Indonesian rainfall variability during Western North Pacific and Australian monsoon phase related to convectively coupled equatorial waves

The Indonesian archipelago which has over 15,000 islands, lies in the tropics between Asia and Australia. This eventually alters the rainfall variability over the region, which was influenced by the Asian-Australian monsoon and controlled by intraseasonal variabilities such as convectively coupled equatorial waves (CCEW), i.e., Kelvin, n?=?1 equatorial Rossby (ER), mixed Rossby gravity (MRG), and n?=?1 Westward inertio gravity (WIG), including the Madden–Julian Oscillation (MJO). This study examines a 15-year 3B42 data for trapping CCEW and MJO in the region of Indonesia during both active and extreme Western North Pacific (WNP) and Australian (AU) monsoon phases, which are then compared with 30-year rainfall anomalies among 38 synoptic stations over Indonesia. The space–time spectral analysis is employed to filter each wave including the MJO in the equator, then proceeding with the empirical orthogonal function (EOF) method to seek each wave peak which then coincides with WNP and AU monsoon peaks over Indonesia. It is concluded that an extreme monsoon classification has proven to control rainfall activity related to the CCEW and MJO at 60.66% during December through February (DJF)-WNP for only the significant wave perturbation value. Meanwhile, the CCEW and MJO significantly increase/decrease precipitation at Day 0 for about 37.88% from the total of Day 1st to Day end. Although the contribution of the CCEW and MJO does not profoundly influence rainfall activity during monsoon phase over Indonesia, they still modulate weather condition for more than 50%. On the other hand, a complex topography with a number of land–sea complexities is capable of influencing the rainfall variability in the region as a negative relationship is associated with the CCEW and MJO either during DJF-WNP or July through August (JAS)-AU monsoon phase.     

An Effective Approach to Rehabilitate Damaged Barrier System Against Piping and Contaminant Flow

The monitoring operation of an older impoundment (such as dams and waste barrier materials) during the service life of the structure cannot be overemphasized. Since older infrastructures seem to be more susceptible to piping and seepage failure, their construction design should be analyzed and monitored at places where a potential problem could occur. Once an impoundment is constructed without adequate filters layers and foundation treatments, then the prevention of piping or seepage may require an effective approach to constructing a cut-off wall to prevent eventual failure. In order to identify and understand theses failure modes, it is important to identify the physical parameters of the impoundment system, such as the zones of various soil gradations, the compaction of these zones, the hydraulic conductivity, the compatibility of the soil formations within and beneath the core or liner, as well as the cohesive and dispersive properties of soils at various location within the structure. Once these parameters are known and quantified, an adequate assessment of the structure’s susceptibility to piping or contaminant transport can be established. This type of an analysis will enable the proper design of a cut-off wall and predetermine the effectiveness of its long-term performance. The Vermont Waterbury Dam (built in 1938) is example of seepage related problem that implemented a cut-off wall design to prevent piping paths from undermining the structure. In this case, some forensic sampling had to be performed and the parameters of the soils as just mentioned were key factors in determining the wall design. In this paper, the Waterbury dam rehabilitation is investigated as case studies, in order to better understand how older designs and poor construction of impoundments can lead to piping condition in dams as well as failures in waste barrier systems. The Secant Cut-off wall (constructed at Waterbury Dam) is mentioned as a corrective measure taken for this dam and there is a brief discussion as to how this construction rehabilitation technique can be applied to waste barrier impoundments.     

