Developing nonlinear models for sediment load estimation in an irrigation canal

The study was performed to estimate the weekly sediment load in Thal canal located in Mianwali district Punjab, Pakistan. Past records of sediments and discharge have been considered as the input parameters. The best input combinations have been identified with the help of advanced algorithms including full, sequential and increasing embedding, genetic algorithm and hill climbing in combination with the gamma test. Model training has been carried out using two artificial neural network-based algorithms, namely Broyden–Fletcher–Goldfarb–Shanno (BFGS), back-propagation and a local linear regression technique. A variety of statistical parameters including R square, root mean squared error, mean square error and mean bias error (MBE) has been calculated in order to evaluate the best models. The results strongly suggested that BFGS-based model performed better than all other models with remarkably low values of MBE. Significantly high values of correlation coefficient (R square) in both training and testing evidenced a close similarity between actual and predicted sediment load values for the same model.     

Distribution, classification, petrological and related gochemical (SRA) characteristics of a tropical lowland peat dome in the Kota Samarahan-Asajaya area, West Sarawak, Malaysia

Petrographic studies indicate that lateral variations in the decomposition levels of peat are associated with the predominantly occurring peat macerals. Source Rock Analyzer (SRA) results indicate lateral variation in peat organic matter types from type II to III and back again to type II, occurring laterally within the top 0-m to 0.5-m layer at the basin margin to the midsection and further towards the near-center areas of the peat dome. This variation is most likely caused by a combination of factors: (a) Horizontal zonation and lateral variation of the dominant species of plant assemblages (b) Fibric (marginal) peats and hemic to sapric peats associated with type II organic matter (kerogen). Sample organic matter (coal-equivalent kerogen) typing indicates that the relative abundance of phytoclasts and palynomorphs generally supports the organic matter classification obtained by the SRA method. Lateral variations in the peat organic matter types may support the lateral vegetation variation concept. The classification of peat organic matter types (interpreted from visual analyses of palynological slides) occurring from the basin periphery to the mid-section and further towards the basin center yields organic matter of type II to type III and mixed types II to III (coal kerogen-equivalent), respectively.     

Study on mechanochemical effect of silica for short grinding period

Silica was ground in an oscillating mill at various grinding period to study the mechanochemical effect in fine grinding process. The ground particles exhibited massive size reduction where the volume moment diameter of 5.56 μm was reached within 600 s. Aggregation of fine particles was very pronounced when it was ground for 600 s due to high surface energy. Aggregation of fine particles caused the ground particles to exhibit poly-modal particle size distribution. Line broadening and reduction of diffractogram peak intensity were observed. Amorphization rate up to 16.9% was exhibited by the particle ground for 600 s. Preferential breakage of plane was observed where (101) and (111) was easily distorted compared to (110) and (200). Rapid reduction of crystallite size was observed at early stage of grinding until it reached a plateau at 5 nm at 600 s whilst the change in lattice strain was 0.5%.     

The Response of Macrobenthic Communities to Environmental Variability in Tropical Coastal Waters

The relative contributions of spatial and temporal fluctuations are different in shaping natural communities in a tropical coastal/estuarine system. Understanding how coastal communities respond to these fluctuations is still equivocal, and thus, available data are rare. Here, multiple analytical approaches were used to identify key spatial and temporal factors, and to quantify their relative roles in shaping a macrobenthic community through space (contamination degree, physical parameters, and sediment characteristics) and time (climatic factors, season, and year). A dataset of eight sampling times was analyzed over a period of 2 years, in which macrobenthic species abundances were sampled. A total of 33 species were identified, including 18 bivalves, 5 gastropods, and 4 crustaceans. The other taxa were less diverse. The results show that there were no significant temporal changes of macrobenthic community structure, but spatial changes were significant and synchronized with environmental factors (i.e., sediment characteristics, water depth, and the distance from anthropogenic sources). This study demonstrates that spatial factors played a primary role in structuring of macrobenthic assemblages, whereas the influence of temporal factors appeared less across geographically distinct sites. Thus, temporal variation of a coastal macrobenthic community appears to be controlled by partly different processes at different scales.     

