Testing the weak stationarity of a spatio-temporal point process

A common assumption in analyzing spatial and spatio-temporal point processes is stationarity, while in many real applications because of the environmental effects the stationarity condition is not often met. We propose two types of test statistics to test stationarity for spatio-temporal point processes, by adapting, Palahi, Pukkala & Mateu (2009) and by considering the square difference between observed and expected (under stationarity) intensities. We study the efficiency of the new statistics by simulated data, and we apply them to test the stationarity of real data.     

Signature of the upper mantle density structure in the refined gravity data

The gravitational signal of the upper mantle density structures is investigated in the refined gravity data which are corrected for the gravitational contributions of the crust density structures and the Moho geometry. The gravimetric forward modeling is applied to compute these refined gravity data globally on a 1 × 1 arcdeg grid using the global geopotential model (EGM2008), the global topographic/bathymetric model (DTM2006.0) including the ice-thickness data, and the global crustal model (CRUST2.0). The characteristics of the upper mantle density structures are further analyzed in association with the Moho parameters (i.e., Moho depths and density contrast). The 1 × 1 arcdeg global data of the Moho parameters are estimated by applying the combined least-squares approach based on solving Moritz’s generalization of the Vening–Meinesz inverse problem of isostasy. The refined gravity data exhibit mainly the mantle lithosphere structures attributed to the global mantle convection. A significant correlation found over oceans between the refined gravity data and the Moho density contrast is explained by the increasing density of the oceanic lithosphere with age. Despite the lithosphere structures attributed to the global mantle convection are confirmed also in the refined gravity data over continents, the significant correlation between the refined gravity data and the Moho parameters is in this case absent. Instead, the significant proportion of lateral variations of the Moho density contrast within the continental lithosphere is attributed to the depth-dependant density changes due to pressure and thermal gradient.     

A general weighted total Kalman filter algorithm with numerical evaluation

An applicable algorithm for Total Kalman Filter (TKF) approach is proposed. Meanwhile, we extend it to the case in which we can consider arbitrary weight matrixes for the observation vector, the random design matrix and possible correlation between them. Also the updated dispersion matrix of the predicted unknown is given. This approach makes use of condition equations and straightforward variance propagation rules. It is applicable to data fusion within a dynamic errors-in-variables (DEIV) model, which usually appears in the determination of the position and attitude of mobile sensors. Then, we apply for the first time the TKF algorithm and its extended version named WTKF to a DEIV model and compare the results. The results show the efficiency of the proposed WTKF algorithm. In particular in the case of large weights, WTKF shows approximately 25% improvement in contrast to TKF approach.     

Dynamics of hourly sea level at Hillarys Boat Harbour,Western Australia: a chaos theory perspective

Water level forecasting using recorded time series can provide a local modelling capability to facilitate local proactive management practices. To this end, hourly sea water level time series are investigated. The records collected at the Hillarys Boat Harbour, Western Australia, are investigated over the period of 2000 and 2002. Two modelling techniques are employed: low-dimensional dynamic model, known as the deterministic chaos theory, and genetic programming, GP. The phase space, which describes the evolution of the behaviour of a nonlinear system in time, was reconstructed using the delay-embedding theorem suggested by Takens. The presence of chaotic signals in the data was identified by the phase space reconstruction and correlation dimension methods, and also the predictability into the future was calculated by the largest Lyapunov exponent to be 437 h or 18 days into the future. The intercomparison of results of the local prediction and GP models shows that for this site-specific dataset, the local prediction model has a slight edge over GP. However, rather than recommending one technique over another, the paper promotes a pluralistic modelling culture, whereby different techniques should be tested to gain a specific insight from each of the models. This would enable a consensus to be drawn from a set of results rather than ignoring the individual insights provided by each model.     

