干旱半干旱区水资源承载力评价及空间规划指引——以宁夏西海固地区为例

以宁夏西海固地区为例,在区域尺度水资源超载状态分析基础上,构建了栅格尺度水资源承载力评价指标体系和计算方法,阐释了水资源承载力空间格局、特征及其与人口经济要素的空间关系,并提出空间规划与发展路径指引。干旱半干旱区栅格尺度的水资源承载力评估指标体系包括5项一级指标和12项二级指标,案例实证研究与校验表明：指标体系与评估模型具有可操作性,可为空间规划与管制提供更有效的决策支撑;西海固地区栅格尺度的水资源承载力划分为强、较强、中等、较弱以及弱5个等级,强和较强等级区主要位于清水河河谷平原,是黄河扬水灌区与地下水资源富集区的叠加区域,较弱和弱等级区集中分布于黄土丘陵区、六盘山及其余脉山地区。在水资源承载力空间差异分析的基础上,因地制宜地制定空间开发指引,建立“节流为主、开源为辅”的水资源保障体系,有助于构建与区域水资源条件相适应的人口产业布局模式。     

Growth and feeding habits of invasive Pseudorasbora parva in the Chabalang Wetland(Lhasa,China) and its trophic impacts on native fish

In recent years, fish invasion has become one of the main reasons for the decline of nativefish stocks. Pseudorasbora parva is considered one of the major invasive species worldwide. The present study investigated the fish resources of the Chabalang Wetland(Lhasa, Tibet) during dif ferent seasons in2009 and 2013. Four hundred and twelve individuals were subsampled to estimate age, growth, and feeding habit of P. parva. Furthermore, food relationships between P. parva and the native Schizothoracinae fish were also examined. The results revealed a significant shift in species composition and community structure characterized by the disappearance of native fish and outbreak of non-native fish. The percentage of nonnative P. parva in the fish collections significantly increased from 33.64% in 2009 to 64.08% in 2013.The standard length(SL) ranged from 22.00 to 78.71 mm, and their age was 1–5 a. The von Bertalanf fy function was used to model the observed length-at-age data as Lt =112.19(1– e~(-0.1495(t +0.8012))) for females and as Lt =123.12(1– e~(-0.1500(t +0.7132))) for males. The results indicated that P. parva in Tibet has lower growth and mortality rates compared with that from the native ranges. Ninety-seven prey taxa belonging to 9 prey categories were identified in the gut of 38 P. parva. P. parva can be considered a generalized and opportunistic predator, competing with the native fish, especially Schizothorax o'connori, Schizopygopsis younghusbandi younghusbandi, and Ptychobarbus dipogon, for Bacillariophyta and Chironomid larvae.This is an important reason for the decline in native fish population.     

Spatio-temporal variability of small fishes related with environmental factors in a typical domestic tap water lake,Eastern China

The knowledge of prey small fish stock, distribution and abundance is necessary to guide stocking of piscivorous fish for the biomanipulation in domestic tap water lakes. This study describes the current status of small fish community in Lake Kuilei (China), and examines the spatial and seasonal variations of the community in relation to key environmental factors. Based on submerged macrophyte cover and water depth, the lake was divided into five major habitats: (1) macrophyte covered shallow habitat of water depth < 2.00 m, (2) uncovered or less-covered shallow habitat (2.00 m–3.50 m), (3) uncovered medium shallow habitat (3.50 m–5.00 m), (4) uncovered medium deep habitat (5.00 m–6.50 m) and (5) uncovered deep habitat (6.50 m–8.50 m). The abundance and composition of small fish were monitored by benthic fykenet sampling from April 2013 to January 2014. A total of 2881 individuals belonging to 5 families and 21 species were collected. Based on their abundance (accounted for 88.96% of the total) and occurrence (more than 33.33%), Acheilognathus chankaensis, Acheilognathus macropterus, Microphysogobio microstomus, Pseudorasbora parva and Rhinogobius giurinus were recognized as dominant small fish species. The results of correlation analysis identified that species richness ( Sr ), Shannon-Wiener diversity index ( H′ ) and Margalef′s richness index ( D ) were significantly negatively correlated with water depth, but positively correlated with biomass of submerged macrophytes.Redundancy analysis (RDA) revealed that the spatial distributions of most small fishes were negatively associated with water depth. The details of these findings are beneficial to understanding the adaptation of the small fishes in degraded environments, and to developing suitable biomanipulation strategies for the management of fish resources and water quality in the lakes along the lower reach of the Changjiang (Yangtze) River basin.

     

Maximum Entropy and Random Forest Modeling of Mineral Potential: Analysis of Gold Prospectivity in the Hezuo–Meiwu District,West Qinling Orogen,China

Natural Resources Research - This study tested and compared the mineral potential mapping capabilities of the random forest (RF) and maximum entropy (MaxEnt) algorithms using gold deposit...     

