Long-term hydrology and aquatic biogeochemistry data from H. J. Andrews Experimental Forest,Cascade Mountains,Oregon     

Sherri L. Johnson  Don Henshaw  Greg Downing  Steve Wondzell  Mark Schulze  Adam Kennedy  Greg Cohn  Stephanie A. Schmidt  Julia A. Jones 《水文研究》2021,35(5):e14187

The H. J. Andrews Experimental Forest (HJA) encompasses the 6400 ha Lookout Creek watershed in western Oregon, USA. Hydrologic, chemistry and precipitation data have been collected, curated, and archived for up to 70 years. The HJA was established in 1948 to study the effects of harvest of old-growth conifer forest and logging-road construction on water quality, quantity and vegetation succession. Over time, research questions have expanded to include terrestrial and aquatic species, communities and ecosystem dynamics. There are nine small experimental watersheds and 10 gaging stations in the HJA, including both reference and experimentally treated watersheds. Gaged watershed areas range from 8.5 to 6242 ha. All gaging stations record stage height, water conductivity, water temperature and above-stream air temperature. At nine of the gage sites, flow-proportional water samples are collected and composited over 3-week intervals for chemical analysis. Analysis of stream and precipitation chemistry began in 1968. Analytes include dissolved and particulate species of nitrogen and phosphorus, dissolved organic carbon, pH, specific conductance, suspended sediment, alkalinity, and major cations and anions. Supporting climate measurements began in the 1950s in association with the first small watershed experiments. Over time, and following the initiation of the Long Term Ecological Research (LTER) grant in 1980, infrastructure expanded to include a set of benchmark and secondary meteorological stations located in clearings spanning the elevation range within the Lookout Creek watershed, as well as a large number of forest understory temperature stations. Extensive metadata on sensor configurations, changes in methods over time, sensor accuracy and precision, and data quality control flags are associated with the HJA data.  相似文献   

Seismic ground-roll noise attenuation using deep learning     

Harpreet Kaur  Sergey Fomel  Nam Pham 《Geophysical Prospecting》2020,68(7):2064-2077

We propose to adopt a deep learning based framework using generative adversarial networks for ground-roll attenuation in land seismic data. Accounting for the non-stationary properties of seismic data and the associated ground-roll noise, we create training labels using local time–frequency transform and regularized non-stationary regression. The basic idea is to train the network using a few shot gathers such that the network can learn the weights associated with noise attenuation for the training shot gathers. We then apply the learned weights to test ground-roll attenuation on shot gathers, that are not a part of training input to obtain the desired signal. This approach gives results similar to local time–frequency transform and regularized non-stationary regression but at a significantly reduced computational cost. The proposed approach automates the ground-roll attenuation process without requiring any manual input in picking the parameters for each shot gather other than in the training data. Tests on field-data examples verify the effectiveness of the proposed approach.  相似文献   

Characterization of sudden and sustained base flow jump hydrologic behaviour in the humid seasonal tropics of the Panama Canal Watershed     

Yanyan Cheng  Fred L. Ogden  Jianting Zhu 《水文研究》2020,34(3):569-582

Base flows are important for tropical regions with pronounced dry seasons, which are facing increasing water demands. Base flow generation, however, is one of the most challenging hydrological processes to characterize in the tropics. In many years during the May–December wet season in the Panama Canal Watershed (PCW), base flows in rivers abruptly increase. This increase persists until the start of the December–April dry season. Understanding this unusual base flow jump (BFJ) behaviour is critical to improve water provisioning in the seasonal tropics, especially during droughts and extended dry seasons. This study developed an integrated approach combining piecewise regression on cumulative average base flow and sensitivity analysis to calculate the timing and magnitude of BFJ. Rainfall, forest cover, mean land surface slope, catchment area, and estimated subsurface storage were tested as predictors for the occurrence and magnitude of the BFJs in seven subcatchments of the PCW. Sensitivity analysis on correlated predictors allowed ranking of predictor contributions due to isolated and cross-correlation effects. Correlations between observed BFJs and BFJs predicted by watershed and rainfall-related predictors were 0.92 and 0.65 for BFJ timing and magnitude, respectively. Forest cover was the second most significant predictor after cumulative rainfall for jump magnitude, owing to larger subsurface storage and groundwater recharge in forests than pastures. Catchments in the mountainous eastern PCW always generated larger jumps due to their higher rainfall and greater forest cover than the western PCW catchments. The cross-correlations between predictors contributed to more than 50% of the jump variances. The results demonstrate the importance of rainfall gradient and catchment characteristics in affecting the sudden and sustained BFJs, which can help inform land management decisions intended to enhance water supplies in the tropics. This study underscores the need for more research to further understand the hydrological processes involved in the BFJ phenomenon, including better BFJ models and field characterizations, to help improve tropical ecosystem services under a changing environment.  相似文献   