Ambiguity resolved precise point positioning with GPS and BeiDou

This paper focuses on the contribution of the global positioning system (GPS) and BeiDou navigation satellite system (BDS) observations to precise point positioning (PPP) ambiguity resolution (AR). A GPS + BDS fractional cycle bias (FCB) estimation method and a PPP AR model were developed using integrated GPS and BDS observations. For FCB estimation, the GPS + BDS combined PPP float solutions of the globally distributed IGS MGEX were first performed. When integrating GPS observations, the BDS ambiguities can be precisely estimated with less than four tracked BDS satellites. The FCBs of both GPS and BDS satellites can then be estimated from these precise ambiguities. For the GPS + BDS combined AR, one GPS and one BDS IGSO or MEO satellite were first chosen as the reference satellite for GPS and BDS, respectively, to form inner-system single-differenced ambiguities. The single-differenced GPS and BDS ambiguities were then fused by partial ambiguity resolution to increase the possibility of fixing a subset of decorrelated ambiguities with high confidence. To verify the correctness of the FCB estimation and the effectiveness of the GPS + BDS PPP AR, data recorded from about 75 IGS MGEX stations during the period of DOY 123-151 (May 3 to May 31) in 2015 were used for validation. Data were processed with three strategies: BDS-only AR, GPS-only AR and GPS + BDS AR. Numerous experimental results show that the time to first fix (TTFF) is longer than 6 h for the BDS AR in general and that the fixing rate is usually less than 35 % for both static and kinematic PPP. An average TTFF of 21.7 min and 33.6 min together with a fixing rate of 98.6 and 97.0 % in static and kinematic PPP, respectively, can be achieved for GPS-only ambiguity fixing. For the combined GPS + BDS AR, the average TTFF can be shortened to 16.9 min and 24.6 min and the fixing rate can be increased to 99.5 and 99.0 % in static and kinematic PPP, respectively. Results also show that GPS + BDS PPP AR outperforms single-system PPP AR in terms of convergence time and position accuracy.     

Dynamical system analysis of a five-dimensional cosmological model

A five-dimensional cosmological model including a single perfect fluid is studied in the framework of dynamical system analysis. All the critical points of the system are listed with their stability properties and some representative phase diagrams are explicitly shown. It is found that the stabilization of extra dimension is possible and the observed flatness of the three-dimensional space is provided for certain ranges of the equation of state parameter of the fluid. The model suggested here can be considered as a simplified model for examining the possible effects of the extra dimensions in the early universe.     

DHI evaluation by combining rock physics simulation and statistical techniques for fluid identification of Cambrian-to-Cretaceous clastic reservoirs in Pakistan

The use of seismic direct hydrocarbon indicators is very common in exploration and reservoir development to minimise exploration risk and to optimise the location of production wells. DHIs can be enhanced using AVO methods to calculate seismic attributes that approximate relative elastic properties. In this study, we analyse the sensitivity to pore fluid changes of a range of elastic properties by combining rock physics studies and statistical techniques and determine which provide the best basis for DHIs. Gassmann fluid substitution is applied to the well log data and various elastic properties are evaluated by measuring the degree of separation that they achieve between gas sands and wet sands. The method has been applied successfully to well log data from proven reservoirs in three different siliciclastic environments of Cambrian, Jurassic, and Cretaceous ages. We have quantified the sensitivity of various elastic properties such as acoustic and extended elastic (EEI) impedances, elastic moduli (K _sat and K _sat–μ), lambda–mu–rho method (λρ and μρ), P-to-S-wave velocity ratio (V _P/V _S), and Poisson’s ratio (σ) at fully gas/water saturation scenarios. The results are strongly dependent on the local geological settings and our modeling demonstrates that for Cambrian and Cretaceous reservoirs, K _sat–μ, EEI, V _P/V _S, and σ are more sensitive to pore fluids (gas/water). For the Jurassic reservoir, the sensitivity of all elastic and seismic properties to pore fluid reduces due to high overburden pressure and the resultant low porosity. Fluid indicators are evaluated using two metrics: a fluid indicator coefficient based on a Gaussian model and an overlap coefficient which makes no assumptions about a distribution model. This study will provide a potential way to identify gas sand zones in future exploration.     

Study of Shallow Low-Enthalpy Geothermal Resources Using Integrated Geophysical Methods

The paper is focused on low enthalpy geothermal exploration performed in south Italy and provides an integrated presentation of geological, hydrogeological, and geophysical surveys carried out in the area of municipality of Lecce. Geological and hydrogeological models were performed using the stratigraphical data from 51 wells. A ground-water flow (direction and velocity) model was obtained. Using the same wells data, the ground-water annual temperature was modeled. Furthermore, the ground surface temperature records from ten meteorological stations were studied. This allowed us to obtain a model related to the variations of the temperature at different depths in the subsoil. Integrated geophysical surveys were carried out in order to explore the low-enthalpy geothermal fluids and to evaluate the results of the model. Electrical resistivity tomography (ERT) and self-potential (SP) methods were used. The results obtained upon integrating the geophysical data with the models show a low-enthalpy geothermal resource constituted by a shallow ground-water system.     

