A parallel domain decomposition algorithm for coastal ocean circulation models based on integer linear programming

This paper presents a new parallel domain decomposition algorithm based on integer linear programming (ILP), a mathematical optimization method. To minimize the computation time of coastal ocean circulation models, the ILP decomposition algorithm divides the global domain in local domains with balanced work load according to the number of processors and avoids computations over as many as land grid cells as possible. In addition, it maintains the use of logically rectangular local domains and achieves the exact same results as traditional domain decomposition algorithms (such as Cartesian decomposition). However, the ILP decomposition algorithm may not converge to an exact solution for relatively large domains. To overcome this problem, we developed two ILP decomposition formulations. The first one (complete formulation) has no additional restriction, although it is impractical for large global domains. The second one (feasible) imposes local domains with the same dimensions and looks for the feasibility of such decomposition, which allows much larger global domains. Parallel performance of both ILP formulations is compared to a base Cartesian decomposition by simulating two cases with the newly created parallel version of the Stevens Institute of Technology’s Estuarine and Coastal Ocean Model (sECOM). Simulations with the ILP formulations run always faster than the ones with the base decomposition, and the complete formulation is better than the feasible one when it is applicable. In addition, parallel efficiency with the ILP decomposition may be greater than one.     

Developing environmental indices using fuzzy numbers ordered weighted averaging (FN-OWA) operators

Environmental indices (EI) constitute a common communication tool that is often used to describe the overall status of environmental systems (air, water and soil). EI development entails the use of mathematical operators to aggregate various non-commensurate input parameters in a logical manner. The ordered weighted averaging (OWA) operator is a general mean type operator that provides flexibility in the aggregation process such that the aggregated value is bounded between minimum and maximum values of the input parameters. This flexibility of the OWA operator is realized through the concept of orness, which is a surrogate for decision maker’s attitude. The type of input parameters also affects the choice of aggregation operators. If the input parameters are linguistic or fuzzy, the aggregation through OWA operators is not possible, and the use of fuzzy arithmetic is warranted. The concept of fuzzy number OWA (FN-OWA) operators is explored to handle situations in which one or more input parameter has fuzzy (or linguistic) values. The proposed approach is demonstrated using data provided in an earlier study by Swamee and Tyagi (ASCE J Environ Eng 126(5):451–455, 2000) for establishing water quality indices. Multiple hypothetical scenarios are also generated to highlight the utility and sensitivity of the proposed approach.     

Seasonal circulations in the Malay Peninsula Eastern continental shelf from a wave–tide–circulation coupled model

A wave–tide–circulation coupled model based on Princeton Ocean Model is established to study the seasonal circulation in the Malay Peninsula Eastern Continental Shelf region. The model successfully reconstructs the observed seasonal variation of the circulation in the region, as well as the main currents. The simulated tidal harmonic constants, sea surface temperature, and sea surface height anomaly agree with the observations well. The model results show that the upper-layer circulation in the region is mainly controlled by the monsoon winds, while there are two transitions in spring and fall. An anti-cyclonic eddy is present off the Peninsular Malaysia’s east coast in summer, centered at 5°N and 105.5°E, both in the TOPEX/Poseidon data and in the model. Numerical experiments show that the wind stress curl and bathymetry steering are responsible for its formation.     

Runoff and erosion processes and rates in the Zin valley badlands,northern Negev,Israel

Badland areas are usually regarded as impermeable zones which generate high runoff and are very vulnerable to sheetwash and rainsplash. To test those considerations sprinkling experiments using two rainfall simulators were carried out on slopes of varying aspect in the northern Negev (Israel). For one unit 1·5 m² plots were used with rainfall of natural characteristics at 36 mm/hr intensity and 43–48 minute duration, runoff being recorded and water/sediment samples taken every 5 minutes. The second unit was used on 30–50 m² plots but rainfall energy production was below that of natural rainfall. Results show that due to the high stability and strong flocculation of clay-rich aggregates rainsplash is ineffective in surface sealing so that infiltration capacities remain high despite intense, prolonged rainfall. Aspect differences are reflected in variation of surface properties despite homogenous bed-rock, which cause marked differences in hydrological response. North-facing slopes respond more quickly, more frequently and produce more runoff than south-facing slopes. Non-uniform runoff generation is also seen within plots of one aspect reflecting subtle variations in surface properties. Comparison of rainfall intensity and duration used during the experiments with those prevailing under natural conditions shows that under present day conditions surface flow in the Zin valley badlands must be extremely infrequent and denudation rates very low.     

