我国棉花主产省区比较优势分析

1992-1998年平均，我国12个棉花主产省（区）的粮棉单产比和植棉相对效益分别为1.94-7.24和0.95-5.41，经统计分析，这一单产比和相对效益每上升1，一个省1999年与1992年棉花产量之比就分别下降34.0个百分点、上升48.3个百分比，据此比较优势分析，在1999年我国棉花总产下调的形势下，甘肃、新疆宜保持原有产量水平、江苏、浙江、山东、河北、四川5省宜适当下调，而江西、安徽、河南、湖南、湖北5省则宜酌情处理。基于近期国际棉花市场形势的变化，作者认为，与其它省份一样，2001年甘肃、新疆的棉花产量也有较大的上调空间。     

沙漠边缘地区苹果“两高一优”栽培管理技术规范

通过对沙漠边缘地区影响苹果高产高效和优质的生态因子的综合评估，在多项生产试验的基础上，提出了该区苹果幼树期、结果期两个阶段“两高一优”栽培管理技术规范。     

强干热天气对柑桔产量的影响

分析了１９８８年强干热天气过程对柑桔开花座果及其产量的影响和危害，提出了防御对策。     

湖北省1991年度柑桔冻害与避冻栽培区划

文章研究了湖北省各地1992年柑桔单产的减产率与1991年12月最低气温的关系，发现两者之间是一种指数相关关系，它能较好地解释冻害程度与最低气温的关系。用Gumbel分布计算了59个台站5、10、20、25和50年一遇的最低气温。并根据各地不同的10年一遇最低气温，将湖北省分成适宜、次适宜和不适宜柑桔种植区。为柑桔避冻栽培提供了科学依据。     

农业气象产量预测业务系统的研制

农业气象产量预测业务系统（The Agrometeorological Yield Forecasting Operational System，简称AYFOS）使用Quick BASIC、MS-C和汇编语言混合编写而成，采用下拉式和弹出式中文菜单提示、彩色光（亮）条选择的人机界面，提供在线帮助。系统软件结构合理，操作方便、灵活，容错性好，产品图文并茂。系统功能齐全，包括数据管理、组建预测模型、预测模型思路记忆、模型实时预测与预测集成、产品输出管理和系统维护等主要功能模块。系统在某些方面具有自己的软件特色     

吉林省稻田土壤营养元素与水稻产量的相互关系

土壤中的营养元素是土壤肥力的重要组成部分。通过对吉林省主要水稻种植区稻田土壤中的主要营养元素N、P、K及土壤理化性质进行的测试分析 ,及对其与水稻产量之间的关系的探讨表明 ,当水解氮∶速效磷∶速效钾接近 1∶0 .0 6～ 0 .0 8∶0 .4～ 0 .6时 ,水稻单产水平较高 ,这为合理施肥、提高水稻产量提供了科学依据     

浅析传统塑性位势理论与广义塑性位势理论

就传统塑性位势理论与广义塑性位势理论(考虑和不考虑应力主轴旋转两种情况下)进行了系统的综述与比较。两种位势理论就解决金属与岩土变形机制问题均获得了很大的成功(尤其是后者);浅析了广义塑性位势理论遇到的困境和发展前景。     

A Fifty‐Year Record of Historical Sedimentation at Deer Lake,North Carolina*

Although many once‐deforested areas of the eastern United States are now revegetated, impacts of this disturbance on watershed processes may persist. In this study, lake sediment stratigraphy and magnetism were used to assess the recovery of a small watershed in the southern Blue Ridge Mountains following abrupt reduction of human impacts. Average sediment yields were found to be higher than those of less disturbed basins nearby, and lower than those reported from the early twentieth‐century Piedmont Province. Temporal trends in sediment yield appear to reflect both meteorological and land‐use histories. Although most of the lake sediment is magnetically similar to bottomland sources, two instances of local upland sediment input, possibly related to human activities, are evident in the record. Interpreting relationships between sediment yield and changing environmental influences is impeded by poor temporal control in the methodology as well as by the intrinsic dynamics of the fluvial system.     

Sediment yield variability in Spain: a quantitative and semiqualitative analysis using reservoir sedimentation rates

An existing dataset of area-specific sediment yield (SSY) for 60 catchments in Spain that was retrieved from sediment deposition rates in reservoirs [Avendaño Salas, C., Sanz Montero, E., Rayán, C., Gómez Montaña, 1997. Sediment yield at Spanish reservoirs and its relationship with the drainage basin area. In: Proceedings of the 19th Symposium of Large Dams, Florence, 1997. ICOLD (International Committee on Large Dams), pp. 863–874] reveals that catchment area alone explains only 17% of the variability in SSY. In this study, an attempt to explain the remaining variability in SSY was made using a quantitative and a semiqualitative approach for 22 catchments. During a field survey, the 22 selected catchments were characterised by topography, vegetation cover, lithology, shape and the presence of gullies in the broad vicinity of the reservoir. This information was used to develop a factorial scoring index model that provides a fairly accurate and reliable prediction of SSY. A classical multiple regression model using climatic, topographic and land use properties derived from regional datasets could not explain as much variance as the qualitative index model, nor did it appear to be as reliable. The same conclusion could be drawn when using the CORINE soil erosion risk map of southern Europe. The low prediction capability of the multiple regression models and the CORINE soil erosion risk map could be attributed mainly to the fact that these methods do not incorporate gully erosion and that the land cover data are not a good representation of soil cover. Both variables have been shown to be of great importance during the field surveys. Future assessments of SSY could be quickly and efficiently made using the proposed factorial scoring index model. In comparison with other models, which demand more data, the index model offers an alternative prediction tool.     

MODELING OF SEDIMENT AND NONPOINT SOURCE POLLUTANT YIELD

1 INTRODUCT1ONWaer bodies commonly receive both point soure and nonpoint source pollutans. NonPoint pollution ischaracterized by occasional high loads and high concotions (PfatO, et al, l990; Shen, et al., l992;Novotuy and Olem,l994; Li and Shen, l996). It is very difficult to measure, to colltrOl and to trCat. FornonPoint source pollution control, the most productive research area is probably the develOPmnt andtesting of better watershed water quality models (Haith, l998). Measureme…