Dissolved organic nitrogen dynamics in the North Sea: A time series analysis (1995–2005)

Dissolved organic nitrogen (DON) dynamics in the North Sea was explored by means of long-term time series of nitrogen parameters from the Dutch national monitoring program. Generally, the data quality was good with little missing data points. Different imputation methods were used to verify the robustness of the patterns against these missing data. No long-term trends in DON concentrations were found over the sampling period (1995–2005). Inter-annual variability in the different time series showed both common and station-specific behavior. The stations could be divided into two regions, based on absolute concentrations and the dominant times scales of variability. Average DON concentrations were 11 μmol l⁻¹ in the coastal region and 5 μmol l⁻¹ in the open sea. Organic fractions of total dissolved nitrogen (TDN) averaged 38 and 71% in the coastal zone and open sea, respectively, but increased over time due to decreasing dissolved inorganic nitrogen (DIN) concentrations. In both regions intra-annual variability dominated over inter-annual variability, but DON variation in the open sea was markedly shifted towards shorter time scales relative to coastal stations. In the coastal zone a consistent seasonal DON cycle existed with high values in spring–summer and low values in autumn–winter. In the open sea seasonality was weak. A marked shift in the seasonality was found at the Dogger Bank, with DON accumulation towards summer and low values in winter prior to 1999, and accumulation in spring and decline throughout summer after 1999. This study clearly shows that DON is a dynamic actor in the North Sea and should be monitored systematically to enable us to understand fully the functioning of this ecosystem.     

基于注意力机制与自适应时序分解的气温预报模型

针对传统方法在捕捉气象序列长期依赖关系及泛化性能上的不足,提出了一种基于稀疏注意力与自适应时序分解的气温预报模型（ATFSAS）。该模型整体采用编码器 解码器架构,结合稀疏注意力机制以有效捕捉气象观测数据间的长期依赖性。为减少编码过程中造成的冗余,提出了一种信息蒸馏方法。通过结合多层解码器与自适应时序分解单元,逐步细化预报信号中的周期性和趋势性分量,实现了较为精准的气温预报。基于德国耶拿气象数据集,进行24 h精细化气温预报,其平均绝对误差为1.7108℃。基于中国地面气候资料日值数据集,进行中短期日平均气温预报和多地区单日平均气温预报,相比传统模型LSTM,ATFSAS模型预报结果的平均绝对误差分别提升了35.56%和23.66%。     

下扬子地区幕府山组陆缘海-台地黑色细粒沉积岩系沉积学和孔隙结构特征

黑色细粒沉积岩系沉积学和孔隙结构研究对于沉积环境恢复、页岩气储层评价和有利储层预测具有重要意义.利用下扬子地区最新完钻的XYZ-1钻井资料,综合钻井岩心、岩石薄片、XRD分析、氩离子-场扫描电镜等手段,开展幕府山组细粒沉积岩系的沉积学和孔隙结构研究.结果表明,幕府山组岩性组成以块状、纹层状深色(碳质)泥岩、浅灰色纹层状...     

中国沿海赤潮灾害时间序列特征的模拟与预测

对赤潮灾害时间序列的特征分析是进行赤潮灾害防灾减灾工作的基础,对未来赤潮灾害的预测具有重要意义.通过观察发现中国沿海赤潮灾害年发生频次和分布面积的时间序列(2004-2019年)均呈现出趋势项和周期项并存的特征,因此利用灰色-周期外延组合预测模型对两个序列中的趋势项和周期项进行提取,模型的拟合度分别达到95.20％和9...     

用树木年轮重建伊犁南天山北坡西部的降水量序列

根据采自伊犁地区南天山北坡11个采点的树木年轮样本,建立了每个采点的3种年表。通过单相关普查发现,标准化树轮年表序列与当年1~5月的降水显著相关。分析表明该时段降水与树木年轮生长呈正相关具有明确的树木生理学意义。利用新源上限(XNAUt)、昭苏上限(ZUt、ZUt 2)和特克斯下限(TLt)4个标准化树轮年表序列可较好地重建该区域在该时段的降水量。经交叉检验,所得重建方程是稳定可靠的,重建的降水序列是可信的。通过分析发现:伊犁地区南天山北坡300年以来1~5月的降水大致经历了6个偏湿阶段和6个偏干阶段;有2.0~2.8年、24.8年、28.3年、33年、99年的变化准周期;在1909年发生由多向少的突变;1740年、1870年发生由少向多的突变,其中又以1870年前后的突变最为明显。     

Can 234U–230Th dating be used to date large semi‐arid tufas? Challenges from a study in the Naukluft Mountains,Namibia

