COMPARISON OF TWO AUTOREGRESSIVE MODELS FOR MONTHLY STREAM FLOW GENERATION1

ABSTRACT: Two autoregressive models for monthly stream flow generation are compared based on the reproduction of the historical record in terms of several important statistics such as the mean, standard deviation, skewness coefficient, correlation coefficient, and the reservoir storage components. In the comparison, both theoretical considerations and practical applications are employed to evaluate the performance of each model.     

Estimation of the spatial covariance in Universal Kriging: Application to forest inventory

This paper presents a simple least squares procedure for estimating the spatial covariance and compares it with the numerically more difficult restricted maximum likelihood procedure. Thereafter, it compares design-based and kriging techniques for the estimation of spatial averages in the context of double sampling, as used in forest inventory, where terrestrial sample plots are combined with auxiliary information based on aerial photographs. A case study illustrates the theory.     

Prenatal diagnosis and psychological distress: Amniocentesis or chorionic villus biopsy?

The psychological reactions of 211 women undergoing prenatal diagnosis (PND) with amniocentesis (group A, n = 122) or chorionic villus biopsy (group V, n = 90) were exmained by questionnaires and interviews. The distress experienced while waiting for the test, during the test procedure, and while waiting for the result was reported by the women, both in questionnaires and in interviews. In the questionnaires, no difference between the two diagnostic methods was observed. In the interviews, however, the women undergoing amniocentesis appeared significantly more distressed by the procedure. In group A 97 per cent and in group V 100 per cent wished a method which, like chorionic villus biopsy, could be used in the first weeks of pregnancy. The risk of miscarriage was, as described in other studies, regarded as a serious threat by the pregnant women.     

Evaluating Alternative Temporal Survey Designs for Monitoring Wetland Area and Detecting Changes Over Time in California

Evaluation of wetland extent and changes in extent is a foundation of many wetland monitoring and assessment programs. Probabilistic sampling and mapping provides a cost‐effective alternative to comprehensive mapping for large geographic areas. One unresolved challenge for probabilistic or design‐based approaches is how best to monitor both status (e.g., extent at a single point in time) and trends (e.g., changes in extent over time) within a single monitoring program. Existing wetland status and trends (S&T) monitoring programs employ fixed sampling locations; however, theoretical evaluation and limited implementation in other landscape monitoring areas suggest that alternative designs could increase statistical efficiency and overall accuracy. In particular, designs that employ both fixed and nonfixed sampling locations (alternately termed permanent and temporary samples), termed sampling with partial replacement (SPR), are considered to efficiently and effectively balance monitoring current status with detection of trends. This study utilized simulated sampling to assess the performance of fixed sampling locations, SPR, and strictly nonfixed designs for monitoring wetland S&T over time. Modeled changes in wetland density over time were used as inputs for sampling simulations. In contrast to previous evaluations of SPR, the results of this study support the use of a fixed sampling design and show that SPR may underestimate both S&T.     

Resolution and Analysis of Spatial Variations and Patterns in an Urban Lake with Rapid Profiling Instrumentation

Rapid response vertical profiling instrumentation was used to document spatial variability and patterns in a small urban lake, Onondaga Lake, associated with multiple drivers. Paired profiles of temperature, specific conductance (SC), turbidity (T_n), fluorometric chlorophyll a (Chl_f), and nitrate nitrogen (NO₃^?) were collected at >30 fixed locations (a “gridding”) weekly, over the spring to fall interval of several years. These gridding data are analyzed (1) to characterize phytoplankton (Chl_f) patchiness in the lake's upper waters, (2) to establish the representativeness of a single long‐term site for monitoring lake‐wide conditions, and (3) to resolve spatial patterns of multiple tracers imparted by buoyancy effects of inflows. Multiple buoyancy signatures were resolved, including overflows from less dense inflows, and interflows to metalimnetic depths and underflows to the bottom from the plunging of more dense inputs. Three different metrics had utility as tracers in depicting the buoyancy signatures as follows: (1) SC, for salinity‐enriched tributaries and the more dilute river that receives the lake's outflow, (2) T_n, for the tributaries during runoff events, and (3) NO₃^?, for the effluent of a domestic waste treatment facility and from the addition of NO₃^? solution to control methyl mercury. The plunging inflow phenomenon, which frequently prevailed, has important management implications.     

基于生活垃圾分类的厨余垃圾采样方法研究

与复杂的混合生活垃圾相比,厨余垃圾成分较单一,需要针对性的采样方法.本研究基于生活垃圾分类背景,在《生活垃圾采样和分析方法》(CJ/T 313—2009)的基础上,就采样位点和采样节点数对分类存放的厨余垃圾采样的影响展开研究.研究结果表明,仅采集垃圾桶中间位点的样品不具有代表性,不同情景应有不同的采样策略.当厨余垃圾流节点数少于2时需采集所有节点,当厨余垃圾流节点数为3~7时需采集2个节点,而当厨余垃圾节点数为8~18时需采集3个节点,均少于CJ/T 313—2009中要求的采样节点数.厨余垃圾的总量增大,则其最少采样节点数相应上升,但最少采样点受到厨余垃圾流节点数的制约.     

基于BERT-BILSTM-CRF模型的电力行业事故文本智能分析*

为解决电力行业事故报告文本较长、语义复杂,难以进行有效文本识别问题,提出1种以BERT作为底层的预训练模型,并设计1种双重注意力机制编码器,结合BILSTM-CRF深度挖掘事故文本语义特征,从而实现文本智能分析。首先构建电力词典,通过对BERT预训练,进行BIO标注,然后引入BILSTM-CRF模型实现对文本标签智能分类,最后将该模型与现行其他4种深度学习模型进行对比。研究结果表明:该模型智能识别精确率、召回率及F1值(查准率)均达到约97%,较其他4种模型中效果最好的模型分别提高0.02,0.03,0.02。研究结果可为电力行业事故报告文本分析提供1种新思路。     

Using GIS to Generate Spatially Balanced Random Survey Designs for Natural Resource Applications

Sampling of a population is frequently required to understand trends and patterns in natural resource management because financial and time constraints preclude a complete census. A rigorous probability-based survey design specifies where to sample so that inferences from the sample apply to the entire population. Probability survey designs should be used in natural resource and environmental management situations because they provide the mathematical foundation for statistical inference. Development of long-term monitoring designs demand survey designs that achieve statistical rigor and are efficient but remain flexible to inevitable logistical or practical constraints during field data collection. Here we describe an approach to probability-based survey design, called the Reversed Randomized Quadrant-Recursive Raster, based on the concept of spatially balanced sampling and implemented in a geographic information system. This provides environmental managers a practical tool to generate flexible and efficient survey designs for natural resource applications. Factors commonly used to modify sampling intensity, such as categories, gradients, or accessibility, can be readily incorporated into the spatially balanced sample design.