Uptake of macroelements by the helophytePhalaris arundinacea L.     

Jean Paul Dubois 《Aquatic Sciences - Research Across Boundaries》1994,56(1):70-79

Helophytes are often incorporated into biological wastewater treatment plants. In favourable situations, they can take up large amounts of nutrients. One helophyte, the reed canarygrass (Phalaris arundinacea L.), is fast growing when supplied with sufficient light and nutrients. Experiments were carried out under natural climatic conditions in small plastic tanks filled with sand with regular additions of a balanced and concentrated nutrient solution. In the growing season (May–October), plant production reached 10.5 kg m^–2 of dry biomass, of which 66% was in the aerial parts. Maximum nutrient uptake capacity was reached just after flowering and before senescence (beginning of October): 49% N, 34% P, 52% K and 34% Mg of the input was fixed in the aerial parts, which are easily harvestable. The corresponding values for the below ground parts were 12%, 10%, 11% and 11% respectively. Excretion of K and Mg has been observed when nutrients are translocated to the storage organs.  相似文献   

REPRESENTATION OF SPECTRA BY CONTINUOUS FUNCTIONS     

BJRN K.ALSBERG 《地理学报(英文版)》1993,(3)

A general framework for manipulating spectra as functions in traditional multivariate methods such asPCA and PLS is described.The functional representation is very convenient for compression,ensuringsmoothness and continuity.There are two fundamentally different types of representations:(a)byfunctions and(b)by function coefficients.The use of coefficients is the most practical way of analysis.  相似文献   

岩石化学成分统计分析中的定和变量问题及其解决途径   总被引：2，自引：0，他引：2  

周建文 《岩石学报》1991,7(1):36-43

用岩石化学成分数据之类的定和数组计算相关系数或用于多元统计分析时,由于恒定总数约束的影响,致使结果出现很大的畸变。本文通过定和数组及对应的开数组之间的关系确定了开数组的范围,进而导出“误差对应模型”决定了该开数组,使恒定总数约束影响得以消除,最后用云南金顶铅锌矿的岩石化学分析样作了上述处理,取得了良好的实际效果。  相似文献   

A factor analytic approach to the identification of geomorphic processes from soil particle size characteristics     

Thomas J. East 《地球表面变化过程与地形》1985,10(5):441-463

Q-mode factor analysis of soil particle size data is used to identify the three dominant geomorphic processes responsible for the spatial variability of particle size in a catchment on the basaltic Darling Downs landsurface. Three factors are shown to account for 95 per cent of the textural variability of a suite of transported and sedentary materials. The spatial characteristics of groups of samples associated with the three factors suggests that the three factors are associated with suspended sediment transport and deposition, weathering, and bedload transport and deposition respectively. These interpretations are supported by the detailed graphical analysis of the cumulative particle size curves. The spatially variable influence of the three factors and related processes is given by their respective factor loadings which are mappable for the surface layer materials.  相似文献   

数值模式初值的敏感性程度对四维同化的影响   总被引：3，自引：0，他引：3  

郜吉东  丑纪范 《气象学报》1995,53(4):471-479

用著名的Ｌｏｒｅｎｚ系统作了共轭变分同化的数值试验。发现随着模式对初值敏感性程度的增加，用这种方法得到和模式相协调的初始场愈来愈困难，直到某些情况下的完全失败。这表明四维同化和可预报期限是联系在一起的。另一方面，随着方程不精确程度的增加，变分同化的效果愈来愈差，直到所做的预报无任何意义可言。如果在做变分同化的同时对模式参数也进行反演，就可使得基于Ｌｏｒｅｎｚ系统所做的预报效果大大提高。  相似文献   

区域资料四维同化试验   总被引：3，自引：0，他引：3       下载免费PDF全文

朱宗申  马清云 《应用气象学报》1995,6(1):1-8

根据国家气象中心有限区分析预报系统的基本方案，设计一个以6小时为周期的间歇区域资料四维同化方案，对我国的两次暴雨过程进行两种不同粗细水平分辨率的资料四维同化和短期模式预报的试验。结果表明，由同化方案初值获得的短期预报明显好于LAFS方案的预报结果，高分辨率同化方案对预报的改进更明显。  相似文献   

Impact of Doppler Radar Wind in Simulating the Intensity and Propagation of Rainbands Associated with Mesoscale Convective Complexes Using MM5-3DVAR System     

S. Abhilash  Someshwar Das  S. R. Kalsi  M. Das Gupta  K. Mohankumar  John P. George  S. K. Banerjee  S. B. Thampi  D. Pradhan 《Pure and Applied Geophysics》2007,164(8-9):1491-1509

