湖北省湖泊资源特点及开发利用

通过对湖北省境内主要湖泊（面积大于１０ｋｍ＾２）的调查与分析，阐述了湖泊资源的几个特点，探讨了湖泊资源利用中存在的问题，并就湖泊资源的合理开发利用途径提出了建议。     

ESTIMATING A CARBON/CHLOROPHYLL RATIO IN NANNOPLANKTON (CRETEIL LAKE,S-E PARIS,FRANCE)1

ABSTRACT: The phytoplankton biomass of the Créteil Lake was characterized through 47 paired measurements of particulate organic carbon and chlorophyll. When determining the tranfers of organic carbon in the lake, the need to convert the phytoplankton biomass into carbon units led to the estimation of a carbon to chlorophyll ratio using regression analyses. An average C:Chl ratio of 80 was found. C:Chl has been found to be highly variable but the value commonly used is C:Chl = 40. In Créteil Lake, the high C:Chl value would characterize the nannoplankton that dominated in the lake. No general conversion factor apparently exists for natural populations; thus, more studies may be necessary for a better knowledge of the carbon budget in lakes.     

LAKE EVAPORATION STUDIES USING SATELLITE THERMAL INFRARED DATA1

Thermal infrared radiation data were acquired by the Heat Capacity Mapping Mission (HCMM) satellite over the surface area (385 km²) of Utah Lake during periodic overpasses in 1978 and 1979. The thermal infrared data were converted to lake surface temperatures which were subsequently used in correlations with lake evaporation. Correlations between HCMM surface temperature and pan-derived evaporation exceeded r = 0.90 when HCMM night and day/night average temperatures and two-day average evaporation values were tested. Similar regression studies were done using monthly data from a conceptual evaporation model and the evaporation pan versus monthly HCMM temperature data. In this test both the HCMM day and night monthly temperature versus the monthly model or pan evaporation had correlations exceeding r = 0.95. Empirical estimates of both short and long term lake evaporation using satellite thermal infrared data seem feasible. Attempts to use the HCMM thermal information as direct input to a theoretical approach to calculating evaporation were inconclusive; however, a definite potential seems to exist.     

浅水湖泊群水质模型的近似解析解法

为了实现在一般微机上也能模拟浅水湖泊群的水质变化，从水质变化的基本控制方程出发，根据浅水湖泊群的水流特征与污染物迁移特性，首先建立了浅水湖泊群ＢＯＤ－ＤＯ模型，然后针对恒定水流和污染源稳定排放污水的情形，把处于湖泊边界上的污染源所面临的湖面视为半无限区域，并考虑到浓度的可叠加性，提出了浅水湖泊群ＢＯＤ－ＤＯ模型的近似解析解法。实例结果表明，这种解法计算工作量和存储量都较小，在一般微机上即能进行，且计算准确度基本上能满足工程实际要求。     

星云湖、杞麓湖磷污染来源比较

通过对星云湖、杞麓湖水体磷含量变化情况、流域产业结构和磷入湖途径的比较分析，认为近年来星云湖水体磷含量水平的大幅提高，使星云湖水质由Ⅲ类在大约5a的时间里下降为Ⅴ类、劣Ⅴ类，与星云湖流域及周边磷化工产业的快速发展息息相关。而杞麓湖由于流域内无磷矿资源也没有大的磷化工产业，其磷含量水平得于稳定。     

洱海沉积物重金属地球化学相及其污染历史研究

高原封闭、半封闭型湖泊是气候和环境演化的敏感指示器，其沉积物记录具有连续性、敏感性和高分辨率的特点。高原湖泊沉积记录在恢复和重塑各种短时间尺度（千年、百年、十年）的气候和环境演化序列上，具有其它自然历史记录无法替代的优势，尤其在揭示近代环境污染历史方面更有其独到之处。本文通过对洱海沉积物重金属地球化学相的研究，利用因子分析方法，识别了沉积物重金属的主要来源和影响其分布的主要因素，即：流域侵蚀作用、大气沉降作用、工业废水与生活污水的排放，以及早期成岩作用。同时，结合沉积物柱芯210PBex计年结果，本文初步评价了洱海150多年来的重金属污染历史：1958年以来．因为化石燃料使用量的增加．洱海湖区大气污染日趋严重；1982年后，由于西洱河水电站的建成运行和湖区植被的破坏，流域侵蚀作用显著加强，应当引起重视。     

浅水湖泊营养盐的释放

对浅水湖泊中营养盐释放的影响因素分别进行了综述和讨论,并认为水动力过程和水-土界面的铁、锰、硫循环与沉积物中磷释放的关系应该给予足够的重视.     

东昌湖生态系统服务功能及其影响因子分析

湖泊生态系统的服务功能划分为供给功能、支撑功能、调节功能和美学功能,各项功能的发挥程度与水文特征、水质状况、生物多样性、空间物理结构和湖滨景观五个影响因子有关.通过对东昌湖历史变迁的分析,总结得出各因子对东昌湖生态系统服务功能演变的影响及各功能的变化趋势(供给功能和支撑功能呈现先增强后削弱的变化,而调节功能和美学功能总体上呈增强趋势).最后,为使东昌湖生态系统良性循环提出建议:科学调引谭庄水库补水水源,综合考虑生态效益和经济效益,促进东昌湖的综合开发和可持续利用.     

滇池水葫芦生物防治的研究

安全性测定结果发现:在供试的具有代表性的24个科,46种植物中,水葫芦象甲只危害水葫芦,不危害其他任何的当地植物。控制效益实验表明:象甲成虫可大量取食水葫芦叶片和叶柄及茎杆,明显降低植株光合作用;象甲幼虫钻蛀茎杆,致使茎杆变黄植株枯萎,甚至茎杆根部腐烂死亡;象甲可十分有效地降低水葫芦植株的繁殖速率(t>0.01,差异十分显著);象甲还可明显抑制植株个体生长量(t>0.01,差异十分显著);象甲对水葫芦株高和根长也能起到明显的抑制作用。象甲在昆明地区一年发生2~3代,卵,幼虫,蛹和成虫均可正常生长发育,高海拔并不影响象甲的自然生长。     

Human Settlements on the Northern Shores of Lake Aral and Water Level Changes

The shore of Lake Aral in Kazakhstan is a perfect area for studying the human adaptation strategy to past climate changes. New archaeological material, gathered along the northern shores during the expedition of the INTAS project CLIMAN, is briefly presented. Changes in settlement activity during the Atlantic and Subboreal are related to lake level changes of the Aral Sea. A previ-ously proposed lake level maximum needs to be revised. In particular the lake level stand at 72/73 m, with an assumed age of 5000 BP is definitely refused. Based on the presented data the maximum lake level most probably never reached beyond 57/58 mean average sea level (masl). Furthermore the regression during the 15^th–16^th centuries has been underestimated. It may have been lower than the present day level. Thus the present desiccation of the Aral Sea is historically not unique, as a similar regression, probably induced by man as well, has occurred at least once during history. A readjustment of the water level is, therefore, possible at any time.