A study on the dependency of GNSS pseudorange biases on correlator spacing

We provide a comprehensive overview of pseudorange biases and their dependency on receiver front-end bandwidth and correlator design. Differences in the chip shape distortions among GNSS satellites are the cause of individual pseudorange biases. The different biases must be corrected for in a number of applications, such as positioning with mixed signals or PPP with ambiguity resolution. Current state-of-the-art is to split the pseudorange bias into a receiver- and a satellite-dependent part. As soon as different receivers with different front-end bandwidths or correlator designs are involved, the satellite biases differ between the receivers and this separation is no longer practicable. A test with a special receiver firmware, which allows tracking a satellite with a range of different correlator spacings, has been conducted with live signals as well as a signal simulator. In addition, the variability of satellite biases is assessed through zero-baseline tests with different GNSS receivers using live satellite signals. The receivers are operated with different settings for multipath mitigation, and the changes in the satellite-dependent biases depending on the receivers’ configuration are observed.     

Extremely large rockslides and rock avalanches in the Tien Shan Mountains, Kyrgyzstan

Most systematic research on large rock-slope failures is geographically biased towards reports from Europe, the Americas, the Himalayas and China. Although reports exist on large rockslides and rock avalanches in the territory of the former Soviet Union, they are not readily available, and few translations have been made. To begin closing this gap, we describe here preliminary data from field reconnaissance, remote sensing and geomorphometry of nine extremely large rock-slope failures in the Tien Shan Mountains of central Kyrgyzstan. Each of these catastrophic and prehistoric failures exceeds an estimated 1 km³ in volume, and two of them involve about 10 km³. Failure of rock slopes in wide valleys favoured the emplacement of hummocky long-runout deposits, often spreading out over >10 km², blocking major rivers. Most of these gigantic slope failures are located on or near active faults. Their spatial clustering and the high seismic activity in the Tien Shan support the hypothesis that strong seismic shaking caused or triggered most of these large-scale rock-slope failures. Nevertheless detailed field studies and laboratory analyses will be necessary to exclude hydroclimatic trigger mechanisms (precipitation, fluvial undercutting, permafrost degradation), and to determine their absolute ages, frequency and the large-landslide hazard of central Kyrgyzstan.     

Localization and regularization for iterative ensemble smoothers

Ensemble-based data assimilation methods have recently become popular for solving reservoir history matching problems, but because of the practical limitation on ensemble size, using localization is necessary to reduce the effect of sampling error and to increase the degrees of freedom for incorporating large amounts of data. Local analysis in the ensemble Kalman filter has been used extensively for very large models in numerical weather prediction. It scales well with the model size and the number of data and is easily parallelized. In the petroleum literature, however, iterative ensemble smoothers with localization of the Kalman gain matrix have become the state-of-the-art approach for ensemble-based history matching. By forming the Kalman gain matrix row-by-row, the analysis step can also be parallelized. Localization regularizes updates to model parameters and state variables using information on the distance between the these variables and the observations. The truncation of small singular values in truncated singular value decomposition (TSVD) at the analysis step provides another type of regularization by projecting updates to dominant directions spanned by the simulated data ensemble. Typically, the combined use of localization and TSVD is necessary for problems with large amounts of data. In this paper, we compare the performance of Kalman gain localization to two forms of local analysis for parameter estimation problems with nonlocal data. The effect of TSVD with different localization methods and with the use of iteration is also analyzed. With several examples, we show that good results can be obtained for all localization methods if the localization range is chosen appropriately, but the optimal localization range differs for the various methods. In general, for local analysis with observation taper, the optimal range is somewhat shorter than the optimal range for other localization methods. Although all methods gave equivalent results when used in an iterative ensemble smoother, the local analysis methods generally converged more quickly than Kalman gain localization when the amount of data is large compared to ensemble size.     

The deep geothermal potential of the Berlin area

In this study, we model the geothermal potential of deep geological formations located in the Berlin region in Germany. Berlin is situated in a sedimentary geological setting (northeastern German basin), comprising low-enthalpic aquifers at horizons down to 4–5 km depth. In the Berlin region, the temperature increases almost linearly with depth by about 30 K per kilometer, thus allowing for direct heating from deep aquifer reservoirs in principle. Our model incorporates eight major sedimentary units (Jurassic, Keuper, Muschelkalk, Upper/Middle/Lower Buntsandstein, Zechstein Salt and Sedimentary Rotliegend). Owing to lack of available petro-physical rock data for the Berlin region, we have evaluated literature data for the larger northeastern German basin to develop a thermodynamic field model which regards depth-corrected equations of state within statistical intervals of confidence. Integration over the thicknesses of the respective structural units yields their “heat in place”—energy densities associated with the pore fluid and the rock matrix under local conditions in Joule per unit area at the surface. The model predicts that aquifers in the Middle Buntsandstein and in the Sedimentary Rotliegend may well exhibit energy densities about 10 GJ m^?2 for the pore fluids and 20 GJ m^?2 to 40 GJ m^?2 for the rock matrices on average. Referring these figures to the city area of Berlin (about 892 km²), a significant hydrothermal potential results, which however remained undeveloped until today for the reason of present development risks. The model accounts for these risks through statistical intervals of confidence which are in the order of ±60 to ±80 % of the trend figures. To minimize these uncertainties, scientific field explorations were required in order to assess the petro-physical aquifer properties locally.     

