Javed Mallick

Risk assessment of soil erosion in semi-arid mountainous watershed in Saudi Arabia by RUSLE model coupled with remote sensing and GIS

Soil erosion is the most important factor in land degradation and influences desertification in semi-arid areas. A comprehensive methodology that integrates revised universal soil loss equation (RUSLE) model and GIS was adopted to determine the soil erosion risk (SER) in semi-arid Aseer region, Saudi Arabia. Geoenvironmental factors viz. rainfall (R), soil erodibility (K), slope (LS), cover management and practice factors were computed to determine their effects on average annual soil loss. The high potential soil erosion, resulting from high denuded slope, devoid of vegetation cover and high intensity rainfall, is located towards the north western part of the study area. The analysis is investigated that the SER over the vegetation cover including dense vegetation, sparse vegetation and bushes increases with the higher altitude and higher slope angle. The erosion maps generated with RUSLE integrated with GIS can serve as effective inputs in deriving strategies for land planning/management in the environmentally sensitive mountainous areas.

Spatial variability of soil erodibility and its correlation with soil properties in semi-arid mountainous watershed, Saudi Arabia

Soil erodibility values are best estimated from long-term direct measurements on runoff-plots; however, in lack of field tests, these values can be estimated using relationships based on physico-chemical soil properties. The study objective was to assess the erodibility and its correlation with soil properties. The average erodibility value was estimated 0.043 t ha h ha−1 MJ−1 mm−1. The areas with heavy textured soil and low organic matter content had the lowest values of erodibility. The erodibility decreases as the sand content increases, whereas silt showed a positive correlation. The erodibility factors and its relation to soil properties were evaluated using multiple regression analysis. Results revealed that sand and organic matter content of soil combinedly explained 78% of variation. Altitudinal increases also seem to affect the soil texture. This study has demonstrated that soil properties and erodibility values can be used as assistance for soil conservation practices and modelling of landscape processes.

Evaluating the co-relationship between concrete flexural tensile strength and compressive strength

The relationship of flexural tensile strength and compressive strength for different range of concrete strength proposed by various authors and country standards indicate diverse and wide variations in recommendations to predict the concrete flexural tensile strength. This paper presents the experimental study to predict flexural tensile strength and compressive strength improved empirical relations using statistical procedures for wide range of concrete strength (35 to 100 MPa) and for different member depth of concrete (80 to 250 mm). It is concluded from study that the flexural tensile strength and compressive strength proportionality equations should be derived in power model for more precision, and the size of the member should also be included in the proportionality equations in addition to compressive strength.

GIS-based landslide susceptibility evaluation using fuzzy-AHP multi-criteria decision-making techniques in the Abha Watershed, Saudi Arabia

AbstractLandslides are natural geological disasters causing massive destructions and loss of lives, as well as severe damage to natural resources, so it is essential to delineate the area that probably will be affected by landslides. Landslide susceptibility mapping (LSM) is making increasing implications for GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. It is considered to be an effective tool to understand natural disasters related to mass movements and carry out an appropriate risk assessment. This study is based on an integrated approach of GIS and statistical modelling including fuzzy analytical hierarchy process (FAHP), weighted linear combination and MCE models. In the modelling process, eleven causative factors include slope aspect, slope, rainfall, geology, geomorphology, distance from lineament, distance from drainage networks, distance from the road, land use/land cover, soil erodibility and vegetation proportion were identified for landslide susceptibility mapping. These factors were identified based on the (1) literature review, (2) the expert knowledge, (3) field observation, (4) geophysical investigation, and (5) multivariate techniques. Initially, analytical hierarchy process linked with the fuzzy set theory is used in pairwise comparisons of LSM criteria for ranking purposes. Thereafter, fuzzy membership functions were carried out to determine the criteria weights used in the development of a landslide susceptibility map. These selected thematic maps were integrated using a weighted linear combination method to create the final landslide susceptibility map. Finally, a validation of the results was carried out using a sensitivity analysis based on receiver operator curves and an overlay method using the landslide inventory map. The study results show that the weighted overlay analysis method using the FAHP and eigenvector method is a reliable technique to map landslide susceptibility areas. The landslide susceptibility areas were classified into five categories, viz. very low susceptibility, low susceptibility, moderate susceptibility, high susceptibility, and very high susceptibility. The very high and high susceptibility zones account for 15.11% area coverage. The results are useful to get an impression of the sustainability of the watershed in terms of landsliding and therefore may help decision makers in future planning and mitigation of landslide impacts.

Geospatial Approach on Landslide Susceptibility Zonation and Geo-design in Semi-arid Mountainous Watershed, Saudi Arabia

Landslide is a natural geological disaster, greatly affected by geological features, precipitation and anthropogenic activities. The characteristics of the Abha mountainous watershed are sedimentary soft, hard silt and clay rocks.

Satellite-Derived Land Surface Temperature and Landscape Characterization of National Capital Region (NCR), India Using Multispectral and Thermal Data

Environmental problems resulting from urbanization (e.g., global warming, air pollution, water pollution and environmental deterioration) have negatively affected the quality and comfort of urban livelihood.