Effect of land use land cover changes on land surface temperature during 1984–2020: a case study of Baghdad city using landsat image

Natural Hazards - Urban land surface temperature (LST) is dependent on many factors, including land cover, building materials, urban density, and other human activities. The current study evaluated...     

Fusion Methods and Multi-classifiers to Improve Land Cover Estimation Using Remote Sensing Analysis

Geotechnical and Geological Engineering - Adopting a low spatial resolution remote sensing imagery to get an accurate estimation of Land Use Land Cover is a difficult task to perform. Image fusion...     

Geophone‐ground coupling with flat bases

Seismic acquisition can be costly and inefficient when using spiked geophones. In most cases, such as the desert, the most practical solution is the use of flat bases, where geophone‐ground coupling is based on an optimal choice of the mass and area of contact between the receiver and the ground. This optimization is necessary since areas covered by sand are loose sediments and poor coupling occurs. Other cases include ground coupling in stiff pavements, for instance urban areas and ocean‐bottom nodes. We consider three different approaches to analyse coupling and model the geophone with a flat base (plate) resting on an elastic half‐space. Two existing models, based on the full‐wave theory, which we refer to as the Wolf and Hoover‐O'Brien models, predict a different behaviour with respect to the novel method introduced in this work. This method is based on the transmission coefficient of upgoing waves impinging in the geophone‐ground contact, where the ground is described as an anelastic half‐space. The boundary conditions at the contact have already been used to model fractures and are shown here to provide the equation of the damped oscillator. This fracture‐contact model depends on the stiffness characteristic of the contact between the geophone base plate and the ground. The transmission coefficient from the ground to the plate increases for increasing weight and decreasing base plate area. The new model predicts that the resonant frequency is independent of the geophone weight and plate radius, while the recorded energy increases with increasing weight and decreasing base plate area (as shown from our own experiments and measurements by Krohn) which is contrary to the theories developed by Wolf and Hoover‐O'Brien. The transient response is obtained by an inverse Fourier transform. Optimal geophone‐ground coupling and energy transmission are required, the first concept meaning that the geophone is following the motion of the ground and the second one that the signal is detectable. As a final example, we simulate seismic acquisition based on the novel theory, showing the differences between optimal and poor ground‐to‐geophone energy transmission.     

An integrated approach to coastal rehabilitation: Mangrove restoration in Sungai Haji Dorani,Malaysia

To achieve an efficient method of coastal rehabilitation, a coastal structure was applied in combination with the mangrove restoration scheme in Sungai Haji Dorani where coastal forest over-cutting associated with erosion has resulted in severe coastline retreat. Such an attempt provides the opportunity to mitigate erosion as well as improve ecological and socio-economic aspects of coastal areas, both of which are of great importance to local communities and authorities. Beach morphological changes were monitored for an eight-month period of time. The results indicate that the attempt has been successful in retaining sediment on the beach and consequently raising the elevation of the site. While the monitoring schedule is required to continue for several years to evaluate long-term performance of the rehabilitation effort, approximately 30% of the transplanted mangrove saplings' survival after eight months shows that the project was moderately successful. Since the general conditions of the selected site represent the majority of the eroded shorelines on the west coast of Peninsular Malaysia, the method applied in this study can be replicated as an appropriate cost-effective alternative for the same cases.     

Modification of fractal algorithm for oil spill detection from RADARSAT-1 SAR data

This paper introduces a modified formula for the fractal box counting dimension. The method is based on utilization of the probability distribution formula in the fractal box count. The purpose of this method is to use it for the discrimination of oil spill areas from the surrounding features, e.g., sea surface and look-alikes in RADARSAT-1 SAR Wide beam mode (W1) and Standard beam mode (S2) data have been collected under different wind speeds. The results show that the new formula of the fractal box counting dimension is able to discriminate between oil spills, look-alike areas and pixels of the size of a single ship. The W1 mode data illustrate an error standard deviation of 0.05, thus performing a better discrimination of oil spills as compared to S2 mode data. We conclude that automatic detection and discrimination of oil spill and other sea surface features can be opertionalized by using the new formula for fractal box counting.