The large, extensive tufa deposits of the semi‐arid Naukluft Mountains, Namibia are potentially important palaeoenvironmental indicators in an area with few proxy records. Tufas are reliable indicators of increased moisture availability, and have been shown to be amenable to ²³⁴U–²³⁰Th dating, although two challenges are detrital contamination and open‐system behaviour. Densely cemented tufa facies are good candidates for dating, minimising these problems. We report attempts to date five densely‐cemented units, which are only found rarely within the Naukluft deposits. We applied a detailed methodology using multiple subsample analysis, measurement of insoluble residues, application of ‘isochron’ mixing lines, and attempted open‐systems modelling, alongside observations of micromorphology and cathodoluminescence in order to assess the validity of any obtained dates. Surprisingly, densely cemented tufas were found not always to be suitable for dating. Two units contained detrital contamination, which could not be corrected for using a single leachate correction or ‘isochron’ methods. Two units contained ‘excess ²³⁰Th’. This could result under a closed‐system if initial (²³⁴U/²³⁸U) was sufficiently high. Alternatively this may be the result of open‐system behaviour, and loss of uranium, or incorporation of initial unsupported ²³⁰Th, which render samples unsuitable for ²³⁴U–²³⁰Th dating. Micromorphological appearance and cathodoluminescence behaviour are used to explore these possibilities. This study exemplifies the need for careful sample selection, and highlights the importance of analysing multiple subsamples from any tufa sample. The detailed methodology applied proves to be a powerful tool for identifying the range of problems that can be encountered when selecting suitable candidate samples for successful dating. It also shows that semi‐arid tufa sequences may contain very little material suitable for dating. A reliable age of c 80 ka was obtained for a banded unit within a large fluvial barrage, with less reliable dates suggesting tufa deposition during times since >350 ka through to the late Holocene. Copyright © 2010 John Wiley & Sons, Ltd.     

Screening the current soil drainage class map of Flanders (Belgium) for its predictive quality

The predictive quality of the current drainage class map of Flanders was evaluated using data from two monitoring networks: one with good spatial coverage but poor temporal coverage and another with better temporal but poor spatial coverage. We combine both networks to obtain 1678 point predictions for mean highest water (MHW) and mean lowest water (MLW) tables by applying time series modelling and total least squares regression. The resulting MHW and MLW point data set was used to evaluate the currency of the existing map and to identify regional differences. The quality of the current map is moderate, and large differences occur between regions. Especially the Campine region shows large and systematic differences, whereas the southeastern hills and chalk–loam region is relatively accurate. If more weight is given to errors in the wetter drainage classes, about 50% of the area of Flanders would benefit from remapping. Copyright © 2011 John Wiley & Sons, Ltd.     

Multifractal behaviour of long‐term karstic discharge fluctuations

Karstic watersheds are highly complex hydrogeological systems that are characterized by a multiscale behaviour corresponding to the different pathways of water in these systems. The main issue of karstic spring discharge fluctuations consists in the presence and the identification of characteristic time scales in the discharge time series. To identify and characterize these dynamics, we acquired, for many years at the outlet of two karstic watersheds in South of France, discharge data at 3‐mn, 30‐mn and daily sampling rate. These hydrological records constitute to our knowledge the longest uninterrupted discharge time series available at these sampling rates. The analysis of the hydrological records at different levels of detail leads to a natural scale analysis of these time series in a multifractal framework. From a universal class of multifractal models based on cascade multiplicative processes, the time series first highlights two cut‐off scales around 1 and 16 h that correspond to distinct responses of the aquifer drainage system. Then we provide estimates of the multifractal parameters α and C₁ and the moment of divergence q_D corresponding to the behaviour of karstic systems. These results constitute the first estimates of the multifractal characteristics of karstic spingflows based on 10 years of high‐resolution discharge time series and should lead to several improvements in rainfall‐karstic springflow simulation models. Copyright © 2012 John Wiley & Sons, Ltd.     

Pulse generation models for daily intermittent streamflows / Modèles de génération d’impulsions pour des débits journaliers intermittents

Abstract

Abstract Generating pulses and then converting them into flow are two main steps of daily streamflow generation. Three pulse generation models have been proposed on the basis of Markov chains for the purpose of generating daily intermittent streamflow time series in this study. The first one is based on two two-state Markov chains, whereas the second uses a three-state Markov chain. The third model uses harmonic analysis and fits Fourier series to the three-state Markov chain. Results for a daily intermittent streamflow data series show a good performance of the proposed models.     

Discrete wavelet‐based trend identification in hydrologic time series

Trend identification is a substantial issue in hydrologic series analysis, but it is also a difficult task in practice due to the confusing concept of trend and disadvantages of methods. In this article, an improved definition of trend was given as follows: ‘a trend is the deterministic component in the analysed data and corresponds to the biggest temporal scale on the condition of giving the concerned temporal scale’. It emphasizes the intrinsic and deterministic properties of trend, can clearly distinguish trend from periodicities and points out the prerequisite of the concerned temporal scale only by giving which the trend has its specific meaning. Correspondingly, the discrete wavelet‐based method for trend identification was improved. Differing from those methods used presently, the improved method is to identify trend by comparing the energy difference between hydrologic data and noise, and it can simultaneously separate periodicities and noise. Furthermore, the improved method can quantitatively estimate the statistical significance of the identified trend by using proper confidence interval. Analyses of both synthetic and observed series indicated the identical power of the improved method as the Mann–Kendall test in assessing the statistical significance of the trend in hydrologic data, and by using the former, the identified trend can adaptively reflect the nonlinear and nonstationary variability of hydrologic data. Besides, the results also showed the influences of three key factors (wavelet choice, decomposition level choice and noise content) on discrete wavelet‐based trend identification; hence, they should be carefully considered in practice. Copyright © 2012 John Wiley & Sons, Ltd.