进行对比研究.结果表明,该模型模拟流域土壤水分有一定的精度,能够满足农田水分预测和灌溉需水分析的要求;而且该模型需要的参数较少,计算过程简单,获取数据容易.另外选择黑河上游阿柔草地站气象数据,对高山草原的土壤水分动态变化进行模拟计算,同样得到很好的模拟结果.认为BBH模型能够满足不同下垫面类型的土壤水分的模拟要求,具有一定的实用意义.采用参数同定法对模型的参数进行了敏感性分析,确定了模型参数的适用范围和敏感程度.在结合模型模拟与实际观测的基础上,探讨了农田和草地土壤水分的变化规律,结果发现:土壤水分冬春两季变化缓慢,夏秋两季变化剧烈.
We first discuss the relativity of "true value and homogeneity" for quantitative remote sensing products (QRSPs), and then propose the definitions of "eigenaccuracy" and "eigenhomogeneity" under practical conditions. The eigenaccuracy and eigenhomogeneity for land surface crucial parameters such as albedo, leaf area index (LAI), and surface temperature are analyzed based on a series of experiments. Secondly, we point out the differences and similarities between the scale-free phenomena of the QRSPs and the measurements of the coastline length (1-dimensional) and the curved surface area (2-dimensional). An information fractal algorithm for the QRSPs is presented. In a case study for the LAI, when the fractal dimension is 2.16, the ratio of the LAI retrieval values obtained respectively from remote sensing data of 30 m and 6 km pixel resolution can actually reach as high as 2.86 for the same 6 km pixel using the same retrieval model. Finally, we propose an operational validation method "one test and two matches" and multipoint observation when the real situation does not allow carrying out scanning measurement without gap and overlap on the ground surface.
