Urban flood vulnerability assessment in a densely urbanized city using multi-factor analysis and machine learning algorithms

Theoretical and Applied Climatology - Flood is considered as the most devastating natural hazards that cause the death of many lives worldwide. The present study aimed to predict flood...     

Spatiotemporal trends of temperature extremes in Bangladesh under changing climate using multi-statistical techniques

Theoretical and Applied Climatology - The rise in the frequency and magnitude of extreme temperature phenomena across the globe has led to the recurrent incidence of global climate hazards, which...     

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

Landslides 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.     

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.     

Perceived and actual risks of drought: household and expert views from the lower Teesta River Basin of northern Bangladesh

Natural Hazards - Disaster risk perception and risk appraisal are essential in formulating an appropriate disaster risk reduction policy. This study examines the actual vs perceived drought risks...     

Nexus between vulnerability and adaptive capacity of drought-prone rural households in northern Bangladesh

Natural Hazards - Bangladesh is one of the world’s most climate-vulnerable countries. The appraisal of household vulnerability and capacity to adapt under climate change is therefore crucial...     

Extent of farm mechanization and technical efficiency of rice production in some selected areas of Bangladesh

GeoJournal - The research has been conducted to explore the extent of adopting mechanization at farm level and its impact on rice producers’ technical efficiency. Primary data and information...     

Food security and dietary diversity of tea workers of two tea gardens in greater Sylhet district of Bangladesh

The study analyzed the food security and dietary diversity of tea workers in Lakkatura Tea Garden and Ootterbhag Tea garden in greater Sylhet district of Bangladesh. A total of 200 respondents (100 from each tea estate) were interviewed to evaluate the food security and dietary diversity. The study found that average daily per capita calorie intake by tea workers was 2095.96 kcal. In addition, around 85.30% of the total calorie intake was received from the rice consumption. Average per capita daily intake of rice was estimated at 538.51 gm which is higher than the national average. It was also observed that 71.7 and 65.0% households were food secure in Lakkatura and Ootterbhag Tea garden, respectively. In Lakkatura Tea Garden, 61.67% tea workers have medium dietary diversity and in Ootterbhag Tea Estate 49.47% tea workers have low dietary diversity. Using the logit model analysis, this study provides food consumption patterns of tea workers and determine the factors responsible for food security. Household size, farm income and daily calorie intake were found having significant influence on households’ food security. For improving socioeconomic conditions of tea workers, educational institution should be set up to improve their educational status and government should give loans for them at a low interest rate and create alternative job opportunity in off season.

     

Simulating and predicting river discharge time series using a wavelet‐neural network hybrid modelling approach

Accurate simulation and prediction of the dynamic behaviour of a river discharge over any time interval is essential for good watershed management. It is difficult to capture the high‐frequency characteristics of a river discharge using traditional time series linear and nonlinear model approaches. Therefore, this study developed a wavelet‐neural network (WNN) hybrid modelling approach for the predication of river discharge using monthly time series data. A discrete wavelet multiresolution method was employed to decompose the time series data of river discharge into sub‐series with low (approximation) and high (details) frequency, and these sub‐series were then used as input data for the artificial neural network (ANN). WNN models with different wavelet decomposition levels were employed to predict river discharge 48 months ahead of time. Comparison of results from the WNN models with those of the ANN models alone indicated that WNN models performed a more accurate prediction. Copyright © 2011 John Wiley & Sons, Ltd.     

Impact of irrigation in Barind Area,NW Bangladesh — An evaluation based on the meteorological parameters and fluctuation trend in groundwater table

The Barind Integrated Area Development Project (BIADP), NW Bangladesh launched in late eighties of last century boosted cropping intensity from 117% in pre-BIADP to about 200% at present. Increasing trend of rainfall for the period 1980–2006 in the southern portion had a positive impact on BIADP, but in the northeastern part, reverse trend is indicated. The groundwater outflow from the central part following the surface gradient is indicative of effluent drainage characteristics. Although rainfall has increased in the southern part, there has been progressive decline in groundwater level due to increase in irrigation demand. In the northern part there has been decline in groundwater level due to less resource potential. The PET, ET_crops and net irrigation requirement generally has decreased from pre- to post-Project implementation stages and rainwater has been the supplementary irrigation resource and thus dependency on groundwater has been reduced with exception in northwestern part. While the southern part is marching towards humid condition, north is creeping towards semi-aridity. Proper groundwater resource management with ecological balance is warranted for the sustainability of BIADP.