Forecasting future changes in Manzala Lake surface area by considering variations in land use and land cover using remote sensing approach

This study assesses the changes in surface area of Manzala Lake, the largest coastal lake in Egypt, with respect to changes in land use and land cover based on a multi-temporal classification process. A regression model is provided to predict the temporal changes in the different detected classes and to assess the sustainability of the lake waterbody. Remote sensing is an effective method for detecting the impact of anthropogenic activities on the surface area of a lagoon such as Manzala Lake. The techniques used in this study include unsupervised classification, Mahalanobis distance supervised classification, minimum distance supervised classification, maximum likelihood supervised classification, and normalized difference water index. Data extracted from satellite images are used to predict the future temporal change in each class, using a statistical regression model and considering calibration, validation, and prediction phases. It was found that the maximum likelihood classification technique has the highest overall accuracy of 93.33%. This technique is selected to observe the changes in the surface area of the lake for the period from 1984 to 2015. Study results show that the waterbody surface area of the lake declined by 46% and the area of floating vegetation, islands, and land agriculture increased by 153.52, 42.86, and 42.35% respectively during the study period. Linear regression model prediction indicates that the waterbody surface area of the lake will decrease by 25.24% during the period from 2015 to 2030, which reflects the negative impact of human activities on lake sustainability represented by a severe reduction of the waterbody area.     

Natural hazards,extreme events,and mountain topography

The hazard of any natural process can be expressed as a function of its magnitude and the annual probability of its occurrence in a particular region. Here we expand on the hypothesis that natural hazards have size–frequency relationships that in parts resemble inverse power laws. We illustrate that these trends apply to extremely large events, such as mega-landslides, huge volcanic debris avalanches, and outburst flows from failures of natural dams. We review quantitative evidence that supports the important contribution of extreme events to landscape development in mountains throughout the world, and propose that their common underreporting in the Quaternary record may lead to substantial underestimates of mean process rates. We find that magnitude–frequency relationships provide a link between Quaternary science and natural hazard research, with a degree of synergism and societal importance that neither discipline alone can deliver. Quaternary geomorphology, stratigraphy, and geochronology allow the reconstruction of times, magnitudes, and frequencies of extreme events, whereas natural hazard research raises public awareness of the importance of reconstructing events that have not happened historically, but have the potential to cause extreme destruction and loss of life in the future.     

Computer simulation of flow through a lattice flow-cell model

For single-phase flow through a network model of a porous medium, we report (1) solutions of the Navier–Stokes equation for the flow, (2) micro-particle imaging velocimetry (PIV) measurements of local flow velocity vectors in the “pores throats” and “pore bodies,” and (3) comparisons of the computed and measured velocity vectors. A “two-dimensional” network of cylindrical pores and parallelepiped connecting throats was constructed and used for the measurements. All pore bodies had the same dimensions, but three-different (square cross-section) pore-throat sizes were randomly distributed throughout the network. An unstructured computational grid for flow through an identical network was developed and used to compute the local pressure gradients and flow vectors for several different (macroscopic) flow rates. Numerical solution results were compared with the experimental data, and good agreement was found. Cross-over from Darcy flow to inertial flow was observed in the computational results, and the permeability and inertia coefficients of the network were estimated. The development of inertial flow was seen as a “two-step” process: (1) recirculation zones appeared in more and more pore bodies as the flow rate was increased, and (2) the strengths of individual recirculation zones increased with flow rate. Because each pore-throat and pore-body dimension is known, in this approach an experimental (and/or computed) local Reynolds number is known for every location in the porous medium at which the velocity has been measured (and/or computed).     

Field-aligned conductance values estimated from Maxwellian and kappa distributions in quiet and disturbed events using Freja electron data

We study the question of what difference it makes for the derived field-aligned conductance (K) values if one uses Maxwellian or kappa distributions for the fitting of low-orbiting satellite electron flux spectra in the auroral region. This question has arisen because sometimes a high-energy tail is seen in the spectra. In principle, the kappa fits should always be better, because the kappa distribution is a generalization of the Maxwellian. However, the physical meaning of the parameters appearing in the Maxwellian is clearer. It therefore makes sense to study under which circumstances it is appropriate to use a Maxwellian. We use Freja electron data (TESP and MATE) from two events. One of the events represents quiet magnetospheric conditions (stable arc) and the other represents disturbed conditions (surge). In these Freja events, at least, using kappa rather than Maxwellian fitting gives a better fit to the observed distribution, but the difference in K values is not large (usually less than 20%). The difference can be of either sign. However, sometimes even the kappa distribution does not provide a good fit, and one needs a more complicated distribution such as two Maxwellians. We investigate the relative contributions of the two Maxwellians to the total field-aligned conductance value in these cases. We find that the contribution of the high-energy population is insignificant (usually much less than 20%). This is because K is proportional to n/E_c E_c, where n is the source plasma density and E_c is the characteristic energy.