Pollution history and recovery of a boreal lake exposed to a heavy bleached pulping effluent load

We examined the effects of heavy pulp mill discharges on the Lake Lievestuoreenjärvi ecosystem and the later recovery of diatom and chironomid communities from age-dated short core samples. Beginning in 1927 the lake received a heavy effluent load from a sulphite pulp mill. Except for the recession during the Second World War and the temporary closure of the mill from 1967 to 1971, the industrial load, containing large quantities of nutrients, organic matter and toxic compounds, increased continuously. In the early 1980s, laboratory documents were falsified by the directors of the mill and the systematic illegal effluent overload led to a collapse of the whole lake ecosystem. In 1985, the outdated plant was finally closed down. Based on the assessment of chemical properties and biological remains of the sediment, we distinguished five developmental phases in the ecological state of the lake. In the pre-industrial phase, the pelagic and profundal benthic communities were dominated by species preferring ultraoligotrophic or oligotrophic lakes. Concomitant with the increasing discharge and deposition of chlorine compounds, resin acids, and mercury, as well as strong acidity and hypolimnetic and epilimnetic anoxia, the ecological status changed in a short period from excellent to bad. Finally, in the early 1960s, the majority of the lake was virtually dead and the aquatic life survived only in the uppermost littoral zone. Since 1985, a fast recovery in the water quality has led to a strong, but temporary eutrophy in pelagic communities. The main peak of eutrophication was caused by the invasion of a species new to the lake,Aulacoseira granulata var.angustissima. Later, the pelagic communities shifted towards oligotrophy, but the original, pre-industrial status has not been re-established. The profundal benthic communities have not achieved the pre-industrial structure, but at present indicate mesotrophy.     

海洋动物体石油烃污染评价标准参考值的探讨

目前,国内外尚无颁布任何海洋生物石油污染评价标准,为了满足海洋生物石油污染评价的需要,本文采用综合分析与毒理学分析相结合的方法,探讨和提出了海洋动物石油污染评价标准参考值,海洋鱼类、贝类和甲壳类的石油污染评价标准参考值（干重）分别为１５、７０ 和２５ ｍ ｇ／ｋｇ。     

季节内印度洋-西太平洋对流涛动对次季节-季节尺度大气可预报性的影响

利用非线性局部Lyapunov指数和条件非线性局部Lyapunov指数定量估计了季节内印度洋-西太平洋对流涛动（IPCO）和实时多变量Madden-Julian指数（RMM指数）可预报期限,量化了季节内IPCO对S2S尺度大气可预报性的贡献,深入研究了季节内IPCO演变下S2S尺度可预报期限空间分布的变化规律。结果表明：（1）与RMM指数相比,季节内IPCO指数可预报性更强,可预报期限达到31天左右,比RMM指数高出2周以上;（2）印度洋-西太平洋区域S2S尺度大气可预报性最强,可预报期限达到30天以上,其中季节内IPCO是该地区的主要可预报性来源之一,其贡献达到6天,占总可预报期限的25%以上;（3）随着季节内IPCO的演变,印度洋-西太平洋地区S2S尺度大气可预报性有空间结构变化,表现为可预报期限异常的传播和振荡。S2S尺度大气可预报期限正负异常沿季节内IPCO传播路径,一支以赤道中西印度洋为起点北传至印度半岛,一支向东传播,经过海洋性大陆到赤道西太平洋后向北传播,到达日本南部。同时,可预报性异常的传播在在东印度洋和西太平洋表现出反向变化的特征,形成东西两极振荡,当季节内IPCO向正位相发展时,东印度洋具有更强的可预报性,西太平洋具有更弱的可预报性,反之亦然。季节内IPCO的发展（衰退）可使东印度洋（西太平洋）S2S尺度大气可预报性更强,表明模式预报技巧对此具有更大的提升空间。     

Measures of Parameter Uncertainty in Geostatistical Estimation and Geostatistical Optimal Design

Studies of site exploration, data assimilation, or geostatistical inversion measure parameter uncertainty in order to assess the optimality of a suggested scheme. This study reviews and discusses measures for parameter uncertainty in spatial estimation. Most measures originate from alphabetic criteria in optimal design and were transferred to geostatistical estimation. Further rather intuitive measures can be found in the geostatistical literature, and some new measures will be suggested in this study. It is shown how these measures relate to the optimality alphabet and to relative entropy. Issues of physical and statistical significance are addressed whenever they arise. Computational feasibility and efficient ways to evaluate the above measures are discussed in this paper, and an illustrative synthetic case study is provided. A major conclusion is that the mean estimation variance and the averaged conditional integral scale are a powerful duo for characterizing conditional parameter uncertainty, with direct correspondence to the well-understood optimality alphabet. This study is based on cokriging generalized to uncertain mean and trends because it is the most general representative of linear spatial estimation within the Bayesian framework. Generalization to kriging and quasi-linear schemes is straightforward. Options for application to non-Gaussian and non-linear problems are discussed.     