Sea Level Prediction in the Yellow Sea From Satellite Altimetry With a Combined Least Squares-Neural Network Approach

Accessible high-quality observation datasets and proper modeling process are critically required to accurately predict sea level rise in coastal areas. This study focuses on developing and validating a combined least squares-neural network approach applicable to the short-term prediction of sea level variations in the Yellow Sea, where the periodic terms and linear trend of sea level change are fitted and extrapolated using the least squares model, while the prediction of the residual terms is performed by several different types of artificial neural networks. The input and output data used are the sea level anomalies (SLA) time series in the Yellow Sea from 1993 to 2016 derived from ERS-1/2, Topex/Poseidon, Jason-1/2, and Envisat satellite altimetry missions. Tests of different neural network architectures and learning algorithms are performed to assess their applicability for predicting the residuals of SLA time series. Different neural networks satisfactorily provide reliable results and the root mean square errors of the predictions from the proposed combined approach are less than 2?cm and correlation coefficients between the observed and predicted SLA are up to 0.87. Results prove the reliability of the combined least squares-neural network approach on the short-term prediction of sea level variability close to the coast.     

西南印度洋中脊表层沉积物非碳酸盐组分的粒度特征及其地质意义

The carbonate-free fraction of 20 surface sediments collected from the ultraslow-spreading Southwest Indian Ridge(SWIR) was studied by grain size analysis and mineralogical analysis with X-ray powder diffraction(XRD),stereo microscopy and scanning electron microscopy(SEM). The characteristics of the carbonate-free fraction of the sediments were obtained, and related influential factors were discussed. The results show that the mean grain size of this fraction is in 1.96Φ–8.19Φ, with poorly sorting and unimodal, bimodal or irregular bimodal distribution patterns. Four grain size end members of the fraction are derived with the End Member Model method. The finest end member EM1 shows a significant contribution of terrigenous materials of the aeolian input and sediment carried by the bottom current. End member EM2 with medium size mainly reflects sediment of a siliceous bioclast origin. EM3 and EM4 are interpreted as representing the coarser volcanic materials related to bedrock weathering or volcanic activities. Multi-provenance is the dominant factor controlling the grain size pattern of the carbonate-free fraction of the sediments in that area. In addition, sediment transport processes such as the bottom current and wind are the minor factors that influence the grain size distribution of the carbonate-free fraction sediments.     

模糊聚类定权法对SLR定轨精度的影响

针对卫星激光测距(satellite laser ranging,SLR)精密定轨过程中存在的测站观测数据合理定权问题,将一种改进的模糊聚类算法引入到SLR观测数据定权中。基于国际激光测距服务(International Laser Ranging Service,ILRS)提供的全球SLR测站性能报告,对测站进行近实时滑动分类定权,改变SLR数据处理中权重的经验或者随意性选取模式。经过LAGEOS1卫星2014年1月至2016年12月3年全球SLR实测数据处理的测试。结果表明,当考虑LAGEOS标准点总数、LAGEOS标准点RMS值以及LAGEOS标准点合格率这3项测站质量控制因素确定的测站权值能最大限度地提高卫星定轨精度和观测数据的使用效率,对参与计算的365个3d弧段数据,91.46%弧段精度得到提高,平均提高约3.7mm,且每个测站的定轨残差RMS也得到了降低。这对于正在迈向毫米级测量精度的SLR技术至关重要。     

检定场的机载激光雷达精度评价方法

为了对机载激光雷达测量精度进行科学地评价,保障数据成果质量,满足新型仪器装备计量检测的需要,该文基于空对地检定场圆形标志点,利用平均值法和最小外包圆法对机载激光雷达的平面精度和高程精度进行评价研究。结果表明:针对低空机载激光雷达可以获取高密度的地面点云,可以利用轮廓突出且特殊形状的控制点进行三维精度评价;利用平均值法和最小外包圆法均可以对机载激光雷达进行快速、有效地三维精度评价。     

A comparison of three widely used GPS triple-frequency precise point positioning models

GPS Solutions - The EUREF Permanent Network (EPN) is a network of continuously operating GNSS stations installed throughout the European continent. The EPN Central Bureau (CB) performs the...     

基于ETOPO1数据的全球及重点海域水深统计与分析

由于不同的水深探测手段及海深反演方法适用于不同深度的海域,且全球海域水深分布不均,因此在探测及反演海深之前,需对目标海域的水深分布有一定认识。本文采用ETOPO1模型对全球及部分海域进行统计分析,结果表明,全球及大西洋、印度洋、太平洋区域的水深大多处于3 000—10 000 m,其中3 000—5 000 m水深海域占比较大,因此,在这些海域主要采用重力数据结合船测数据进行反演,同时应注意避开海岸带、岛屿较多、海脊存在的区域;对于水深小于1 000 m的海域,可以根据外部环境,采用多波束船测、水深遥感、机载激光测深等方式进行探测。通过分析及统计全球和重点海域的水深可以为海深探测及海底地形反演方法的选取提供参考。