科拉半岛白海集水区水体底质中的亲铜元素(Hg、Cd、Pb、As)     

Дауваиътер В А  朱佛宏 《海洋地质前沿》2007,23(9):22-23

俄罗斯欧洲部分的北方包括穆尔曼斯克地区,具有独一无二的矿物原料资源。在穆尔曼斯克区土地上有俄罗斯极大的矿山采掘、矿山加工和矿山冶金企业。它们每年从地下采出数百万吨岩石至地表,释放入大气圈、水池和流水中数千吨污染物,其中包含剧毒性的金属化合物和生物质污染物。在  相似文献   

基于DEM的河流多尺度显示研究   总被引：6，自引：0，他引：6  

沈涛  苏山舞 《测绘科学》2003,28(2):20-22

进行了基于DEM的河流多尺度显示方法的研究和试验。采用斯特拉勒算法对河流线进行分级,通过DEM提取河流的高差、集水面积等属性信息,并以此为基础提出了对河流的主支流的自动判别的方法,最终以国家基础地理信息的全国1∶25万数据库为数据源实现了实验区域河流的多尺度显示。  相似文献   

黄土高原丘陵区小流域地下水补给特征          下载免费PDF全文

马建业  孙宝洋  肖俊波  王杉杉  马波  李占斌 《干旱区地理》2018,41(5):992-1000

地下水补给量反映了含水层的可更新能力,是地下水资源管理与合理开发利用的关键参数之一。为定量研究黄土高原丘陵沟壑区小流域地下水的补给特征,基于岔巴沟流域上游、中游、下游3个水文站1959-1969年降水与日径流观测资料,通过退水分析法估算了流域地下水补给量,并分析了与降水量和基流量的关系及其在年内的补给变化过程。结果表明：岔巴沟流域年平均基流量为13.09 mm·a^-1,更新时间为124 d,补给量为11.46 mm·a^-1,降水入渗补给率为0.025,基流补给率为0.89。从上游到下游地下水补给量与入渗补给率逐渐增大,且上游与下游之间有显著差异（P<0.05）;基流补给率逐渐减小,各集水区之间差异均显著。地下水补给量与降水量呈线性正相关（R²>0.40）,在下游集水区内随降水量变化的增幅较大。基流量与降水量也呈正相关关系（R²>0.77）,干流基流80%以上源于降水补给转化。以5月份为节点可将地下水补给过程分为"一次补给"和"二次补给"2个主要阶段,其分别占全年总补给量约30%和70%,并且"二次补给"是造成岔巴沟流域不同集水区地下水补给量差异的主要阶段,并且为无资料地区小流域地下水资源的评价提供借鉴。  相似文献   

SWMM模型在城市排水系统中的应用   总被引：1，自引：0，他引：1  

冯艳杰  肖建华 《地理空间信息》2011,(5):125-126,129

通过分析GIS在暴雨径流管理模型建模中的作用,以武汉市东湖流域为例,研究基于G1S的暴雨径流管理模型的应用和方法。结果表明,模拟结果与检测数拟合度很高,为模型的进一步深入应用奠定了基础。  相似文献   

评再版的《集水区经营》论丛     

冯海燕 《山地学报》2006,24(6):775-776

对再版的《集水区经营》论丛进行较详尽的评介。认为该论丛作者为水土保持研究和水土保持工作者提供了较为完整的、行之有效的集水区经营理念和借鉴模式,具有较高的指导性和可借鉴性。  相似文献   

黄土塬区坡面及小集水区泥沙输移比变化特征   总被引：5，自引：0，他引：5  

赵晓光  石辉 《山地学报》2002,20(6):718-722

文章首先推荐了计算泥沙输移比SDR时，所需侵蚀量、输移量的量测方法：侵蚀量用坡长为20m（水平距）、宽5m直线坡，在不同降雨及土地利用下，通过小区出口断面的泥沙量；输移量为坡长大于20m的径流小区小集水区出口处的拦蓄量。然后通过黄土塬区坡面坡度为9%的30m、40m、60m径流小区9年野外实验所得45组有效数据的分析，发现单宽最小径流率qmin和最大含沙量ρmax可判别坡面泥沙侵蚀与输移的对比关系，即输移比SDR，并依据这些参数值，可将侵蚀输移状态划分为“侵蚀——输移区”，“侵蚀——堆积——输移区”和“侵蚀——输移挠动区”3个侵蚀输移状态类型区，同时通过研究给出了各区之间过度转换临界值的计算公式，即ρmax=11.96 0.117qmin和qmin=0.187ρmax-85.676。并能过对21条塬面不同面积（0.5hm^2-41.3hm^2）、坡长（30m-965m)小集水区淤积（输移量）的测量，将测量值与标准小区侵蚀量作对比，计算出各自的输移比SDR，并分别建立了SDR与坡长L、SDR与集水面积A的关系式，即SDR=2.85L^-0.306和SDR=0.735A^-0.151，为快速估算塬面小集水区泥沙输移比SDR值提供了方便。最后，分析了植被覆盖、土壤含水状况、人为活动等其它基因素对泥沙输移比SDR的影响。  相似文献   

