Susceptibility mapping of gully erosion using GIS-based statistical bivariate models: a case study from Ali Al-Gharbi District,Maysan Governorate,southern Iraq

This work aims to evaluate the predictive capability of three bivariate statistical models, namely information value, frequency ratio, and evidential belief functions, in gully erosion susceptibility mapping in northeastern Maysan Governorate (Ali Al-Gharbi District) in southern Iraq. The gully inventory map, consisting of 21 gullies of different sizes, was prepared based on the interpretation of remotely sensed data supported by field survey. The gully inventory data (polygon format) were randomly partitioned into two sets: 14 gullies for build and training the bivariate model, and the remaining 7 gullies for validating purposes. Twelve gully influential factors were selected based on data availability and the literature review. The selected factors were related to lithology, geomorphology, soil, land cover, and topography (primary and secondary) settings. Analysis of factor importance using information gain ratio proved that out of 12 gully influential factors, eight were of more importance in developing gullies (the average merit was greater than zero). The most important factors and the training gully inventory map were used to generate three gully erosion susceptibility maps based on the three bivariate models used. For validation, the area under the operating characteristics curves for both success and prediction rates was used. The results indicated that the highest prediction rate of 82.9% was achieved using the information value technique. All the bivariate models had prediction rates greater than 80%, and thus they were regarded as very good estimators. The final conclusion was that the bivariate models offer advanced techniques for mapping gully erosion susceptibility.     

Examining the rainfall–topography relationship using non-stationary modelling technique in semi-arid Aseer region,Saudi Arabia

The mountainous region of Aseer, corresponding to the Afromontane phytogeographic region, is an eco-sensitive zone and has complex relationship between topography and rainfall. The region is located inland of the red sea escarpment edge in the west. Therefore, rainfall can occur during any month of the year in the mountain of the high Aseer region when moist air forces up the escarpment from the red sea. Monitoring the rainfall data and its topographical elevation variable in Aseer region is an essential requirement for feasible and accurate rainfall-based data for different applications, such as hydrological and ecological resource management in rugged terrain and remote areas. The relationship of elevation and rainfall are spatially non-stationary, non-linear, scale dependent, and often modelled by conventional regression models. Therefore, a local modelling technique, geographically weighted regression (GWR), was applied to deal with non-stationary, non-linear, scale-dependent problems. The GWR using topoclimatic data (elevation and rainfall) to analyse the cumulative rainfall data for rainy months (March to June) of the 4 years estimated from CHIRPS (Climate Hazards Group InfraRed Precipitation with Stations) product for Aseer region. The bandwidth (scale-size) of the Aseer region rainfall–elevation relationship has stabilised at round off 12 km. By selecting the suitable bandwidth, the spatial pattern of the rainfall–elevation relationship was significantly enhanced by using the GWR than the traditional ordinary least squares (OLS) regression model. GWR local modelling techniques estimated well in terms of accuracy, predictive power and decreased residual autocorrelation. Additionally, GWR assesses the significance of local statistic at each location and identified the location of spatial clusters with local regression coefficients significantly improved as compared with global OLS model, thereby highlighting local variations. Therefore, the GWR, local modelling approach managed to produce more accurate estimates by taking into account local characteristics.     

Flood susceptibility mapping using a geomorphometric approach in South Australian basins

Natural Hazards - Watershed characteristics and their hydrological responses can have severe effects on the occurrence and extent of floods. Therefore, this study focuses on the integration of...     

A thermo‐hydro‐mechanical model for unsaturated soils based on the effective stress concept

A simple thermo‐hydro‐mechanical (THM) constitutive model for unsaturated soils is described. The effective stress concept is extended to unsaturated soils with the introduction of a capillary stress. This capillary stress is based on a microstructural model and calculated from attraction forces due to water menisci. The effect of desaturation and the thermal softening phenomenon are modelled with a minimal number of material parameters and based on existing models. THM process is qualitatively and quantitatively modelled by using experimental data and previous work to show the application of the model, including a drying path under mechanical stress with transition between saturated and unsaturated states, a heating path under constant suction and a deviatoric path with imposed suction and temperature. The results show that the present model can simulate the THM behaviour in unsaturated soils in a satisfactory way. Copyright © 2010 John Wiley & Sons, Ltd.     

