月球上发现固态水

月球勘探者’在月球两极发现水冰的存在 ,不仅为人类在月球上建立维持生命系统 ,而且为我们研究地球上水的来源提供了新的线索。本文简明介绍了月球上固态水的探测、分布区、来源及其意义。     

海冰数值预报在海洋开发中的应用

９０年代以来，海冰数值预报的产品被应用到多种领域，如海上石油开发，海上交通运输，海洋工程及海洋环境保护等，并创造了良好的社会和经济效益。本文叙述了海冰数值预报在海洋开发中的应用，特别侧重于局部海区的冰模式，为海洋工程服务以及结冰海区溢油行为和归宿的模拟研究。     

细粒酒精模型冰的特征长度和变形模量

描述了细粒酒精模型冰特征长放和变形模量的测试理论基础和方法，给出了实际测量结果并该对方法存在的问题进行了讨论。简述了试验过程中发生蠕变的事实并给出最佳试验的砝码质量和试验国外还给出了特征长度，变形模量与冰密度和未冻液体含量的试验关系。     

辽东湾海冰漂移的动力要素分析

利用辽东海JZ20－2海域冰期气象、水文和海冰的实测资料和海冰数值模拟结果，对海冰漂移过程中风和流的拖曳力、海冰内力、科氏力和海面倾斜力要素的基本特征进行了分析；采用海冰热力－动力模式对1999年2月3日6：50至2月5日6：50间辽东湾海冰进行了48h数值模拟，对并JZ20-2海域的海冰动力要素进行了对比分析。发现海冰内力、风和流的拖曳力为同一量级，海面倾斜力和科氏力明显较小，其均值的比例关系依次为14．7：18．8：32．6：1．5：1．0；海冰各动力要素相互影响，共同决定了海冰的漂移速度和运动轨迹。     

2001—2018年基于MODIS遥感影像的青海湖湖冰物候变化特征分析及其影响因素

青海湖是青藏高原上最大的咸水湖,研究该区域冬季湖泊冻融时间的变化趋势及其与气候变化之间的关系,可以为预测未来气候对青海湖水情变化提供重要的见解。根据冰的亮度温度值高于水的亮度温度值这一差异,使用2001—2018年MODIS MOD02QKM数据产品和Landsat TM/ETM+遥感影像分别提取了青海湖开始冻结、完成冻结、开始消融和完成消融四个时间点的数据,综合分析青海湖湖冰物候特征变化,并结合气象数据,得出湖冰物候变化对气候的响应。结果表明：青海湖每年11月左右进入冰期,12月开始形成稳定的冰盖,次年3月或4月开始消融。湖冰覆盖时长和封冻期的变化趋势基本相同,整体上呈现出缩短的趋势,湖冰消融期整体上呈现出先缩短后增加的趋势;2001—2018年,平均首日冻结面积为8.15%,平均冻结速率为192.02 km²?d^?1,开始冻结和完成冻结的日期略有延迟,开始消融和完成消融的日期已经大大提前;冬季温度越高,青海湖湖冰封冻时间越短,日照时数越长湖冰覆盖时长越短,对于湖冰消融期来说,降水量越多湖冰消融速度越慢,平均风速越大湖冰消融速度越快。初步认为,气温是湖冰冻融的主要因素,预测未来1—2 a青海湖冬季气温仍会呈现上升趋势,湖冰封冻时长也会出现缩短趋势。     

深井冰冷冻系统

深井降温是深部矿产资源开采过程中的主要技术问题之一 ,讨论一种深井降温的新技术及方法冰冷冻系统     

凤眼莲、稻草和污泥制备生物炭的特性表征与环境影响解析

有机废弃物限氧热解制备生物炭可在减缓温室气体排放的同时改善土壤和水体环境质量,但同时生物炭在环境中的应用具有潜在生态毒理风险.因此,在将生物炭大规模应用于各类环境介质前,对其关键物理-化学性质进行系统分析与评价是极为必要的.本文选择对我国水生生态环境危害最大的入侵植物凤眼莲(Eichhornia crassipes)和我国产量最高的农业废弃物稻草,以及市政污水处理厂剩余污泥3种生物质前体,于250~550℃进行低温慢热解,对所制备生物炭的表面形貌、元素组成、矿物形态和一系列关键化学特性进行了全面表征与比较分析.在此基础上,深入探讨了此3类生物炭应用于土壤改良、重金属污染修复和水体富营养化控制的潜力与风险.结果表明,凤眼莲生物炭中K、Ca、Na、Mg含量最为丰富,指示其对于缓解土壤酸化具有重要应用价值,而其中P主要以AlPO_4晶体态存在,水溶性较低,这有利于降低此类生物炭引起水体富营养化的风险;水稻秸秆生物炭阳离子交换量(CEC)相对较高,达到33.7 cmol·kg~(-1),表明其在提高土壤保肥能力和降低重金属生物有效性方面具有较大潜力;SEM-EDX显示,凤眼莲生物炭和稻草秸秆生物炭均具有发达的束筒结构,可优先考虑用于改善土壤通气性;但是,部分生物炭中水溶性Cd、As含量超出安全阈值,表明对有机质前体和热解产物进行严格检测和筛选是实现生物炭在环境与农业中安全利用的必要环节.     

