梅州市名城文化景观的保护与开发研究

从名城文化内涵出发，着眼于作为客家人文中心和名城文化景观的集中的梅州市区，全面分析了其中丰富多样的文化景观资源的特征及其文化内蕴。揭示了梅州名城文化景观保护与开发过程中的成绩与存在问题。并从文化地理学的视觉，结合旅游开发和城市规划，论证了科学保护与开发梅州名城文化景观的下述对策与途径的必要性与可行性：提升名城办的职能并与相关部门共营名城文化氛围；强化名城轴线与标志性文化景观；抢救与保护“老字号”等一批文化景观景区；适度利用，以积极的开发促其效的保护。     

云南松根系对土壤牵引效应测试系统的设计与实现

目前在野外对云南松根系与土壤的机械效庆的研究，由于测试研究受多种因数的影响，开展研究困难较大，研究精度也受到一定程度的影响，这对较深入的描述根系与土壤相互作用的机械效应带来一定的困难。本文基于这一实际，设计了能在室内和野外进行实时测试分析的测试系统，并配套了支持PCMCIA插槽的DAQP－12型模数转换（A／D）卡，以及直流电供电的QT－300型调理装置。结合所配套的硬件，利用Visual C在Windows95/98平台编写了软件，经过实际试验测试，系统各项性能能够满足云南松根系对土壤的机械效应研究的测试分析要求。     

滇池农村固体废物和化肥流失治理试验研究

怎样合理处置农村固体废物和减少农田化肥流失一直是农村面源污染控制的难题之一。该研究将农村固体废物的处理与减少化肥施用措施有机结合，利用微生物复合发酵剂和农村固体废物生产活性肥料，开展了一系列农业种植试验和数据监测，在此基础上，提出了一套实用性强、效果好的控制农业固体废物和化肥流失污染的对策措施。     

山岳型旅游区人文建筑环境后效与调控模型

许多山岳型旅游区内或其流域上游，都建有人文建筑，而且在急剧增多，导致自然环境日趋恶化，其中乱建疗养院和旅馆的影响最为严重。通过地监测并全面分析张家界环境演变趋势，发现住宿施对环境的影响，比其他游乐设施更为明显。张家界国家森林公园生态环境的脆弱因子是金鞭溪水质。金鞭溪水质恶化主要表现为蓝藻，绿藻迅速繁殖，感官质量下降。主要原因是磷污染较重，总磷年均值100%超标。本文提出了基于环境脆弱因子的动态阈值调控模型，通过计算得出：在不超出张家界景区最为脆弱的环境因子-金鞭溪水质标准：总磷≤0.02前提下，金鞭溪上游接待区住宿设施生态阈值的动态系列：春季临界床位数为1186，夏季为3057，冬季为545，秋季为333。目前的建筑规模已超过了金鞭溪上游接待区住宿设施生态阈值。     

城乡一体化的动力机制与对策思路——以浙江省金华市为例

文章首先分析了金华实施城乡一体化的背景，然后运用增长极理论阐述了该地区城乡一体化的动力机制，最后从工业园区化，农村城市化，基础设施一体化的角度，分析了制约此进程的一些因素。并提出了相应对策与思路。     

云南省金沙江流域土壤流失方程研究

云南金沙江流域是长江中上游水土流失最严重的区域。本项研究以“通用土壤流失方程”(USLE)为蓝本,运用小区实验等手段,综合分析了各个侵蚀因子,建立了云南金沙江流域土壤流失方程A=R·K·LS·c·P,并确定了方程中诸因子的求算方法和数值,以及该流域土壤允许流失量,为方程的应用提供了基本的技术数据。同时,还进行了方程的检验,方程计算值与小区实测值的相对误差在6.3％以下,表明该方程在实际应用中是可靠的。该方程的建立,可为云南金沙江流域预测预报土壤侵蚀,制定土地合理利用规划方案、水土保持措施和土地生态安全格局提供了一套可靠的科学方法和依据。     

云南省金沙江流域水土流失基本特征分析

在应用新近建立的云南金沙江流域土壤流失方程测算该流域各县(市、区)年均土壤流失总量和各地类年均 土壤流失量基础上,分析了该流域水土流失的总体特征、各地类水土流失特征和不同坡度级坡耕地的水土流失特 征,为因地制宜地防治水土流失提供了依据。     

