Contribution of offshore islands in the prediction of water levels due to tide�Csurge interaction for the coastal region of Bangladesh

In this study, a doubly nested tide?Csurge interaction model was established for the coastal region of Bangladesh. A fine grid model, capable of incorporating all major offshore islands, was nested into a coarse grid model extending up to 15°N latitude of the Bay of Bengal. To take into account the thickly populated small and big islands between Barisal and Chittagong and the extreme bending of the coastline accurately, a very fine grid model for this region was again nested into the fine grid model. Along the northeast corner of this very fine grid model, the Meghna River discharge was taken into account. The boundaries of the coast and islands were approximated through proper stair step, and the model equations were solved by semi?Cimplicit finite difference technique using staggered grid. Appropriate tidal regime over the model domain was generated by forcing the sea level to be oscillatory with the constituent M2 along the southern open boundary of the coarse grid model omitting wind stress. This previously generated tidal regime was introduced as the initial state of the sea for nonlinear tide?Csurge interaction phenomenon. The model was applied to estimate water levels along the coastal region of Bangladesh due to the interaction of tide and surge associated with the storm April 1991, and the results were found to be in a reasonable agreement with those observed. The model was used to investigate the influence of offshore islands on water levels and water levels were found to be significantly influenced by offshore islands.     

Assessing building vulnerability to earthquake and tsunami hazard using remotely sensed data

Quantification of building vulnerability to earthquake and tsunami hazards is a key component for the implementation of structural mitigation strategies fostering the essential shift from post-disaster crisis reaction to preventive measures. Facing accelerating urban sprawl and rapid structural change in modern urban agglomerations in areas of high seismic and tsunami risk, the synergetic use of remote sensing and civil engineering methods offers a great potential to assess building structures up-to-date and area-wide. This paper provides a new methodology contextualizing key components in quantifying building vulnerability with regard to sequenced effects of seismic and tsunami impact. The study was carried out in Cilacap, a coastal City in Central Java, Indonesia. Central is the identification of significant correlations between building characteristics, easily detectable by remote sensing techniques, and detailed in situ measurements stating precise building vulnerability information. As a result, potential vertical evacuation shelters in the study area are detected and a realistic vulnerability assessment of the exposed building stock is given. These findings obtained allow for prioritization of intervention measures such as awareness and preparedness strategies and can be implemented in local disaster management.     

Coupling short-time sequencing batch reactor and coagulation–settling process for co-treatment of landfill leachate with raw municipal wastewater

The co-treatment of landfill leachate (LFL) with municipal wastewater (MWW) using shortcut sequencing batch reactor combined with coagulation–settling process (SBR + CS) was investigated. Four ratios of LFL to MWW volume (v/v) were used during experiments including the ratios 1:9, 2:8, 3:7 and 5:5. The average quality of the LFL was chemical oxygen demand (COD) of 20,800 mg L^?1 and NH₄-N of 2,645 mg L^?1. The SBR-treating LFL in six series where mixing aeration and settling phases were varied from 4 to 14 h was combined with coagulation (FeCl₃, Al₂(SO₄)₃) with an interval of 2 h. It was found that ratio (1:9) of leachate to MWW under aeration and mixing phase of 4 h with settling time of 1.5 h exhibited the highest ability to remove both COD and NH ₄ ⁺ -N, 99% and 85%, respectively. The short-time sequential batch reactor was tested for the treatment of raw LFL, and only 47% and 23% removal of COD and NH ₄ ⁺ -N, respectively, could be achieved.     

Forecasting flood risk in the Indus River system using hydrological parameters and its damage assessment

Hydrological parameters are among the widely used parameters in assessing flood risk. On the other hand, anticipated flood damages, in case of flooding, are estimated with the help of expected losses in areas nearer to the watercourse. The major source of almost every-year flooding in Pakistan is the Indus River system that comprises the major rivers of Pakistan. We first use observed data to construct simulated data models based on various probability distributions namely normal, lognormal, Weibull, largest extreme value, gamma-3, and log-Pearson type-3 distributions and thereby compute probable maximum flood. Secondly, we perform log-Pearson type-3 analysis with and without historic adjustment on the observed data series of 17 years to forecast floods with return periods T of 2, 5, 10, 25, 50, 100, and 200 years. We also categorize the river structures based on the risk of flooding. Lastly, we estimate risk of flood damages in terms of expected losses based on observed data. The present study reveals that the log-Pearson type-3 distribution is relatively better for estimating probable maximum flood. We use exceedence probability to assess the risk of flooding in the various structures of the said rivers. The analysis shows that flood damages in Pakistan may be reduced by increasing the design capacity of the structures and also by giving awareness to people about the flood-generating factors.     

Geotechnical assessment of ground conditions around a tilted building in Cairo, Egypt using geophysical approaches

The flood plain of the Nile River has been a safe dwelling throughout history. Recently with a growing population and vast growing urbanization, some buildings have started to experience structural damages, which are not related to their construction design, but rather to the ground conditions around the buildings' foundations. Variations in properties of the soil supporting the buildings' foundations such as soil-bearing capacity, moisture content, and scouring may eventually lead to the failure of these buildings. This study is attempting to characterize the variations in the soil properties around the City Star shopping mall, in eastern Cairo, where a large building has tilted over the past few years. This tilting may lead to the collapse of the whole building if it continues at the same rate. An integrated geophysical investigation including multi-channel analysis of surface wave (MASW), ground-penetrating radar (GPR), and 2-D electrical resistivity tomography (ERT) was used around the affected building to help detect possible causes of deterioration. The GPR data showed a soil-filled layer overlaying a thick bottom layer of higher moisture content. The MASW data revealed a middle layer of relatively low shear wave velocity sandwiched between two relatively high shear wave velocity layers. The ERT data showed an upper low resistivity layer overlying a high resistivity layer. Integrating the interpretations of the three geophysical methods provides a combined model that reflects lateral and vertical variation in the soil properties. This variation becomes dramatic near the tilted corner of the building.     