流域水系自动提取在西苕溪流域的应用   总被引：7，自引：0，他引：7  

李昌峰  赵锐 《热带地理》2003,23(4):319-323

论述了如何基于栅格DEM自动提取流域自然水系的原理、方法和流程.以西苕溪中上游流域为例,根据DEM精度、上游集水区面积阈值和下垫面地形的不同,对所提取水系进行了比较.针对在平均地形坡度小于3°的平坦区域所提取水系与实际河网偏差较大的问题,提出了利用主干河道和平原水系数字化作为约束条件生成河网的新方法.  相似文献   

基于DEM的全国集水区提取及在泥石流孕险分析中的应用     

顾学云  王茜 《测绘与空间地理信息》2013,(3):34-36,40

3S技术的发展给水文科学带来了新的机遇。基于DEM的水文特征提取技术已经比较成熟,本文从自然灾害防治的角度出发,将基于DEM的流域提取技术应用到泥石流的防治工作中去,重点分析并确定了泥石流发生的流域范围,针对相应集水范围提取了全国范围的集水区边界数据。  相似文献   

藏南普莫雍错流域水体离子组成与空间分布及其环境意义(英文)   总被引：2，自引：1，他引：1  

朱立平  鞠建廷  汪勇  谢曼平  王君波  彭萍  甄晓林  林晓 《地理学报(英文版)》2010,20(1):109-120

The chemistry of major cations (Mg²⁺, Ca²⁺, Na⁺, and K⁺) and anions (HCO₃ ⁻, SO₄ ²⁻, and Cl⁻) in the water of Lake Pumayum Co and its inflow river was studied, revealing the obvious ionic difference among various inflow rivers and the lake. The chemical type of the lake water was Mg²⁺-Ca²⁺-HCO₃ ⁻-SO₄ ²⁺, but the major ions of the main inflow rivers were Ca²⁺-Mg²⁺-HCO₃ ⁻. In the lake inlet of Jiaqu River, the main inflow river, there was significant variance of water chemistry within the depth less than 2 m. However, it was almost homogeneous at other area of the lake. Therefore, with the evidence of distribution of water chemistry and oxygen isotope of lake water, a conclusion can be outlined that Jiaqu River had a distinct effect on the hydrochemistry of the water on the submerged delta, whereas this is not the case for other rivers. The Gibbs plot revealed that the dominant mechanism responsible for controlling chemical compositions of the lake water was rocks weathering in the drainage area. Ion ratios and ternary plots further explored the main processes controlling the water chemistry of the catchment, i.e., carbonate weathering, pyrite weathering, and silicate weathering. The different hydrochemistry characteristics between river water and lake water may result from the CaCO₃ precipitation. The findings will benefit the explanation of the environmental significance of carbonate in paleolimnological studies in the lake.  相似文献   

Inter-annual variations in vegetation and their response to climatic factors in the upper catchments of the Yellow River from 2000 to 2010   总被引：1，自引：0，他引：1  

Ran Cao  Weiguo Jiang  Lihua Yuan  Wenjie Wang  Zhongliang Lv  Zheng Chen 《地理学报(英文版)》2014,24(6):963-979

To understand the variations in vegetation and their correlation with climate factors in the upper catchments of the Yellow River, China, Normalized Difference Vegetation Index（NDVI） time series data from 2000 to 2010 were collected based on the MOD13Q1 product. The coefficient of variation, Theil–Sen median trend analysis and the Mann–Kendall test were combined to investigate the volatility characteristic and trend characteristic of the vegetation. Climate data sets were then used to analyze the correlation between variations in vegetation and climate change. In terms of the temporal variations, the vegetation in this study area improved slightly from 2000 to 2010, although the volatility characteristic was larger in 2000–2005 than in 2006–2010. In terms of the spatial variation, vegetation which is relatively stable and has a significantly increasing trend accounts for the largest part of the study area. Its spatial distribution is highly correlated with altitude, which ranges from about 2000 to 3000 m in this area. Highly fluctuating vegetation and vegetation which showed a significantly decreasing trend were mostly distributed around the reservoirs and in the reaches of the river with hydropower developments. Vegetation with a relatively stable and significantly decreasing trend and vegetation with a highly fluctuating and significantly increasing trend are widely dispersed. With respect to the response of vegetation to climate change, about 20–30% of the vegetation has a significant correlation with climatic factors and the correlations in most areas are positive： regions with precipitation as the key influencing factor account for more than 10% of the area; regions with temperature as the key influencing factor account for less than 10% of the area; and regions with precipitation and temperature as the key influencing factors together account for about 5% of the total area. More than 70% of the vegetation has an insignificant correlation with climatic factors.  相似文献