Recent evolution of Lake Arreo,northern Spain: influences of land use change and climate

We present a high-resolution, multiproxy reconstruction of the depositional history of Lake Arreo, northern Spain, for the last 60 years. We conducted sedimentological, geochemical and diatom analyses in short cores and made a detailed comparison with regional instrumental climate data (1952–2007), limnological monitoring of the lake (1992–2008) and recent land use changes that affect the lake catchment. Chronology is based on “floating” discontinuous varve counts and ¹³⁷Cs and ¹⁴C dates. Four periods were identified in the Lake Arreo recent history: (1) prior to 1963, varved facies intercalated with fine turbidite deposits, and diatom assemblages dominated by Cyclotella taxa indicate predominantly meromictic conditions, (2) from 1964 to 1978, permanent anoxia persisted in bottom waters, as shown by similar facies and diatom assemblages as before, though detrital layers were coarser, (3) from 1979 to 1994, sediment delivery to the lake increased and laminated, clastic facies were deposited, and (4) from 1995 to 2008, dominance of massive facies and an increase in Fragilaria tenera and Achnanthes minutissima reflect relatively lower lake levels, less frequent bottom anoxia with more frequent water column mixing, similar to modern conditions. The period 1952–1979 was a time of meromixis and varved facies deposition, and was characterized by higher rainfall and less intense agricultural pressure in the watershed. There were two short humid periods (1992–1993 and 1996–1998) when monitoring data show more anoxic weeks per year and relatively higher lake levels. Increased cultivation of small landholdings in 1963, and particularly after 1979, caused a large increase in sediment delivery to the lake. The inferred lake evolution is in agreement with monitoring data that suggest a transition from dominantly meromictic conditions prior to 1993–1994 to a predominantly monomictic pattern of circulation since then, particularly after 2000. The synergistic effects of intensive water extraction for irrigation and lower rainfall since 1979, and particularly since 1994, brought the long period of meromictic conditions in Lake Arreo to an end. Water balance and sediment delivery to the lake are dominant factors that control the limnological and mixing conditions in Lake Arreo and they must be considered in management and restoration plans.     

High-precision repeat-groundtrack orbit design and maintenance for Earth observation missions

The focus of this paper is the design and station keeping of repeat-groundtrack orbits for Sun-synchronous satellites. A method to compute the semimajor axis of the orbit is presented together with a station-keeping strategy to compensate for the perturbation due to the atmospheric drag. The results show that the nodal period converges gradually with the increase of the order used in the zonal perturbations up to \(J_{15}\). A differential correction algorithm is performed to obtain the nominal semimajor axis of the reference orbit from the inputs of the desired nodal period, eccentricity, inclination and argument of perigee. To keep the satellite in the proximity of the repeat-groundtrack condition, a practical orbit maintenance strategy is proposed in the presence of errors in the orbital measurements and control, as well as in the estimation of the semimajor axis decay rate. The performance of the maintenance strategy is assessed via the Monte Carlo simulation and the validation in a high fidelity model. Numerical simulations substantiate the validity of proposed mean-elements-based orbit maintenance strategy for repeat-groundtrack orbits.     