Supervised neural network recognition of habitat zones of rice invertebrates

This study aimed to evaluate effectiveness and performance of several supervised neural network models and make pattern recognition on invertebrate habitat zones. Probabilistic, general regression, and linear neural networks, and discriminant analysis were used to recognize both known and unknown invertebrate habitat zones. The results showed that neural network models were better than traditional discriminant analysis in the recognition of known habitat zones. There was not distinctive variation in recognition from different neural network models. Sensitivity analysis indicated that the learning rate of the neural network would influence recognized results. An unknown invertebrate species from Lepidoptera was recognized to be soil-dweller (dryland) by both neural network models and discriminant analysis. In sensitivity analysis it was additionally recognized to be the type of plant canopy (terrestrial). Overall the species was estimated to be a soil-dweller (dryland) or live on plant canopy (terrestrial). It was concluded that neural network models can perform better than conventional statistic models in pattern recognition, but a comprehensive comparison among various models is necessary in order to achieve a high reliable recognition and prediction. Furthermore, sensitivity analysis can lead to an in-depth grasp on the mechanism in the recognition and is thus needed.     

SLA–chlorophyll-a variability and covariability in the Algero-Provençal Basin (1997–2007) through combined use of EOF and wavelet analysis of satellite data

Data reduction and signal decomposition techniques have been applied to a large bio-physical remotely sensed dataset covering the decade 1997–2007. The aim was the estimation of the spatial (basin and sub-basin scales) and temporal (seasonal and interannual) variability of sea level anomalies and chlorophyll-a concentration in the Algero-Provençal Basin, as well as the study of their covariability. Empirical orthogonal functions, wavelet analysis, singular value decomposition and correlation maps have been successfully used to individuate the patterns of (co)variability of the investigated fields. The seasonal variability of the phytoplanktonic biomass is divided in two distinct modes, timewise and spacewise separated. Positive interannual events are related to anomalies in 1999 and 2005, while the main (negative) anomaly is that of summer 2003, associated to the European 2003 heatwave. The analysis of the sea level anomalies shows a minimum in the formation of anticyclonic Algerian eddies during that period. The largest anticorrelation between sea level anomalies and phytoplanktonic biomass is found in the central zone of the basin, suggesting a clear biological response to the shoaling/deepening of the isopycnae and so to the nutrient injection into the euphotic layer. The analysis suggests that the driver of the variability of the nutricline depth in this central area is the displacement (seasonal) of the North Balearic Front and the formation/action of the frontal eddies.     

Petroleum Electromagnetic Prospecting Advances and Case Studies in China

Remarkable progress has been made in electromagnetic (EM) techniques as applied to the petroleum industry in instruments, data acquisition, and processing and interpretation in China. Included here is equipment, such as high-power Controlled Source EM (CSEM) acquisition systems, acquisition methods, such as the three dimensional small-bin Continuous Electromagnetic Array acquisition method, Time and Frequency Domain Controlled Source Electromagnetic, Borehole-to-surface Electromagnetic technique and marine magnetotelluric method. Data processing methods, such as fast three dimensional inversion using nonlinear conjugate gradients, and data interpretation methods, like Induced Polarization and Resistivity anomalies for hydrocarbon detection, are also included. These new techniques have been applied in petroleum survey and many cases are in complicated areas. They have successfully served the investigation of deep igneous rock reservoirs, and prediction of potential hydrocarbon targets. The cases indicate that electromagnetic techniques can help seismic survey to effectively detect hydrocarbon reservoir and remarkably improve drilling successes.     

