Tree-based threshold modeling for short-term forecast of daily maximum ozone level

This paper proposes a simple class of threshold autoregressive model for purpose of forecasting daily maximum ozone concentrations in Southern California. Linear time series model has been widely considered in environmental modeling. However, this class of models fails to capture the nonlinearity in ozone process and the complexity of meteorological interactions with ozone. In this article, we used the threshold autoregressive models with two classes of regimes; periodic and meteorological regimes. Days in week were used for the periodic regimes and the regression tree method was used to define the regimes as a function of meteorological variables. As the reference model we used the autoregressive model with lagged ozone and various lagged meteorological variables as the covariates. The proposed models were applied to a 3-year dataset of daily maximum ozone concentrations obtained from five monitoring stations in San Bernardino County, CA and their forecast performances were evaluated using an independent year-long dataset from the same stations. The results showed that the threshold models well capture the nonlinearity in ozone process and remove the nonstationarity in model residuals. The threshold models outperformed the non-threshold autoregressive models in day-ahead forecasts. The tree-based model showed slightly better performance than the periodic threshold model.     

湖泊水环境模糊数学评价模型及其在富营养化排序中的应用

本文根据模糊水文学关于水体“清洁”与“污染”之间无明确界面,在识别过程中具有模糊性的论点,提出湖泊水环境评价的模糊数学模型。应用此模型对我国12个湖泊富营养化污染状况进行排序,结果与实际相符,文中提出的评价模型,原则上也适用于其他环境领域的评价工作。     

Daily river water temperature forecast model with a k‐nearest neighbour approach

Water temperature is a key abiotic variable that modulates both water chemistry and aquatic life in rivers and streams. For this reason, numerous water temperature models have been developed in recent years. In this paper, a k‐nearest neighbour model (KNN) is proposed and validated to simulate and eventually produce a one‐day forecast of mean water temperature on the Moisie River, a watercourse with an important salmon population in eastern Canada. Numerous KNN model configurations were compared by selecting different attributes and testing different weight combinations for neighbours. It was found that the best model uses attributes that include water temperature from the two previous days and an indicator of seasonality (day of the year) to select nearest neighbours. Three neighbours were used to calculate the estimated temperature, and the weighting combination that yielded the best results was an equal weight on all three nearest neighbours. This nonparametric model provided lower Root Mean Square Errors (RMSE = 1·57 °C), Higher Nash coefficient (NTD = 0·93) and lower Relative Bias (RB = ? 1·5%) than a nonlinear regression model (RMSE = 2·45 °C, NTD = 0·83, RB = ? 3%). The k‐nearest neighbour model appears to be a promising tool to simulate of forecast water temperature where long time series are available. Copyright © 2011 John Wiley & Sons, Ltd.     

Deuterium‐excess determination of evaporation to inflow ratios of an alpine lake: Implications for water balance and modeling

The numerous lakes on the Tibetan Plateau play an important role in the regional hydrological cycle and water resources, but systematic observations of the lake water balance are scarce on the Tibetan Plateau. Here, we present a detailed study on the water cycle of Cona Lake, at the headwaters of the Nujiang‐Salween River, based on 3 years (2011–2013) of observations of δ¹⁸O and δ²H, including samples from precipitation, lake water, and outlet surface water. Short‐term atmospheric water vapor was also sampled for isotope analyses. The δ²H–δ¹⁸O relationship in lake water (δ²H = 6.67δ¹⁸O ? 20.37) differed from that of local precipitation (δ²H = 8.29δ¹⁸O + 12.50), and the deuterium excess (d‐excess) in the lake water (?7.5‰) was significantly lower than in local precipitation (10.7‰), indicating an evaporative isotope enrichment in lake water. The ratio of evaporation to inflow (E /I ) of the lake water was calculated using both d‐excess and δ¹⁸O. The E /I ratios of Cona lake ranged from 0.24 to 0.27 during the 3 years. Observations of atmospheric water vapor isotopic composition (δ _A ) improved the accuracy in E /I ratio estimate over a simple precipitation equilibrium model, though a correction factor method provided nearly identical estimates of E /I ratio. The work demonstrates the feasibility of d‐excess in the study of the water cycle for lakes in other regions of the world and provides recommendations on sampling strategies for accurate calculations of E /I ratio.     