Using hysteretic behaviour and hydrograph classification to identify hydrological function across the “hillslope–depression–stream” continuum in a karst catchment     

Runrun Zhang  Xi Chen  Zhicai Zhang  Chris Soulsby 《水文研究》2020,34(16):3464-3480

In cockpit karst landscapes, fluxes from upland areas contribute large volumes of water to low-lying depressions and stream flow. Hydrograph hysteresis and similarity between monitoring sites is important for understanding the space–time variability of hydrologic responses across the “hillslope–depression–stream” continuum. In this study, the hysteretic feature of hydrographs was assessed by characterizing the loop-like relationships between responses at upstream sites relative to subsurface discharge at the outlet of a small karst catchment. A classification of hydrograph responses based on the multi-scale smoothing Kernel -derived distance classifies the hydrograph responses on the basis of similarities between hillslope and depression sites, and those at the catchment outlet. Results demonstrate that the temporal and spatial variability of hydrograph hysteresis and similarity between hillslope flow and outlet stream flow can be explained by the local heterogeneity of depression aquifer. Large depression storage deficits emerging in the highly heterogeneous aquifer produce strong hysteresis and multiple relationships of upstream hydrographs relative to the outlet subsurface discharge. In contrast, when depression storage deficits are filled during consecutive rainfall events, depression hydrographs at the high permeability sites are almost synchronous or exhibit a monotonous function with the hydrographs at the outlet. This reduced hydrograph hysteresis enhances preferential flow paths in fractured rocks and conduits that can accelerate the hillslope flow to the outlet. Therefore, classification of hydrograph similarities between any upstream sites and the catchment outlet can help to identify the dominant hydrological functions in the heterogeneous karst catchment.  相似文献   

Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data     

《International Journal of Applied Earth Observation and Geoinformation》2020

Most studies have the achieved rapid and accurate determination of soil organic carbon (SOC) using laboratory spectroscopy; however, it remains difficult to map the spatial distribution of SOC. To predict and map SOC at a regional scale, we obtained fourteen hyperspectral images from the Gaofen-5 (GF-5) satellite and decomposed and reconstructed the original reflectance (OR) and the first derivative reflectance (FDR) using discrete wavelet transform (DWT) at different scales. At these different scales, as inputs, we selected the 3 optimal bands with the highest weight coefficient using principal component analysis and chose the normalized difference index (NDI), ratio index (RI) and difference index (DI) with the strongest correlation with the SOC content using a contour map method. These inputs were then used to build regional-scale SOC prediction models using random forest (RF), support vector machine (SVM) and back-propagation neural network (BPNN) algorithms. The results indicated that: 1) at a low decomposition scale, DWT can effectively eliminate the noise in satellite hyperspectral data, and the FDR combined with DWT can improve the SOC prediction accuracy significantly; 2) the method of selecting inputs using principal component analysis and a contour map can eliminate the redundancy of hyperspectral data while retaining the physical meaning of the inputs. For the model with the highest prediction accuracy, the inputs were all derived from the wavelength range of SOC variations; 3) the differences in prediction accuracy among the different prediction models are small; and 4) the SOC prediction accuracy using hyperspectral satellite data is greatly improved compared with that of previous SOC prediction studies using multispectral satellite data. This study provides a highly robust and accurate method for predicting and mapping regional SOC contents.  相似文献   

面向数字孪生城市的智能化全息测绘   总被引：2，自引：0，他引：2  

顾建祥  杨必胜  董震  杨常红 《测绘通报》2020,(6):134-140

以大数据、物联网、人工智能、虚拟现实、云计算、智能驾驶等新技术为代表的信息化浪潮席卷全球，数字世界与物理世界正形成两大平行发展、相互作用的体系，数字孪生技术应运而生。随着物联网技术（IOT）的发展，数字孪生的理念被引入到智慧城市建设中来，深刻影响着城市规划、建设与治理。笔者所在单位面向数字孪生城市和自然资源统一监管对测绘地理信息的新需求，在全国开创性地开展了面向数字孪生城市的智能化全息测绘试点工作。本文结合上海市智能化全息测绘试点工作，从数字孪生城市、数字孪生城市对地理信息的新需求、智能化全息测绘关键技术及测绘成果等方面展开了论述，重点介绍了智能化全息测绘的技术体系和产品体系，以及在社会各领域的应用成果。  相似文献   

