Effects of detailed soil spatial information on watershed modeling across different model scales

Hydro-ecological modelers often use spatial variation of soil information derived from conventional soil surveys in simulation of hydro-ecological processes over watersheds at mesoscale (10–100 km²). Conventional soil surveys are not designed to provide the same level of spatial detail as terrain and vegetation inputs derived from digital terrain analysis and remote sensing techniques. Soil property layers derived from conventional soil surveys are often incompatible with detailed terrain and remotely sensed data due to their difference in scales. The objective of this research is to examine the effect of scale incompatibility between soil information and the detailed digital terrain data and remotely sensed information by comparing simulations of watershed processes based on the conventional soil map and those simulations based on detailed soil information across different simulation scales. The detailed soil spatial information was derived using a GIS (geographical information system), expert knowledge, and fuzzy logic based predictive mapping approach (Soil Land Inference Model, SoLIM). The Regional Hydro-Ecological Simulation System (RHESSys) is used to simulate two watershed processes: net photosynthesis and stream flow. The difference between simulation based on the conventional soil map and that based on the detailed predictive soil map at a given simulation scale is perceived to be the effect of scale incompatibility between conventional soil data and the rest of the (more detailed) data layers at that scale. Two modeling approaches were taken in this study: the lumped parameter approach and the distributed parameter approach. The results over two small watersheds indicate that the effect does not necessarily always increase or decrease as the simulation scale becomes finer or coarser. For a given watershed there seems to be a fixed scale at which the effect is consistently low for the simulated processes with both the lumped parameter approach and the distributed parameter approach.     

VS型垂直摆倾斜仪的安装调试与标定要点

本文总结了铁岭地震台安装，调试与标定VS型垂直倾仪的经验。     

考虑轴向变形、双轴弯曲耦合效应的钢筋混凝土柱的弹塑性分析

在实际地震作用下，高层，特别是高宽比较大的高层结构中，由于倾覆力矩的作用、柱子、特别是外边柱所受轴力的变化将不可忽略。轴向变形与双轴弯曲的耦合作用，将是柱子塑性变形的显著特征。基于材料本构关系的“纤维模型”，能较精确地反映轴向变形，双轴弯曲三者之间的耦合作用。一组钢筋混凝土柱子双轴压弯的计算结果与试验结果的比较，证明了“纤维模型”的有效性和精确性。     

遥测地震仪发射机电路分析及检修

在无线遥测地震仪器中 ,发射机长期使用容易出现输出功率下降、无输出功率、发射频率不准等故障。分析了发射机典型电路——石英晶体主振电路、倍频电路、激励级电路、功率放大级电路的基本原理。排除发射机的故障时 ,先从不同单元电路逐一检查、测试 ,判断故障类型 ,最后进行发射机总调试     

湖泊水下数字高程模型建模方法及应用模型

介绍了当前湖泊水下地形测量的一般方法和作业过程。针对逐点插入构建不规则三角网算法，本文提出了效率改正算法和格网索引号快速计算算法。基于不规则三角网，给出了湖泊水下数字高程模型的一般应用模型——任意点高程计算、填挖方计算模型及等深线计算模型。     

灰色GM(1,1)模型最优维数的研究

灰色GM(1,1)模型的维数对模型的预测精度有很大的影响,本文通过自编的FORTRAN程序,在合适的范围内对GM(1,1)模型的维数进行自动优化,通过对宁波市地面沉降数据的计算分析,得到了C和P的定性关系,确定了优化的评价标准,维数最优化后的模型能反映预测数列变化幅度的大小。     

一种基于浑沌理论的联想记忆神经网络模型

根据联想记忆神经网络的基本原理，提出了一种基于浑沌理论的联想记忆神经网络模型及相应的求解方案，并对该种模型进行了预报试验。结果表明，该种模型的历史预报准确率和实际预报准确率均超过一般随机预报，值得进一步研究和应用。     

大陆地震的动力学模型研究

应用非线性动力学模型，以大陆构造构体为参照对象，对大陆地震的成组孕育和发生过程进行模拟研究，通过对６×８弹簧－滑块－阻尼器组合单元非线性动力学模型的理论计算及其结果的分析，得到了一系列与实际地震较类似的人工地震图像，如模型中的地震活动在时间上有轮回怀，在地点上有条带性，并在不同轮回中有条过移的现象。模型中应力变化十分复杂，但仍能为预测地震提供概略性的信息。     

AN EVALUATION OF SEVERAL TURBULENCE SCHEMES FOR THE PREDICTION OF MEAN AND TURBULENT FIELDS IN COMPLEX TERRAIN

A prognostic three-dimensional mesoscale model has been developed andused in one- and two-dimensional modes to evaluate ten local turbulenceclosure schemes. The schemes ranged from first-order to the two-equationprognostic schemes. Predictions by the models were compared for aone-dimensional convective boundary layer using mixed layer scaling andmeasurements to interpret the results. Two-dimensional simulations were alsoperformed for a sea-breeze flow and for flow over a hill. The results showedthat for all of the models considered, minor differences were produced in themean meteorological fields and in the vertical scalar fluxes, but majordifferences were apparent in the velocity variances and dissipation rate.Predicted tracer concentrations were very sensitive to the turbulence modelformulation for dispersion from a point source in the convective boundarylayer, particularly for the prediction of maximum concentrations. Predictedtracer concentrations from a surface volume source for the two-dimensionalsimulations were similar for all models, although the degree of mixing in themorning growth period produced some differences. Generally, good results forthe mean meteorological fields can be obtained with first-order schemes, evenif they underpredict the magnitude of turbulence in the convective boundarylayer, and reasonable tracer concentrations can also be obtained with thesemodels provided near-source effects are not important. The two-equationprognostic models performed best for the prediction of turbulence in theconvective boundary layer.