塔河流域森林生态建设存在的主要问题及其策略

随着时间的推移,塔河流域生态环境恶化的现实已被越来越多的人们所认识。造成塔河中下游森林退化,生态环境恶化的主要原因除自然因素外,主要是人为不合理的社会经济活动的影响。目前塔河流域森林生态建设存在的主要问题有:第一水资源不合理的利用成为沙漠化和次生盐渍化的主要原因;第二传统的生活方式和掠夺式的生产方式使生态环境遭到破坏;第三耕地的增加,满足不了人口发展的需求,大面积的无序开荒,导致生态环境进一步恶化。为塔河中下游林地植被恢复、建设及防止退化的策略有:塔河中下游生态工程治理的原则;塔河中下游生态环境治理的基本思路;塔河流域生态环境治理的主要对策,合理利用水资源,坚持生产、生态建设并重,确保生态用水;要积极调整农村产业结构,正确处理林业和农业、林业和牧业以及林业和工业发展的关系;大力发展农村能源建设,从根本上解决农村薪材和生态保护之间矛盾;大力保护、恢复、发展荒漠林草植被,大力发展绿洲林业,建立荒漠生态环境和绿洲共同支撑的稳定的生态体系;积极实施林业生态工程和林果工程,建立较为完备和发达的生态和产业体系。     

塔里木河下游绿色走廊的生态问题与治理对策

从经济、军事和生态三个角度分析了保护塔里木河下游绿色走廊的必要性,概括了该区域的生态环境现状,即河水矿化度升高、地下水位下降从而导致植被的退化和沙漠化加剧的问题。最后提出了以水资源合理利用为前提和中心的治理对策。     

塔里木河中游段治理中的牧区水利建设

塔里木河中下游地区生态环境急剧恶化,最主要的原因是中游段河水近一半21×108m3被人为的散失,造成下游河水所剩无几,致使尾闾台特玛湖干涸。解决的根本办法是将中下游段两岸的农牧民迁出,实现人为耗水为零。近期切实可行的办法是积极开展牧区水利建设,改变牧业生产方式,集中高效利用塔河水资源,发展人工草地,改良天然草场,实现牧业生产生态环境的协调发展,人与自然和谐相处。     

NUTRIENT CONCENTRATION CRITERIA AND CHARACTERIZATION OF PATTERNS IN TROPHIC STATE FOR RIVERS IN HETEROGENEOUS LANDSCAPES1

ABSTRACT: A method is demonstrated for the development of nutrient concentration criteria and large scale assessment of trophic state in environmentally heterogeneous landscapes. The method uses the River Environment Classification (REC) as a spatial framework to partition rivers according to differences in processes that control the accrual and loss of algae biomass. The method is then applied to gravel bed rivers with natural flow regimes that drain hilly watersheds in New Zealand's South Island. An existing model is used to characterize trophic state (in terms of chlorophyll a as a measure of maximum biomass) using nutrient concentration, which controls the rate of biomass accrual, and flood frequency, which controls biomass loss. Variation in flood frequency was partitioned into three classes, and flow data measured at 68 sites was used to show that the classes differ with respect to flood frequency. Variation in nutrient concentration was partitioned at smaller spatial scales by subdivision of higher level classes into seven classes. The median of flood frequency in each of the three higher level classes was used as a control variable in the model to provide spatially explicit nutrient concentration criteria by setting maximum chlorophyll a to reflect a desired trophic state. The median of mean monthly soluble reactive phosphorus and soluble inorganic nitrogen measured at 68 water quality monitoring sites were then used to characterize the trophic state of each of the seven lower level classes. The method models biomass and therefore allows variation in this response variable to provide options for trophic state and the associated nutrient concentrations to achieve these. Thus it is less deterministic than using reference site water quality. The choice from among these options is a sociopolitical decision, which reflects the management objectives rather than purely technical considerations.     

EFFECTS OF WATERSHED REPRESENTATION ON RUNOFF AND SEDIMENT YIELD MODELING1

ABSTRACT: This paper evaluates the effects of watershed geometric representation (i.e., plane and channel representation) on runoff and sediment yield simulations in a semiarid rangeland watershed. A process based, spatially distributed runoff erosion model (KINEROS2) was used to explore four spatial representations of a 4.4 ha experimental watershed. The most complex representation included all 96 channel elements identifiable in the field. The least complex representation contained only five channel elements. It was concluded that oversimplified watershed representations greatly influence runoff and sediment yield simulations by inducing excessive infiltration on hillslopes and distorting runoff patterns and sediment fluxes. Runoff and sediment yield decrease systematically with decreasing complexity in watershed representation. However, less complex representations had less impact on runoff and sediment‐yield simulations for small rainfall events. This study concludes that the selection of the appropriate level of watershed representation can have important theoretical and practical implications on runoff and sediment yield modeling in semiarid environments.     