运用GD-PBIBD编码的矢量空间数据数字指纹算法     

陈金萍  张黎明  蒋美容  王昊 《测绘通报》2020,(8):81

针对矢量空间数据叛逆者追踪难及编码效率低的问题，本文提出了一种运用GD-PBIBD码的指纹算法。首先运用GD-PBIBD构造指纹编码，将待嵌入指纹序列运用Logistic映射置乱，通过D-P算法提取矢量空间数据的特征点，对特征点实施DFT变换得到相位系数和幅度系数；然后运用QIM方法将指纹嵌入DFT变换域的幅度系数上；最后应用DFT逆变换得到含指纹的矢量空间数据。试验选取部分中国路网数据和某区域绿地数据，运用该算法嵌入指纹后，对其进行线性和非线性模拟攻击，成功提取指纹序列，利用汉明距离追踪出合谋者。该算法编码构造简单，在码长一定的情况下，较BIBD码可容纳更多的用户，效率高；算法抗单用户指纹攻击及多重攻击的稳健性较好，也能够抵抗多用户最小值和最大最小值攻击，追踪到所有叛逆者，可用于矢量空间数据版权保护，为矢量空间数据叛逆者追踪提供依据。  相似文献   

基于OSM的浮动车轨迹数据校正方法     

胡向勇  郭圆 《测绘通报》2020,(10):139

浮动车轨迹数据具有覆盖范围广、更新周期短、获取成本低等特点，对于地图的生产和更新具有重要意义，但是由于受到卫星信号被遮挡及多路径效应的影响，其精度普遍较低。本文采用一种基于OSM作为参考数据的方式对浮动车轨迹数据进行校正。首先通过一种分层时空地图匹配的方式将轨迹数据与OSM进行匹配；然后采用引力模型对数据进行校正；最后在武汉市出租车轨迹数据上进行了试验。结果表明，本文提出的数据校正方法可以有效地提高浮动车轨迹数据的精度。  相似文献   

基于点云数据的不规则文物三维重建——以经幢为例     

喜文飞  李灵索  杨勇  李国柱  李春梅  李金平 《测绘通报》2020,(12):87-89

海量点云数据可以较好地构建文物的三维建模，针对文物复杂的表面结构，传统的算法很难达到精细建模，为了解决复杂模型表面的空间三角网构网问题，本文结合空间三角形的法向量构建三角网，以空间三角网表面的曲率为约束条件，构建物体表面的空间三角网，然后对构建的空间三角网进行精细建模。以昆明市文物——经幢为例进行三维重建试验，结果表明，新方法适合室内文物的三维建模，可以达到较好的效果。  相似文献   

BDS卫星钟差半参数平差模型异常数据探测与处理     

李文涛  颜雄  夏磊  任青阳  陈洁  潘雄 《测绘学报》2020,49(1):55-64

针对北斗卫星钟差数据中出现钟跳、粗差等异常数据频次较高的问题,将半参数平差模型引入BDS的钟差数据的处理过程中。首先,在考虑系统误差的同时,改进了常用的钟差模型;其次,综合考虑异常数据和系统误差,利用补偿最小二乘原理和极值求解方法,详细推导了分离异常数据前后参数和非参数估计值与相应观测值改正数的关系表达式,实现了异常数据的定值、参数求解和系统误差分离。在此基础上,引入Cook距离,给出了利用参数分量和非参数分量的Cook距离及混合Cook距离,去判断异常值的位置,并给出了一些参数的选取方法及相应的处理措施,实现了卫星钟差异常数据的定位和定值以及部分系统误差的分离。最后,采用武汉大学GNSS中心提供的采样间隔为5 min的北斗卫星精密钟差数据,将本文方法与常用方法进行了试验对比。试验结果表明,本文方法能够有效地识别并处理卫星钟差数据中的异常值,有效克服了基于经验阈值钟差异常数据探测方法的不足,且该方法对于量级较小的异常钟差数据也有很好的探测效果,一定程度丰富了现有的BDS钟差数据质量控制方法。  相似文献