A spatio-temporal three-dimensional conceptualization and simulation of Dera Ismail Khan alluvial aquifer in visual MODFLOW: a case study from Pakistan

Dera Ismail Khan (DIK) is situated in the Lower Indus Basin of Pakistan. The land use has been changed in the canal command area due to irrigation activities near the Indus River. To check the current status and predict the groundwater levels in the area, the unconfined aquifer has been simulated in Visual MODFLOW for a period of 35 years, i.e., from 1985 to 2020. The 2900-km² area has been modeled with a grid of 500 by 500 m and the depth set to 100 m. The aquifer in the study area has been divided vertically and laterally into three and ten zones, respectively, for the characterization. Water wells and streams were used as the sinks and hydrologic boundaries, respectively. The model was successfully calibrated in steady and the non-steady state. The simulation revealed that the whole simulation can be divided into two phases, i.e., before and after the construction of the Chashma Right Bank Canal (CRBC), whereas the results were summarized in the form of water table depth maps and groundwater budget calculations. To determine the groundwater sustainability, a conjunctive use scenario has been employed to simulate the aquifer dynamics till 2020. The simulation revealed incremental drawdowns till the end.     

Evaluation of nonlinear models for precipitation forecasting

Prediction of factors affecting water resources systems is important for their design and operation. In hydrology, wavelet analysis (WA) is known as a new method for time series analysis. In this study, WA was combined with an artificial neural network (ANN) for prediction of precipitation at Varayeneh station, western Iran. The results obtained were compared with the adaptive neural fuzzy inference system (ANFIS) and ANN. Moreover, data on relative humidity and temperature were employed in addition to rainfall data to examine their influence on precipitation forecasting. Overall, this study concluded that the hybrid WANN model outperformed the other models in the estimation of maxima and minima, and is the best at forecasting precipitation. Furthermore, training and transfer functions are recommended for similar studies of precipitation forecasting.     

On the occurrence and origin of anthropogenic radionuclides found in a fragment of the Chelyabinsk (LL5) meteorite

A piece of the 2013 Chelyabinsk meteorite was investigated for its content of anthropogenic radionuclides. In addition to traces of cesium‐137 that had been previously reported for this particular fragment, we found an unusually high amount of strontium‐90, which indicates that the source of this contamination was the Kyshtym accident (1957). A high Sr‐90/Cs‐137 activity ratio is characteristic for Kyshtym‐derived contaminations. Based on the cesium‐137 content in the soil from the finding site, it is estimated that the fragment was contaminated with soil particles in the milligram range upon impact. Investigation of the soil revealed very unusual ferromagnetic characteristics and an iron‐rich chemical composition. Mössbauer spectroscopy indicated the presence of steel components in this soil, suggesting that the investigated meteorite fragment was found in an industrial dumping site rather than natural soil.     

Crustal structure of Northwest Zagros (Kermanshah) and Central Iran (Yazd and Isfahan) using teleseismic Ps converted phases

Receiver functions are widely employed to detect P-to-S converted waves and are especially useful to image seismic discontinuities in the crust. In this study we used the P receiver function technique to investigate the velocity structure of the crust beneath the Northwest Zagros and Central Iran and map out the lateral variation of the Moho boundary within this area. Our dataset includes teleseismic data (M _b ≥ 5.5, epicentral distance from 30° to 95°) recorded at 12 three-component short-period stations of Kermanshah, Isfahan and Yazd telemetry seismic networks. Our results obtained from P receiver functions indicate clear Ps conversions at the Moho boundary. The Moho depths were firstly estimated from the delay time of the Moho converted phase relative to the direct P wave beneath each network. Then, we used the P receiver function inversion to find the properties of the Moho discontinuity such as depth and velocity contrast. Our results obtained from PRF are in good agreement with those obtained from the P receiver function modeling. We found an average Moho depth of about 42 km beneath the Northwest Zagros increasing toward the Sanandaj-Sirjan Metamorphic Zone and reaches 51 km, where two crusts (Zagros and Central Iran) are assumed to be superposed. The Moho depth decreases toward the Urmieh-Dokhtar Cenozoic volcanic belt and reaches 43 km beneath this area. We found a relatively flat Moho beneath the Central Iran where, the average crustal thickness is about 42 km. Our P receiver function modeling revealed a shear wave velocity of 3.6 km/s in the crust of Northwest Zagros and Central Iran increasing to 4.5 km/s beneath the Moho boundary. The average shear wave velocity in the crust of UDMA as SSZ is 3.6 km/s, which reaches to 4.0 km/s while in SSZ increases to 4.3 km/s beneath the Moho.