Pre-monsoon rainfall around Kolkata (northeastern part of India) is mostly of convective origin as 80% of the seasonal rainfall is produced by Mesoscale Convective Systems (MCS). Accurate prediction of the intensity and structure of these convective cloud clusters becomes challenging, mostly because the convective clouds within these clusters are short lived and the inaccuracy in the models initial state to represent the mesoscale details of the true atmospheric state. Besides the role in observing the internal structure of the precipitating systems, Doppler Weather Radar (DWR) provides an important data source for mesoscale and microscale weather analysis and forecasting. An attempt has been made to initialize the storm-scale numerical model using retrieved wind fields from single Doppler radar. In the present study, Doppler wind velocities from the Kolkata Doppler weather radar are assimilated into a mesoscale model, MM5 model using the three-dimensional variational data assimilation (3DVAR) system for the prediction of intense convective events that occurred during 0600 UTC on 5 May and 0000 UTC on 7 May, 2005. In order to evaluate the impact of the DWR wind data in simulating these severe storms, three experiments were carried out. The results show that assimilation of Doppler radar wind data has a positive impact on the prediction of intensity, organization and propagation of rain bands associated with these mesoscale convective systems. The assimilation system has to be modified further to incorporate the radar reflectivity data so that simulation of the microphysical and thermodynamic structure of these convective storms can be improved.  相似文献   

A One-dimensional Ensemble Forecast and Assimilation System for Fog Prediction     

M. D. Müller  C. Schmutz  E. Parlow 《Pure and Applied Geophysics》2007,164(6-7):1241-1264

A probabilistic fog forecast system was designed based on two high resolution numerical 1-D models called COBEL and PAFOG. The 1-D models are coupled to several 3-D numerical weather prediction models and thus are able to consider the effects of advection. To deal with the large uncertainty inherent to fog forecasts, a whole ensemble of 1-D runs is computed using the two different numerical models and a set of different initial conditions in combination with distinct boundary conditions. Initial conditions are obtained from variational data assimilation, which optimally combines observations with a first guess taken from operational 3-D models. The design of the ensemble scheme computes members that should fairly well represent the uncertainty of the current meteorological regime. Verification for an entire fog season reveals the importance of advection in complex terrain. The skill of 1-D fog forecasts is significantly improved if advection is considered. Thus the probabilistic forecast system has the potential to support the forecaster and therefore to provide more accurate fog forecasts.  相似文献   

A data-based regional scale autoregressive rainfall-runoff model: a study from the Odra River     

Tomasz Niedzielski 《Stochastic Environmental Research and Risk Assessment (SERRA)》2007,21(6):649-664

This paper aims to compare the performances of multivariate autoregressive (MAR) techniques and univariate autoregressive (AR) methods applied to regional scale rainfall-runoff modelling. We focus on the case study from the upper and middle reaches of the Odra River with its main tributaries in SW Poland. The rivers drain both the mountains (the Sudetes) and the lowland (Nizina Śląska). The region is exposed to extreme hydrologic and meteorological events, especially rain-induced and snow-melt floods. For the analysis, four hydrologic and meteorological variables are chosen, i.e., discharge (17 locations), precipitation (7 locations), thickness of snow cover (7 locations) and groundwater level (1 location). The time period is November 1971–December 1981 and the temporal resolution of the time series is of 1 day. Both MAR and AR models of the same orders are fitted to various subsets of the data and subsequently forecasts of discharge are derived. In order to evaluate the predictions the stepwise procedure is applied to make the validation independent of the specific sample path of the stochastic process. It is shown that the model forecasts peak discharges even 2–4 days in advance in the case of both rain-induced and snow-melt peak flows. Furthermore, the accuracy of discharge predictions increases if one analyses the combined data on discharge, precipitation, snow cover, and groundwater level instead of the pure discharge multivariate time series. MAR-based discharge forecasts based on multivariate data on discharges are more accurate than AR-based univariate predictions for a year with a flood, however, this relation is reverse in the case of the free-of-flooding year. In contrast, independently of the occurrence of floods within a year, MAR-based discharge forecasts based on discharges, precipitation, snow cover, and groundwater level are more precise than AR-based predictions.  相似文献   

基于进化方向遗传算法的四维变分资料同化方法   总被引：7，自引：5，他引：7  

王顺凤  沈桐立  张建伟  孙麟平 《南京气象学院学报》2002,25(6):740-746

数值天气预报模式初始时刻要素场的变分同化问题是一个非线性最优化问题。利用进化方向遗传算法（EDGA）求解该最优化问题，并对理想初始场作数值模拟，结果表明模拟的效果较好。  相似文献