水位波动下的呼伦湖上覆水体与沉积物间隙水之间溶质的运移特征

为了探求内蒙古呼伦湖上覆水体和沉积物间隙水之间溶质运移机制,对呼伦湖的1个沉积物柱芯的间隙水、3个湖泊水体以及湖周边7个地下水体中的氯离子(Cl~-),氢、氧稳定同位素(δD和δ~(18)O)分别进行分析测试,并利用其示踪性对沉积物中溶质运移特征进行研究.结果显示,δD、δ~(18)O和Cl~-浓度在不同水体中的分布具有相似的分布规律,整体上从底部沉积物到上部湖水浓度分布呈现逐渐递减的抛物线趋势,在间隙水中最大值位于所取沉积物柱芯的最深处,Cl~-浓度为306 mg/L,δD和δ~(18)O分别为-58‰和-5.9‰;最小值位于沉积物柱芯上层,并与上覆水体中的值相似,Cl~-浓度为159 mg/L,δD和δ~(18)O分别为-66‰和-7.3‰.为了明确沉积物柱芯中间隙水的高浓度Cl~-和偏正δD、δ~(18)O的来源,比较不同水体的δ~(18)O-δD关系点分布,表明含有偏正值的δD、δ~(18)O和高浓度Cl~-的间隙水与上覆湖水关系密切,可能是由于低水位时期湖水与间隙水相互发生扩散作用而产生的结果.一维对流扩散迁移模型证实扩散作用是控制着沉积物间隙水中溶质浓度在垂向上分布的主要机制,同时湖水水位的变化会影响沉积物间隙水与上覆水体的扩散过程,特别是在水位上升期,富集在沉积物中的溶质可能成为湖水的重要物质来源,影响上覆水体的水质.因此,对于封闭湖泊水位的控制和管理不仅在维持湖泊水量方面有着直接的作用,同时在稳定湖泊水质条件上也有着重要的意义.     

Depression threshold control proxy to improve HEC-HMS modeling of depression-dominated watersheds

ABSTRACT

Many hydrologic models utilize delineation results from traditional methods which create a hydrologically connected drainage system. In depression-dominated areas, topographic characteristics of depressions are vital to modeling unique hydrologic processes associated with puddle-to-puddle (P2P) filling-spilling dynamics. The objective of this study is to evaluate the impacts of the P2P processes and dynamic changes in contributing area on outlet discharge. To do so, an improved HEC-HMS model is developed by incorporating a depression threshold control proxy (DTCP) and an improved conceptual framework. The DTCP uses a storage–discharge function to simulate the P2P dynamics. The improved conceptual framework counteracts the effect of full hydrologic connectivity created by traditional delineation methods by introducing depressional and non-depressional areas to each sub-basin. Application of the improved HEC-HMS model demonstrated that it was capable of accurately simulating outlet discharge and providing the details on surface connectivity and depression storage.     

Variational approach to modeling present-time mantle convection

Summary An analogy of the Hellinger-Reissner functional for the Stokes problem is constructed and the way of determining its minimum by means of spherical harmonic vectors and tensors is described. The variational method is applied to a Newtonian mantle in which the body forces were estimated on the basis of global inversion of gravitational and topographic data. The method is then generalized to the case of a realistic rheology (power-law creep), and prospects of the generalised method are briefly discussed.     

A six-step practical approach to semivariogram modeling

Geostatistical prediction and simulation are being increasingly used in the earth sciences and engineering to address the imperfect knowledge of attributes that fluctuate over large areas or volumes—pollutant concentration, electromagnetic fields, porosity, thickness of a geological formation. Central to the application of such techniques is the need to know the spatial continuity, knowledge that is commonly condensed in the form of covariance or semivariogram models. Their preparation is subdivided here into the following steps: (1) Data editing, (2) Exploratory data analysis, (3) Semivariogram estimation, (4) Directional investigation, (5) Simple modeling, (6) Nested modeling. I illustrate these stages practically with a real data set from a geophysical survey from Elk County, Kansas, USA. The applicability of the approach is not limited by the physical nature of the attribute of interest.     