SNOW AND ICE ALBEDO MEASURED WITH TWO TYPES OF PYRANOMETERS1

ABSTRACT: In order to obtain total short-wave albedos of snow and ice, both incident and reflected solar radiation were measured over a frozen lake surface using two different types of radiation measurement devices: a Kipp and Zonen thermopile pyranometer with a spectral sensitivity of 300 to 2800 nm and a LI-COR photovoltaic pyranometer with a spectral sensitivity of 400 to 1100 am. The spectral response of the LI-COR pyranometers limits its use as a short-wave radiation measurement device. Therefore, two equations were developed to adjust both the daily incident radiation data and the daily reflected radiation data measured by the LI-COR instrument to total short-wave radiation values, i.e., to the waveband of 300 to 2800 nm (visible to near-infrared spectrum). The LI-COR data were then adjusted, and a total short-wave adjusted albedo was calculated with a modeling efficiency of 0.97.     

EFFECT OF SIMULATED CLIMATE CHANGE ON SNOWMELT RUNOFF MODELING IN SELECTED BASINS1

ABSTRACT: The projected increase in the concentration of CO₂ and other greenhouse gases in the atmosphere is likely to result in a global temperature increase. This paper reports on the probable effects of a temperature increase and changes in transpiration on basin discharge in two different mountain snowmelt regions of the western United States. The hydrological effects of the climate changes are modeled with a relatively simple conceptual, semi-distributed snowmelt runoff model. Based on the model results, it may be concluded that increased air temperatures will result in a shift of snowmelt runoff to earlier in the snowmelt season. Furthermore, it is shown that it is very important to include the expected change in climate-related basin conditions resulting from the modeled temperature increase in the runoff simulation. The effect of adapting the model parameters to reflect the changed basin conditions resulted in a further shift of streamflow to April and an even more significant decrease of snowmelt runoff in June and July. If the air temperatures increase by approximately 5°C and precipitation and accumulated snow amounts remain about the same, runoff in April and May, averaged for the two basins, is expected to increase by 185 percent and 26 percent, respectively. The runoff in June and July will decrease by about 60 percent each month. Overall, the total seasonal runoff decreases by about 6 percent. If increased CO₂ concentrations further change basin conditions by reducing transpiration by the maximum amounts reported in the literature, then, combined with the 5°C temperature increase, the April, May, June, and July changes would average +230 percent, +40 percent, ?55 percent, and ?45 percent, respectively. The total seasonal runoff change would be +11 percent.     

APPLICATION OF THE SNOWMELT RUNOFF MODEL USING MULTIPLE-PARAMETER LANDSCAPE ZONES ON THE TOWANDA CREEK BASIN,PENNSYLVANIA1

ABSTRACT: The Snowmelt Runoff Model (SRM) is designed to compute daily stream discharge using satellite snow cover data for a basin divided into elevation zones. For the Towanda Creek basin, a Pennsylvania watershed with relatively little relief, analysis of snow cover images revealed that both elevation and land use affected snow accumulation and melt on the landscape. The distribution of slope and aspect on the watershed was also considered; however, these landscape features were not well correlated with the available snow cover data. SRM streamflow predictions for 1990, 1993 and 1994 snowmelt seasons for the Towanda Creek basin using a combination of elevation and land use zones yielded more precise streamflow estimates than the use of standard elevation zones alone. The use of multiple-parameter zones worked best in non-rain-on-snow conditions such as in 1990 and 1994 seasons where melt was primarily driven by differences in solar radiation. For seasons with major rain-on-snow events such as 1993, only modest improvements were shown since melt was dominated by rainfall energy inputs, condensation and sensible heat convection. Availability of GIS coverages containing satellite snow cover data and other landscape attributes should permit similar reformulation of multiple-parameter watershed zones and improved SRM streamflow predictions on other basins.