2004.7.20云南盈江滑坡泥石流山洪灾害成因及减灾对策

云南省德宏州盈江县位于横断山区西南部.2004年7月18日～19日,该县北部的的支那、盏西、芒璋等地遭受特大暴雨袭击,引起7.20滑坡泥石流山洪灾害,造成59人死亡失踪和15 857万元财产损失.60年一遇、19小时186.2mm的特大暴雨,是该次滑坡泥石流山洪灾害形成的根本原因.针对灾害的特征、现状和发展趋势,提出了拟采取的减灾措施.     

基于GIS的长江中下游地区洪灾风险分区及评价

国内外近几年的发展表明,在所有可能避免和减轻自然灾害的措施中,最简单有效的方法就是通过在科学研究基础上进行风险区划,将自然灾害管理提高到风险管理的水平.在长江流域数字化地图的基础上,选取不同重复期(20,50,100年),及包括1870年历史洪水和1931,1935,1954,1991,1995,1996,1998,1999和2002年共10次洪水,借助Arcview地理信息系统的空间分析和叠加功能,对长江中下游地区的洪水灾害危险性进行了初步评价.首先参考洪水灾害淹没图和相关历史文献记录资料,构建10次洪水受灾县(市)分布图;其次对这10次洪水受灾县(市)分布图进行叠加,得到长江中下游地区洪涝灾害风险性评价图.分析表明:长江中下游地区洪水风险的分布是有规律的,而且具有明显的地理意义.有4个明显的高危风险区,分别是洞庭湖、鄱阳湖两湖平原的湖滨地区和公安以下的长江中游河段的沿江一带,尤其是荆江河段以及两江相夹地势低洼的江汉平原;沿高危风险区外侧为高风险地区,重点在汉江下游、资、沅、澧水、清江流域、皖沿江地区以及太湖流域的部分地区;沿长江于高危风险和高风险地区两侧分别为风险较小地区;其他地区对于洪水灾害而言则为安全地区.评价结果与长江中下游的实际情况基本吻合.     

洪涝灾害评价的威布尔模型

首次将威布尔分布用于淮河流域水灾成灾面积研究,揭示了淮河流域洪涝灾害成灾面积形成的 内在规律,进而利用河南、安徽、江苏和山东4省的各自灾度对淮河流域的灾害风险建立了线性回归模型.实证分析表明,本方法切实可行,特别适用于大样本计算.     

中国水灾社会脆弱性评估方法的改进与应用--以长沙地区为例

中国是洪水灾害发生频繁的国家之一,研究水灾脆弱性对中国的灾害风险管理有重要的意义.但是,合理评估脆弱性尤其是社会脆弱性却面临着极大的挑战.论文对评估社会脆弱性指数的研究现状进行了分析,指出了传统评估方法存在的问题,并尝试改进Hoovering评估模式.选择湘江流域的长沙地区为研究区,应用改进模型对研究区进行了社会脆弱性指数的评估.结果表明,长沙地区社会脆弱性从1980年至2000年基本处于下降趋势,但是在2002年和2003年增长迅速.2003年,长沙5区4县中社会脆弱性指数最大的是开福区,其次是长沙县,而宁乡县的社会脆弱性指数最低.     

Discriminate Analysis for Dust Storm Prediction in the Gobi and Steppe Regions in Mongolia

A discriminate analysis method for probability forecast of dust storms in Mongolia has been developed. The prediction method uses data recorded at 23 meteorological stations in the Gobi and steppe regions of Mongolia, including surface air pressure and geo-potential height at the 500-hPa level on grid points, and weather maps from 1975 to 1990. Weather elements such as air temperature, pressure, geo-potential height etc, which influence the formation of dust storms, are prepared as predictors. To select the most informative/important predictors (variables), we used a mean correlation matrix of variables together with the Mahalonobis distance, and correlation coefficients between dust storms and predictors with an orthogonalization for removing correlated predictors. The most informative predictors for dust storm prediction are intensities of surface cyclones and migratory anticyclones, passage of cold fronts, the horizontal gradients of the surface air pressure in the cold frontal zone, cyclonic circulations from the ground surface up to the 500-hPa level, the geo-potential height at 500-hPa level and its temporal changes. Selected predictors are used in discriminate analysis for formulating dust storm prediction equations. Sandstorm data have been classified into three classes, viz., strong, moderate and weak dust storms, depending on their intensities, durations and areas covered. Predictions of the probabilities of dust storm occurrence use the prediction equations for each class. The prediction is made from 12 hours to 36 hours. Verification of the probability forecasts of dust storms is also shown. The accuracy of forecasts is 72.2–79.9% with the data used for developing equations (dependent variables), in contrast to 67.1–72.0% with unrelated data for deriving equations (independent variables).