Evaluating relationships between soil chemical properties and vegetation cover at different slope aspects in a reclaimed dump

Conducting research about the relationships between soil chemical properties and vegetation coverage at different slope aspects is especially important in reconstructed ecosystems of vulnerable ecological regions. This study was conducted in the first reclaimed dump within the Pingshuo mining area of Shanxi Province, China, to analyze patterns of soil chemical properties (soil organic matter (SOM), soil total nitrogen (STN), soil available phosphorus (SAP) and soil available potassium (SAp) and vegetation coverage (NDVI) and their correlations at different slope aspects. In the reclaimed dump, 26 quadrats were established along four slope aspects (i.e., shady, semi-shady, sunny and semi-sunny slopes). There was no significant difference in SOM or STN among different slope aspects, while SAP differed between shady slopes compared to semi-shady, sunny and semi-sunny slopes; SAP differed significantly between semi-shady and semi-sunny slopes. The NDVI of semi-sunny slopes differed significantly from that of the other three aspects. There was variation in the relationships between NDVI and soil chemical properties, depending on the slope aspects. The logarithm of SOM and NDVI was related linearly on shady and semi-shady slopes, while NDVI was inversely related to the natural logarithm of the logarithm of SOM on sunny and semi-sunny slopes. STN and NDVI had a first-order function relationship on shady and semi-shady slopes, yet a quadratic function relationship on sunny and semi-sunny slopes. The relationships between SAP and NDVI were inverse on all types of slopes. On shady and semi-shady slopes, NDVI had a quadratic relationship with the logarithm of SAp, but it was well fitted by using a cubic function on sunny and semi-sunny slopes. The sensitivity coefficients of soil chemical properties and NDVI were different, and soil chemical properties changed differently depending on changes in NDVI at different slope aspects.     

Future wave climate over the west-European shelf seas

In this paper, we investigate changes in the wave climate of the west-European shelf seas under global warming scenarios. In particular, climate change wind fields corresponding to the present (control) time-slice 1961–2000 and the future (scenario) time-slice 2061–2100 are used to drive a wave generation model to produce equivalent control and scenario wave climate. Yearly and seasonal statistics of the scenario wave climates are compared individually to the corresponding control wave climate to identify relative changes of statistical significance between present and future extreme and prevailing wave heights. Using global, regional and linked global–regional wind forcing over a set of nested computational domains, this paper further demonstrates the sensitivity of the results to the resolution and coverage of the forcing. It suggests that the use of combined forcing from linked global and regional climate models of typical resolution and coverage is a good option for the investigation of relative wave changes in the region of interest of this study. Coarse resolution global forcing alone leads to very similar results over regions that are highly exposed to the Atlantic Ocean. In contrast, fine resolution regional forcing alone is shown to be insufficient for exploring wave climate changes over the western European waters because of its limited coverage. Results obtained with the combined global–regional wind forcing showed some consistency between scenarios. In general, it was shown that mean and extreme wave heights will increase in the future only in winter and only in the southwest of UK and west of France, north of about 44–45° N. Otherwise, wave heights are projected to decrease, especially in summer. Nevertheless, this decrease is dominated by local wind waves whilst swell is found to increase. Only in spring do both swell and local wind waves decrease in average height.     

Remote Targets Recognition Based on Adaptive Weighting Feature Dictionaries and Joint Sparse Representations

With the improvement in resolution, more and more useful information is contained in the space of remote sensing images, which makes the processing of remote sensing data become more complex, and it is easy to cause the curse of dimensionality and the poor recognition effect. In this paper, a remote target recognition approach named AJRC is proposed, which uses joint feature dictionary for sparse representation based on different feature information for adaptive weighting. Firstly, the features of the images are extracted to calculate the contribution weight of each eigenvalue in sparse representation, and each eigenvalue contribution weight is calculated in sparse representation. Through the adaptive method, the contribution ability of each feature value in sparse representation is strengthened, and new atoms are formed to construct feature dictionary, which makes the dictionary more discriminative. Then, the common features of each category image and the private features of a single image are extracted from the feature vector, and a joint dictionary is formed to represent the test image sparse and recognize the output of the target. Aiming at the problem that the target visual contrast difference, the low resolution and the rotation of the target with different angles, the experiment is carried out by different feature extraction methods. At the same time, we use the PCA method to reduce the feature dictionary in order to avoid dimensionality. Experiments show that compared with the existing SRC method and JSM method, this method has better recognition rate.