Volatility modeling of rainfall time series

Networks of rain gauges can provide a better insight into the spatial and temporal variability of rainfall, but they tend to be too widely spaced for accurate estimates. A way to estimate the spatial variability of rainfall between gauge points is to interpolate between them. This paper evaluates the spatial autocorrelation of rainfall data in some locations in Peninsular Malaysia using geostatistical technique. The results give an insight on the spatial variability of rainfall in the area, as such, two rain gauges were selected for an in-depth study of the temporal dependence of the rainfall data-generating process. It could be shown that rainfall data are affected by nonlinear characteristics of the variance often referred to as variance clustering or volatility, where large changes tend to follow large changes and small changes tend to follow small changes. The autocorrelation structure of the residuals and the squared residuals derived from autoregressive integrated moving average (ARIMA) models were inspected, the residuals are uncorrelated but the squared residuals show autocorrelation, and the Ljung–Box test confirmed the results. A test based on the Lagrange multiplier principle was applied to the squared residuals from the ARIMA models. The results of this auxiliary test show a clear evidence to reject the null hypothesis of no autoregressive conditional heteroskedasticity (ARCH) effect. Hence, it indicates that generalized ARCH (GARCH) modeling is necessary. An ARIMA error model is proposed to capture the mean behavior and a GARCH model for modeling heteroskedasticity (variance behavior) of the residuals from the ARIMA model. Therefore, the composite ARIMA–GARCH model captures the dynamics of daily rainfall in the study area. On the other hand, seasonal ARIMA model became a suitable model for the monthly average rainfall series of the same locations treated.     

Groundwater resources assessment using integrated geophysical techniques in the southwestern region of Peninsular Malaysia

Combined geophysical techniques such as multi-electrode resistivity, induced polarization, and borehole geophysical techniques were carried out on volcano-sedimentary rocks in the north of Gemas as part of the groundwater resource’s investigations. The result identifies four resistivity units: the tuffaceous mudstone, tuffaceous sandstone, the tuff bed, and the shale layer. Two types of aquifer systems in terms of storage were identified within the area: one within a fracture system (tuff), which is the leaky area through which vertical flow of groundwater occurs, and an intergranular property of the sandy material of the aquifer which includes sandstone and tuffaceous sandstone. The result also reveals that the aquifer occupies a surface area of about 3,250,555 m² with a mean depth of 43.71 m and a net volume of 9.798?×?10⁷?m³. From the approximate volume of the porous zone (28 %) and the total aquifer volume, a usable capacity of (274.339?±?30.177)?×?10⁷?m³ of water in the study area can be deduced. This study provides useful information that can be used to develop a much broader understanding of the nature of groundwater potential in the area and their relationship with the local geology.     

A Simplified Semi-Automatic Technique for Highway Extraction from High-Resolution Airborne LiDAR Data and Orthophotos

Information on highways is an essential input for various geospatial applications, including car navigation, forensic analysis on highway geometries, and intelligent transportation systems. Semi-automatic and automatic extractions of highways are critical for the regular updating of municipal databases and for highway maintenance. This study presents a semi-automatic data processing approach for extracting highways from high-resolution airborne LiDAR height information and aerial orthophotos. The method was developed based on two data sets. Experimental results for the first testing site showed that the accuracy of the proposed method for highway extraction was 74.50 % for completeness and 73.13 % for correctness. Meanwhile, the completeness and correctness for the second testing site were 71.20 and 70.72 %, respectively. The proposed method was compared with an object-based approach on a different data set. The accuracy for highway extraction of the object-based approach was 64.29 % for completeness and 63.11 % for correctness, whereas that of the proposed method was 67.14 % for completeness and 65.08 % for correctness. This research aims to promote semi-automatic highway extraction from LiDAR data and orthophotos by proposing a new approach and a multistep post-processing technique. The proposed method provides an accurate final output that is valuable for a wide range of geospatial applications.     

Paleomagnetism of Carboniferous sediments from the West Sudetes (SW Poland)

The studied Carboniferous flysch and molasse sediments from the Intra-Sudetic Basin correspond to the period from Middle Visean to Early Autunian. Main magnetic minerals carrying the natural remanent magnetization (NRM) are goethite, magnetite, maghemite and hematite, all usually secondarily formed and/or remagnetized due to several tectonometamorphic events. In most samples several NRM components were isolated. One of them is usually a Jurassic-Triassic overprint. Some others define the Westphalian-Early Permian segment of the declination and inclination trajectory for the Sudetes calculated according to the reference apparent polar wander path for the Baltica plate. The Sudetic path is slightly shifted to the east compared to the reference path, suggesting the possibility of independent movements of the Sudetes during this time. The majority of isolated NRM components are secondary and related to the Sudetic orogenic phase and later tectonometamorphic activity.     

Effect of hot dry summer tropical climate on forage intake and milk yield in Holstein–Friesian and indigenous zebu cows in Sudan

The effects of dry summer ambient temperature on some physiological and productive responses were studied in an exotic European breed (Holstein–Friesian) and a local zebu breed (Butana ecotype) of cattle in Sudan. Rectal temperature and respiration rate were positively correlated, and dry matter intake and milk yield were negatively correlated with variation in ambient temperature. However, significant adverse effects on high ambient temperature were only observed in the exotic breed.     

The Southern Sudanese migration to Khartoum and the resultant conflicts

Today, more than one third of the population of Khartoum are southerners who migrated to the capital mainly in the last eight years because of the civil war. Their conditions are very bad. They are starving in the town, for most of them are unemployed and have no means of living. Their housing conditions in the shanty towns are deplorable. The development of squatter settlements and the struggle for the demarcation of quarters are delineated in this paper. In Khartoum the southerners develop a strong sense of solidarity and develop a growing supra-southern-Sudanese identity replacing the former ethnic and local identities.     

Efficiency of reduced-order, time-dependent adjoint data assimilation approaches

Applications of adjoint data assimilation, which is designed to bring an ocean circulation model into consistency with ocean observations, are computationally demanding. To improve the convergence rate of an optimization, reduced-order optimization methods that reduce the size of the control vector by projecting it onto a limited number of basis functions were suggested. In this paper, we show that such order reduction can indeed speed up the initial convergence rate of an assimilation effort in the eastern subtropical North Atlantic using in situ and satellite data as constraints. However, an improved performance of the optimization was only obtained with a hybrid approach where the optimization is started in a reduced subspace but is continued subsequently using the full control space. In such an experiment about 50% of the computational cost can be saved as compared to the optimization in the full control space. Although several order-reduction approaches seem feasible, the best result was obtained by projecting the control vector onto Empirical Orthogonal Functions (EOFs) computed from a set of adjusted control vectors estimated previously from an optimization using the same model configuration.