A unified approach to environmental systems modeling

The paper considers the differences between hypothetico-deductive and inductive modeling: between modelers who put their primary trust in their scientific intuition about the nature of an environmental model and tend to produce quite complex computer simulation models; and those who prefer to rely on the analysis of observational data to identify the simplest form of model that can represent these data. The tension that sometimes arises because of the different philosophical outlooks of these two modeling groups can be harmful because it tends to fractionate the effort that goes into the investigation of important environmental problems, such as global warming. In an attempt to improve this situation, the paper will outline a new Data-Based Mechanistic (DBM) approach to modeling that tries to meld together the best aspects of these two modeling philosophies in order to develop a unified approach that combines the hypothetico-deductive virtues of good scientific intuition and simulation modeling with the pragmatism of inductive data-based modeling, where more objective inference from data is the primary driving force. In particular, it demonstrates the feasibility of a new method for complex simulation model emulation, in which the methodological tools of DBM modeling are used to develop a reduced dynamic order model that represents the ‘dominant modes’ of the complex simulation model. In this form, the ‘dynamic emulation’ model can be compared with the DBM model obtained directly from the analysis of real data and any tensions between the two modeling approaches may be relaxed to produce models that suit multiple modeling objectives.     

Application of data assimilation for improving forecast of water levels and residual currents in Singapore regional waters

Hydrodynamic models are commonly used for predicting water levels and currents in the deep ocean, ocean margins and shelf seas. Their accuracy is typically limited by factors, such as the complexity of the coastal geometry and bathymetry, plus the uncertainty in the flow forcing (deep ocean tide, winds and pressure). In Southeast Asian waters with its strongly hydrodynamic characteristics, the lack of detailed marine observations (bathymetry and tides) for model validation is an additional factor limiting flow representation. This paper deals with the application of ensemble Kalman filter (EnKF)-based data assimilation with the purpose of improving the deterministic model forecast. The efficacy of the EnKF is analysed via a twin experiment conducted with the 2D barotropic Singapore regional model. The results show that the applied data assimilation can improve the forecasts significantly in this complex flow regime.     

蚌湖与鄱阳湖水量交换关系的分析

根据蚌湖和鄱阳湖修水站的水位同步观测资料,结合湖区地形,分析蚌湖与鄱阳湖的水量交换关系,并利用三峡工程对鄱阳湖修水,星子,都昌站水位影响的预测结果,讨论三峡工程对蚌湖水情的影响。     

Urmia lake water level fluctuation hydro informatics modeling using support vector machine and conjunction of wavelet and neural network

In this research, the simulation of Urmia Lake water level fluctuation by means of two models was applied. For this, Support Vector Machines (SVM), and Neural Wavelet Network (NWN) models that conjugated both the wavelet function and ANN, developed for simulating the Urmia Lake water level fluctuation. The yearly data of rainfall, temperature and discharge to the Urmia Lake and water level fluctuation were used. Urmia Lake is the biggest and the hyper saline lake in Iran. The outcome of the SVM based models are compared with the NWN. The results of SVM model performs better than NWN and offered a practical solution to the problem of water level fluctuation predictions. Analysis results showed that the optimal situation occurred with use of precipitation, temperature and discharge for all station and water level fluctuations at the lag time of one year (RMSEs) of 0.23, 0.41 m obtained by SVM, NWN, respectively, and SSEs of 0.43, 1.33 and R ² of 0.97, 0 obtained by SVM, NWN, respectively. The results of SVM model show better accuracy in comparison with the NWN model.     