Evaluation of the Risk of Marine Slope Instability: A Pseudo-3D Approach for Application to Large Areas

Abstract

This article presents a methodology developed to evaluate the instability of submarine slopes that extend over a large area. Special attention was paid to (1) the complex geometry (bathymetry) and the expanse of the slope, (2) the heterogeneity of the sediment, and (3) the distribution of the pore pressure. The safety factor was considered as a spatially varying quantity. The General Formulation (GLE, Fredlund and Krahn 1977), which fully satisfies equilibrium conditions, was used for evaluating the stability of the marine slope. The submarine slope failure, which occurred on 16 October 1979 during the construction of the new Nice airport, was studied in order to test the developed model. Geotechnical parameters were taken from experimental tests carried out by IFREMER on 19 cores extracted at different depths (from 27 m to 1300 m) (Cochonat, Bourillet, and Savoye, 1993; Mulder et al., 1994). Many scenarios were proposed in order to explain the cause of the Nice slope failure (Habib, 1994). In this article, two of those scenarios were tested. Simulation results are presented and discussed.     

15th International Symposium for the Advancement of Boundary Layer Remote Sensing (ISARS)

Announcement

15th International Symposium for the Advancement of Boundary Layer Remote Sensing (ISARS) 28-30 June 2010     

A photometric study of the contact binary XY Boo

The contact binary XY Boo is observed photoelectrically, and variations of the orbital period and the light curves are indicated. NewBV light curves and those of Binnendijk (1971) and Winkler (1977) are analysed by used of the light curve synthesis method. Combining the derived photometric elements with the spectroscopic elements of McLean and Hilditch (1983), we obtain values of the masses and the radii of the components of the system.     

Modeling soil collapse by artificial neural networks

The feasibility of using neural networks to model the complex relationship between soil parameters, loading conditions, and the collapse potential is investigated in this paper. A back propagation neural network process was used in this study. The neural network was trained using experimental data. The experimental program involved the assessment of the collapse potential using the one-dimensional oedometer apparatus. To cover the broadest possible scope of data, a total of eight types of soils were selected covering a wide range of gradation. Various conditions of water content, unit weights and applied pressures were imposed on the soils. For each placement condition, three samples were prepared and tested with the measured collapse potential values averaged to obtain a representative data point. This resulted in 414 collapse tests with 138 average test values, which were divided into two groups. Group I, consisting of 82 data points, was used to train the neural networks for a specific paradigm. Training was carried out until the mean sum squared error (MSSE) was minimized. The model consisting of eight hidden nodes and six variables was the most successful. These variables were: soil coefficient of uniformity, initial water content, compaction unit weight, applied pressure at wetting, percent sand and percent clay. Once the neural networks have been deemed fully trained its accuracy in predicting collapse potential was tested using group II of the experimental data. The model was further validated using information available in the literature. The data used in both the testing and validation phases were not included in the training phase. The results proved that neural networks are very efficient in assessing the complex behavior of collapsible soils using minimal processing of data. This revised version was published online in July 2006 with corrections to the Cover Date.     

Integration of surface and groundwater resources for the development of Hamad Basin project

Hamad Basin (166,000 km²) is an extensive basin, inhabited by 219,000 souls. It is located in the arid region within the border of four Arab States: Syria, Jordan, Iraq, and Saudi Arabia. Average annual precipitation depth is 78 mm, falling mostly during winter.Integrated studies of the natural resources, (water, soil, range, and animal) were carried out with other complementary studies to formulate a socioeconomic development plan for the promissing areas within the basin.Modern technologies were applied such as remote sensing, isotope analysis, processing, and documenting of basic hydrogeological data within the data bank system using computer facilities.Results revealed that the output of the natural dry plant production amounts to 2.0 × 10⁶ tons. Animal wealth comprise 2 × 10⁶ head mainly of sheep. Average annual surface runoff is 146 × 10⁶ m³, which could be appropriately exploited in water spreading schemes to improve range. Water lost presently through evaporation from vast flat depression (Khabra) could be conserved through deepening the Khabras, and recharging shallow perched aquifer by surface runoff, which could be mined later.Results of regional geology, partial geophysical studies, and hydrogeological, hydrochemical interpretations have concuded the existance of two main aquifer systems, the first lies within the tertiary and quaternary formations, while the second extends to the mesozoic, and paleozoic. Their yield varies quantitively and qualitively, up to 100 × 10⁶ m³ could be safely drawn annually.One compound pilot project was selected within the sector of each of the four Arab States to test the feasibility of the proposed development program for the promissing areas of the basin.     

Estimation of ship motions using closed-form expressions

A semi-analytical approach is used to derive frequency response functions for the wave-induced motions for monohull ships. The results are given as closed-form expressions and the required input information for the procedure is restricted to the main dimensions: length, breadth, draught, block coefficient and water plane area together with speed and heading. The formulas make it simple to obtain quick estimates of the wave-induced motions and accelerations in the conceptual design phase and to perform a sensitivity study of the variation with main dimensions and operational profile.