Overview of Holocene Tsunami Deposits along the Nankai,Suruga, and Sagami Troughs,Southwest Japan

Tsunami deposits provide a basis for reconstructing Holocene histories of great earthquakes and tsunamis on the Pacific Coast of southwest Japan. The deposits have been found in the past 15 years at lakes, lagoons, outcrops, and archaeological excavations. The inferred tsunami histories span 3000 years for the Nankai and Suruga Troughs and nearly 10,000 years for the Sagami Trough. The inferred histories contain recurrence intervals of variable length. The shortest of these —100–200 years for the Nankai Trough, 150–300 years for the Sagami Trough — resemble those known from written history of the past 1000–1500 years. Longer intervals inferred from the tsunami deposits probably reflect variability in rupture mode, incompleteness of geologic records, and insufficient research. The region's tsunami history could be clarified by improving the geologic distinction between tsunami and storm, dating the inferred tsunamis more accurately and precisely, and using the deposits to help quantify the source areas and sizes of the parent earthquakes.     

Elemental characteristics of lacustrine oil shale and its controlling factors of palaeo-sedimentary environment on oil yield: a case from Chang 7 oil layer of Triassic Yanchang Formation in southern Ordos Basin

As an important unconventional resource, oil shale has received widespread attention. The oil shale of the Chang 7 oil layer from Triassic Yanchang Formation in Ordos Basin represents the typical lacustrine oil shale in China. Based on analyzing trace elements and oil yield from boreholes samples, characteristics and paleo-sedimentary environments of oil shale and relationship between paleo-sedimentary environment and oil yield were studied. With favorable quality, oil yield of oil shale varies from 1.4% to 9.1%. Geochemical data indicate that the paleo-redox condition of oil shale’s reducing condition from analyses of V/Cr, V/(V + Ni), U/Th, δU, and authigenic uranium. Equivalent Boron, Sp, and Sr/Ba illustrate that paleosalinity of oil shale is dominated by fresh water. The paleoclimate of oil shale is warm and humid by calculating the chemical index of alteration and Sr/Cu. Fe/Ti and (Fe + Mn)/Ti all explain that there were hot water activities during the sedimentary period of oil shale. In terms of Zr/Rb, paleohydrodynamics of oil shale is weak. By means of Co abundance and U/Th, paleo-water-depth of oil shale is from 17.30 to 157.26 m, reflecting sedimentary environment which is mainly in semi deep–deep lake facies. Correlation analyses between oil yield and six paleoenvironmental factors show that the oil yield of oil shale is mainly controlled by paleo-redox conditions, paleoclimate, hot water activities, and depth of water. Paleosalinity and paleohydrodynamics have an inconspicuous influence on oil yield.     

GaRiRO: Gradient and residual integrated rank ordering of stations in rainfall monitoring network

This paper presents a new method that integrates gradient and residual values for rank ordering of stations in a monitoring network (GaRiRO). The innovation is derived from the fact that the parameter (dependent variable) gauged through the monitoring network is modelled using independent variables that influence its measured quantity. And the dependent variable exhibit non-stationary spatial gradient with respect to the independent variables, particularly in complex terrain. GaRiRO technique was developed to prioritize the rain gauge stations for optimizing the existing network and selection of the best locations for relocation or installation of gauges. Although initially aimed to assist hydrologists with a ranking scheme for rain gauge stations, it can be applied to any environmental, meteorological or hydro-meteorological monitoring network. The new procedure is based on deriving gradient and residual value at each station by modeling the spatial relationship of dependent-independent variable using geographically weighted regression (GWR) technique. For the prospective stations with no record, the gradient value is estimated using GWR model and the residual value is derived from the residual map generated by applying kriging technique on the residual derived at all gauged locations. The method combines the decision factor with analytical strength of GIS for prioritizing the stations which results in limited number of trials for installation or relocation of gauges to yield optimized network configuration.