Influence of geological structures on groundwater accumulation and groundwater salinity in Musandam Peninsula,UAE and Oman

The hydrological setting and groundwater quality of Musandam Peninsula was studied to investigate the influence of geological structures on the groundwater accumulation and groundwater salinity. Five sets of modified morphometric maps were used to reduce errors and carry out the geological structures. The modification was modified by applying mean filter to the Digital Elevation Model (DEM) then applying Soble filter with 10% threshold and equalization enhancement. D8 and algorithms were used to reveal the drainage basins and drainage networks of the entire area. The algorithm determines into which neighbouring pixel any water in a central pixel will flow naturally. Flow direction in a DEM is calculated for every central pixel of input blocks of a 3 × 3 window, all the time comparing the value of the central pixel in the window with the value of its eight neighbours. The spatial association between geological structures and drainage networks was studied using 2D graph and rose diagrams. Flood basin model was applied to simulate the Arabian Gulf water intrusion into the coastal aquifer. The concentrations of solutes in groundwater samples collected from Wadi Al Bih well field and well locations were correlated with the geological structure trends and intersections. The results of the study reveal that the drainage basins, drainage network and groundwater quality are structurally controlled by subsurface geological structure displacements.     

A new bivariate Gamma distribution generated from functional scale parameter with application to drought data

Univariate and bivariate Gamma distributions are among the most widely used distributions in hydrological statistical modeling and applications. This article presents the construction of a new bivariate Gamma distribution which is generated from the functional scale parameter. The utilization of the proposed bivariate Gamma distribution for drought modeling is described by deriving the exact distribution of the inter-arrival time and the proportion of drought along with their moments, assuming that both the lengths of drought duration (X) and non-drought duration (Y) follow this bivariate Gamma distribution. The model parameters of this distribution are estimated by maximum likelihood method and an objective Bayesian analysis using Jeffreys prior and Markov Chain Monte Carlo method. These methods are applied to a real drought dataset from the State of Colorado, USA.     

Determining the susceptibility of Eucalyptus nitens forests to Coryphodema tristis (cossid moth) occurrence in Mpumalanga,South Africa

The cossid moth, Coryphodema tristis was first noted on Eucalyptus nitens trees in Mpumalanga province, South Africa during July 2004. Currently, the moth poses a major threat to commercial forestry in the country. In this study, selected climatic and topographical variables were used to model the susceptibility of E. nitens forests to cossid moth occurrence, thereby providing insight into the variables that may influence the occurrence and spread of the moth. A zigzag sampling technique was used to survey 5316 ha of E. nitens forests for the presence or absence of the moth. The random forest classification algorithm was then used to model the relationship between the climatic and topographical variables and the occurrence of the cossid moth. Results indicate that four variables that included elevation, maximum temperature for September, maximum temperature for April and the median rainfall for April best explained the presence or absence of C. tristis with an overall accuracy of 82% and a kappa value of 0.63. Partial dependence plots indicated that the areas that have a maximum temperature greater than 23°C in September and 22°C in April are likely to be infested by the cossid moth. The results from this study provide a robust and accurate spatial framework to assist forest managers in focussing their existing monitoring and control efforts to specific E. nitens forested areas that are highly susceptible to C. tristis infestations.     

Using geographically weighted regression kriging for crop yield mapping in West Africa

Geographical information systems support the application of statistical techniques to map spatially referenced crop data. To do this in the optimal way, errors and uncertainties have to be minimized that are often associated with operations on the data. This paper applies a spatial statistical approach to upscale crop yields from the field level toward the scale of Burkina Faso. Observed yields were related to the Normalized Difference Vegetation Index derived from SPOT-VEGETATION. The objective was to quantify the uncertainties at the subsequent steps. First, we applied a point pattern analysis to examine uncertainties due to the sampling network of field surveys in the country. Second, geographically weighted regression kriging (GWRK) was applied to upscale the yield observations and to quantify the corresponding uncertainty. The proposed method was demonstrated with the mapping of sorghum yields in Burkina Faso and results were compared with those from regression kriging (RK) and kriging with external drift using a local kriging neighborhood (KEDLN). The proposed method was validated with independent yield observations obtained from field surveys. We observed that the lower uncertainty range value increased by 39%, and the upper uncertainty range value decreased by 51%, when comparing GWRK with RK and KEDLN. Moreover, GWRK reduced the prediction error variance as compared to RK (20 vs. 31) and to KEDLN (20 vs. 39). We found that climate and topography had a major impact on the country’s sorghum yields. Further, the financial ability of farmers influenced the crop management and, thus, the sorghum crop yields. We concluded that GWRK effectively utilized information present in the covariate datasets and improved the accuracies of both the regional-scale mapping of sorghum yields and was able to quantify the associated uncertainty.