Ambient noise levels and detection threshold in Norway

Ambient seismic noise is caused by a number of sources in specific frequency bands. The quantification of ambient noise makes it possible to evaluate station and network performance. We evaluate noise levels in Norway from the 2013 data set of the Norwegian National Seismic Network as well as two temporary deployments. Apart from the station performance, we studied the geographical and temporal variations, and developed a local noise model for Norway. The microseism peaks related to the ocean are significant in Norway. We, therefore, investigated the relationship between oceanic weather conditions and noise levels. We find a correlation of low-frequency noise (0.125–0.25 Hz) with wave heights up to 900 km offshore. High (2–10 Hz) and intermediate (0.5–5 Hz) frequency noise correlates only up to 450 km offshore with wave heights. From a geographic perspective, stations in southern Norway show lower noise levels for low frequencies due to a larger distance to the dominant noise sources in the North Atlantic. Finally, we studied the influence of high-frequency noise levels on earthquake detectability and found that a noise level increase of 10 dB decreases the detectability by 0.5 magnitude units. This method provides a practical way to consider noise variations in detection maps.     

The driving force of basin water resource utilization to lake nutrients

ABSTRACT

Understanding of the effect of basin water resources utilization on lake nutrients is helpful to prevent lake eutrophication and facilitate sustainable water resources management. In this study, a lake basin dualistic water cycle system is established to identify the environmental effect of lake water. Four water utilization indicators were chosen to build a driving relationship with the lake nutrients. Three different trophic lakes in Yunnan Province, China – Dianchi, Erhai and Fuxian – were selected to demonstrate the changes in basin water utilization, runoff, nutrient loads and water-use indicators for the period 2000–2015. In addition, the driving forces of water-use indicators to nutrients (total nitrogen and total phosphorus) were analysed by a general additive model. Finally, an optimized water utilization system for each lake basin is proposed. The research provides a practical tool for water resources and environmental management in lake basins.     

Ecotoxicological approach to water quality assessment

Comparative analysis of approaches and methods of biological assessment of water quality is presented. A method of ecotoxicological diagnostic of aquatic ecosystem health and water quality evaluation based on the physiological state of fish are substantiated. Characteristics of the main symptoms of diseases in fish inhabiting freshwater bodies and pathologic disturbances in their organs and tissues, caused by water bodies contamination with toxic substances, are presented. The method of ecotoxicological assessment of water quality is shown to be both highly informative and easy-to-use in practical monitoring.Translated from Vodnye Resursy, Vol. 32, No. 2, 2005, pp. 184–195.Original Russian Text Copyright © 2005 by Moiseenko.     

Quantitative reconstruction of the lake water paleotemperature of Daihai Lake, Inner Mongolia, China and its significance in paleoclimate

By measuring Sr/Ca ratios of the ostracod shells (Limnocthere cf. inopinata) in sediments of the Daihai Lake, and combined with Sr²⁺/Ca²⁺ ratios of the lake water, this paper obtained paleosalinity of the lake water. Vaporizing experiment of the lake water in laboratory showed that there was a quantitative relationship between salinity and oxygen isotope. Using this relationship, oxygen isotope values of the paleo-lake water were calculated. By measuring the oxygen isotope of the authigenic carbonate in the lake’s sediments, and in combination with the oxygen isotope values of the paleo-lake water, the paleotemperature of the lake water was calculated. Finally, based on these proxies, the paleoclimate in the lake basin was explored.     

磁场散度为零的变分重构法在日冕太阳风数值模拟中的应用

本文利用保持平均磁场散度为零的限制条件,设计出了满足全局散度为零的变分重构方法（Globally solenoidality-preserving variational reconstruction approach,VR-GSP）,并将其应用于日冕太阳风磁流体力学（Magnetohydrodynamics,MHD）数值模拟中的磁场重构.为评估该方法的有效性,我们模拟了2234卡林顿周（Carrington rotation,CR）的日冕结构.在模拟中,我们将VR-GSP方法与Feng等（2019）中的基于最小二乘法的全局磁场散度为零的重构方法（Globally solenoidality-preserving least-squares method,LSQ-GSP）作了比较.比较结果显示,基于VR-GSP方法的MHD模拟同样再现了Solar Dynamics Observatory（SDO）卫星、Solar and Heliospheric Observatory（SOHO）飞船以及Wind卫星观测到的包括冕流以及高低速流等大尺度日冕结构,而且相比于LSQ-GSP,基于VR-GSP的MHD模拟的计算效率更高,从而也说明其更有助于在有限体积框架下设计出满足磁场散度为零的高效和紧致的数值方法,并应用于研究复杂强磁场环境下的磁流体力学问题.