Formation Mechanism of Mud Bank Along the Southwest Coast of India

Mud bank formation during the southwest monsoon along the southwest coast of India remains an enigma to the researchers and coastal community in spite of several earlier studies. The present study attempts to unravel the mystery through a high-frequency, season-long time-series observation at Alappuzha, located at the southern part of the west coast of India, a region of frequent occurrence of mud bank. Using 7-month-long weekly time-series observation, we identified strong winds and high waves associated with onset of the southwest monsoon and subsequent three episodic atmospheric low-pressure events (LPEs).With the help of in situ time-series data, we show that the strong winds and high waves associated with southwest monsoon pre-conditions the near shore bottom sediment to bring it into suspension. The high amplitude waves associated with the southwest monsoon, while propagating from the deep water to shallow water region, interact with the bottom initiating bottom-sediment movement and its suspension due to wave refraction and shoaling. The sporadic occurrence of the atmospheric LPEs enhances the process of suspension of bottom sediment in the near shore region leading to the formation of fluid mud. Simulations with a cohesive sediment transport model yielded realistic estimates of sediment transport, in the presence of an onshore current, a pre-requisite for transporting the fluid mud toward the coast. The prevailing onshore upwelling current during the southwest monsoon provides the favorable pre-requisite conditions for transporting the fluid mud through depression channel network towards the coast. Once sufficient quantity and thickness of fluid mud is accumulated in the near shore region, it acts as a wave damper for subsequent high monsoon waves, as indicated by the time-series wave data, leading to the formation of tranquil mud bank region. Depression channel networks extending from the shelf to the coast off Alappuzha, Kochi, Ponnani, Beypore, and Ullal were found in the bathymetric charts, thus explaining why mud banks occur only at few locations in spite of the prevalence of similar monsoon conditions.     

High-efficiency calculation method for watershed rainfall-runoff routing using one-dimensional dynamic wave equations

Efficiency in solving the Saint-Venant equations for watershed rainfall-runoff routing is important in flood hydrology. This paper presents a high-efficiency numerical solution of one-dimensional dynamic wave equations (HEDWE) for watershed rainfall-runoff routing, in which the full momentum equation is written as a quadratic equation with only one unknown variable Q, water depth is derived from the continuity equation using the two-step predictor-corrector method, and the discrete scheme is the explicit upwind scheme. The results of numerical tests showed the HEDWE approach has several major advantages. 1) It is a stable numerical method, even for an initially dry area. 2) Its computational efficiency is higher than 4.76E+05 times/s. 3) It can be used for overland flow, river flow, and combinations thereof. The primary disadvantages of the HEDWE approach are its unsuitability for rapidly varying flow, such as dam-break floods.     

Identification of Gleissberg Cycles and a Rising Trend in a 315-Year-Long Series of Sunspot Numbers

We show in this short note that the method of singular spectrum analysis (SSA) is able to clearly extract a strong, clean, and clear component from the longest available sunspot (International Sunspot Number, ISN) time series (1700?–?2015) that cannot be an artifact of the method and that can be safely identified as the Gleissberg cycle. This is not a small component, as it accounts for 13% of the total variance of the total original signal. Almost three and a half clear Gleissberg cycles are identified in the sunspot number series. Four extended solar minima (XSM) are determined by SSA, the latest around 2000 (Cycle 23/24 minimum). Several authors have argued in favor of a double-peaked structure for the Gleissberg cycle, with one peak between 55 and 59 years and another between 88 and 97 years. We find no evidence of the former: solar activity contains an important component that has undergone clear oscillations of \(\approx90\) years over the past three centuries, with some small but systematic longer-term evolution of “instantaneous” period and amplitude. Half of the variance of solar activity on these time scales can be satisfactorily reproduced as the sum of a monotonous multi-secular increase, a \(\approx90\)-year Gleissberg cycle, and a double-peaked (\(\approx10.0\) and 11.0 years) Schwabe cycle (the sum amounts to 46% of the total variance of the signal). The Gleissberg-cycle component definitely needs to be addressed when attempting to build dynamo models of solar activity. The first SSA component offers evidence of an increasing long-term trend in sunspot numbers, which is compatible with the existence of the modern grand maximum.     

Automatic Determination of Stellar Atmospheric Parameters Using Neural Networks and Instance-Based Machine Learning

In this article we show how machine learning methods can beeffectively applied to the problem of automatically predictingstellar atmospheric parameters from spectral information, a veryimportant problem in stellar astronomy. We apply feedforwardneural networks, Kohonen's self-organizing maps andlocally-weighted regression to predict the stellar atmosphericparameters effective temperature, surface gravity and metallicityfrom spectral indices. Our experimental results show that thethree methods are capable of predicting the parameters with verygood accuracy. Locally weighted regression gives slightly betterresults than the other methods using the original dataset asinput, while self-organizing maps outperform the other methods when significant amounts of noise are added. We also implemented a heterogeneous ensemble of predictors, combining the results given by the three algorithms. This ensemble yields better results than any of the three algorithms alone, using both the original and the noisy data.