Groundwater regime and calculation of yield response in North China Plain: a case study of Luancheng County in Hebei Province

The groundwater table has been declining at a rate of 0.65 m/yr in Luancheng County since large scale groundwater extraction carried out in the 1960s. The drop of precipitation, substantial increase in agricultural output, variations of crop planting structure and construction of water conservancy projects in the headwater area all tie up with the decline of the groundwater table. On the basis of analyzing the hydrogeological conditions and the water resources utilization of Luancheng County, a three-dimensional groundwater flow model was developed to simulate the county’s groundwater flow through finite-difference method using Visual Modflow software. We divide the research field into four parts after analyzing the hydrogeological condition. Based on parameter calibration and adjustment using measured data, the hydraulic conductivity and specific yield were simulated. Using the calibrated model, we analyze the agricultural water saving potentiality and its influence on the groundwater. The results are as follows: (1) if we decrease the amount of water extracted by 0.14xl0⁸ m³, the average groundwater table of the five observation wells in December will rise by 0.33 m; (2) if we decrease the water by 0.29x 10⁸m³, the average groundwater table of the five observation wells in December will rise by 0.64 m; and (3) if we increase the water by 0.29 x 10⁸m³, the average groundwater table of the five observation wells in December will decline by 0.45 m. So we can draw a conclusion that controlling the agricultural water use is an important way to prevent the decline of groundwater table.     

Size Scaling of Cross Correlation Between Multiple Variables

Reservoir models have large uncertainty because of spatial variability and limited sample data. The ultimate aim is to use simultaneously all available data sources to reduce uncertainty and provide reliable reservoir models for resource assessment and flow simulation. Seismic impedance or some other attribute provides a key source of data for reservoir modeling. These seismic data are at a coarser scale than the hard well data and it not an exact measurement of facies proportions or porosity. A requirement for data integration is the cross-covariance between the well and seismic data.The size-scaling behavior of the cross correlation for different measurement scales was nvestigated. The size-scaling relationship is derived theoretically and validated by numerical studies (including an example with real data). The limit properties of the cross-correlation coefficient when the averaging volume becomes large is shown. After some averaging volume, the volume-dependent cross-correlation coefficient reaches a limit value. This plateau value is controlled mainly by the large-scale behavior of the cross and direct variograms.The cross correlation can increase or decrease with volume support depending on the relative importance of long- and short-scale covariance structures. If the direct and cross variograms are proportional, there is no change in the cross correlation as the averaging volume changes. Our study shows that the volume-dependent cross-correlation coefficient is sensitive to the shape of the cross variogram and differences between the direct variograms of the well data and seismic data.     

A study on the early-warning technique concerning debris flow disasters

According to the principle of the eruption of debris flows, the new torrent classification techniques are brought forward. The torrent there can be divided into 4 types such as the debris flow torrent with high destructive strength, the debris flow torrent, high sand-carrying capacity flush flood torrent and common flush flood by the techniques. In this paper, the classification indices system and the quantitative rating methods are presented. Based on torrent classification, debris flow torrent hazard zone mapping techniques by which the debris flow disaster early-warning object can be ascertained accurately are identified. The key techniques of building the debris flow disaster neural network (NN)real time forecasting model are given detailed explanations in this paper, including the determination of neural node at the input layer, the output layer and the implicit layer, the construction of knowledge source and the initial weight value and so on. With this technique, the debris flow disaster real-time forecasting neural network model is built according to the rainfall features of the historical debris flow disasters, which includes multiple rain factors such as rainfall of the disaster day, the rainfall of 15 days before the disaster day, the maximal rate of rainfall in one hour and ten minutes. It can forecast the probability, critical rainfall of eruption of the debris flows, through the real-time rainfall monitoring or weather forecasting. Based on the torrent classification and hazard zone mapping, combined with rainfall monitoring in the rainy season and real-time forecasting models, the debris flow disaster early-warning system is built. In this system, the GIS technique, the advanced international software and hardware are applied, which makes the system′s performance steady with good expansibility. The system is a visual information system that serves management and decision-making, which can facilitate timely inspect of the variation of the torrent type and hazardous zone, the torrent management, the early-warning of disasters and the disaster reduction and prevention.