Location-allocation modeling for emergency evacuation planning with GIS and remote sensing: A case study of Northeast Bangladesh

This work developed models to identify optimal spatial distribution of emergency evacuation centers(EECs) such as schools, colleges, hospitals, and fire stations to improve flood emergency planning in the Sylhet region of northeastern Bangladesh.The use of location-allocation models(LAMs) for evacuation in regard to flood victims is essential to minimize disaster risk.In the first step, flood susceptibility maps were developed using machine learning models(MLMs), including: Levenberg–Marquardt back propagation(LM-BP) neural network and decision trees(DT) and multi-criteria decision making(MCDM) method.Performance of the MLMs and MCDM techniques were assessed considering the area under the receiver operating characteristic(AUROC) curve.Mathematical approaches in a geographic information system(GIS) for four well-known LAM problems affecting emergency rescue time are proposed: maximal covering location problem(MCLP), the maximize attendance(MA), p-median problem(PMP), and the location set covering problem(LSCP).The results showed that existing EECs were not optimally distributed, and that some areas were not adequately served by EECs(i.e., not all demand points could be reached within a 60-min travel time).We concluded that the proposed models can be used to improve planning of the distribution of EECs, and that application of the models could contribute to reducing human casualties, property losses, and improve emergency operation.     

Climate finance governance in hazard prone riverine islands in Bangladesh: pathway for promoting climate resilience

Bangladesh is one of the topmost climate vulnerable countries in the world where the riverine island (char) dwellers are the most victims of climate change. Climate finance is perceived as the key instruments to address the issues related to climate change impacts and improve the livelihood resilience of the rural people. This article examines the role of climate finance governance at the vulnerable hazard-prone chars in Bangladesh. Climate finance adaptation governance has been assessed through measuring the climate service intervention, behavioral changes and impacts at the local level. The study reveals that the mechanism of climate finance in Bangladesh is good enough, but implementation is not satisfactory. It also observed that there is a lack of participatory governance for disaster management, and there is no direct contribution of climate finance governance in the village level which causes to fail the existing implementation strategy. The study suggests that a riverine island-based long-term development program should be implemented through ensuring effective monitoring system so that climate finance governance can contribute a lot and improve the food security and livelihood resilience of char dwellers.

     

An Anisotropic Model for Granular Material Based on Experiments

Soil is a heterogeneous material and most natural soil deposits show a definite stratification. The mechanical behaviour of such material is generally different in different directions, especially in the direction parallel and perpendicular to the stratification. A series of isotropic compression tests were carried out to study the behavior of granular material produced under controlled stratification in the laboratory. These tests were conducted both on cylindrical and square prismatic tri-axial specimens. It was observed that for hydrostatic loading, the strain response was different in different directions, especially in directions parallel and perpendicular to the direction of soil deposition. A definite trend of anisotropy was observed in the deformation pattern. The observed anisotropy is modeled in this paper by treating soil-dilatancy as a variable quantity. The equation of the plastic potential surface of the model which obeys a non-associated flow rule, is assumed to be dependent on three main variables confining pressure (\(\sigma_{3}\)), void ratio (e) and the angle of bedding plane orientation (δ) during deposition. The angle of bedding plane orientation (δ) was measured with respect to the direction of the major principal stress. The model has a cap yield surface in the isotropic stress direction, which is supplemented by a shear hardening Mohr–Coulomb surface in the deviator direction. This paper focuses on predicting the anisotropic strain response of stratified soil deposits subjected to isotropic compression. The proposed anisotropic model incorporates within an existing strain-hardening sand model, a modified cap yield surface and a modified plastic potential function related to the cap surface, to account for the anistropic response observed in isotropic compression tests. The two dimensional stress–strain model was extended to three dimensional Cartesian space. The strain anisotropy observed in the isotropic compression tests was predicted by the three dimensional anisotropic model proposed for granular materials.     

Analyzing the occurrence of floods and droughts in connection with climate change in Punjab province,Pakistan

Natural Hazards - Frequency and intensity of extreme weather events are immensely changing throughout the world. This study aims to give insight into the changing climatic patterns leading to...     

Macrophytes’ Performance in Floating Treatment Wetlands for the Remediation of Ciprofloxacin-Contaminated Water

The presence of trace antibiotics in domestic and industrial effluents poses a risk of toxicity to fauna and flora. The application of floating treatment wetlands (FTWs) is a low-cost and sustainable approach to remediate wastewater. In this study, the performance of different macrophytes vegetated in FTWs for the remediation of ciprofloxacin (CIP)-contaminated water is investigated. Six macrophytes, Brachia mutica, Typha domingensis, Phragmites australis, Canna indica, Cyperus laevigatus, and Leptochloa fusca, are vegetated in FTWs for the removal of CIP (50 mg L⁻¹) from water. The FTWs show the potential to remove 30–43.58 mg L⁻¹ CIP from water in 28 days. They also reduce the chemical oxygen demand (118–138 mg L⁻¹) and biochemical oxygen demand (35–45 mg L⁻¹) of water. Among the macrophytes, C. indica removes maximum (43.58 mg L⁻¹) and T. domingensis minimum (30 mg L⁻¹) CIP. Canna indica and T. domingensis exhibit the maximum and minimum increase (30% and 12% of dry biomass) in growth, respectively. This study reveals that the FTWs vegetated with different plant species exhibit varying performances in removing CIP from water. This investigation is a step forward toward sustainable bioremediation of water contaminated with antibiotics.     

Analytical model of compact star in low-mass X-ray binary with de Sitter spacetime

In this article, we suggest a Sitter model in favor of compact stars in low-mass X-ray binaries.Here, we have considered the presence of a cosmological constant(on a small scale) to investigate the stellar structure. We conclude that this approach is very suitable for the familiar physical model of compact stars in low-mass X-ray binaries. We calculate the probable radius, compactness(u) and surface redshift(Z_s) of six compact stars in low-mass X-ray binaries, namely Cyg X-2, V395 Carinae/2 S 0921–630, XTE J2123–058,X1822–371(V691 CrA), 4 U 1820–30 and GR Mus(XB 1254–690). We also offer a possible equation of state(EOS) for the stellar objects.     

Inorganic pollutants in the Padma River, Bangladesh

The water and bed-sediment pollution status of the Padma River was determined by analysis of representative samples for selected metals and ions. Water and bed-sediment samples were collected at a T-dam, Rajshahi, Bangladesh, for 7 months. Water and silt-metal content analysis was performed using atomic absorption spectrophotometry or other analytical methods. The data showed the variation of the metal ion-levels in water as follows: Ca 17.11–48.37 ppm, Na 17.51–20.09 ppm, K 1.00–3.60 ppm, Cr 2.80–7.00 ppm, and SO₄ 4.17–5.48 ppm; in bed sediment, the levels were Cr 35–1050 ppm and Pb 12–48 ppm. The occurrence of Na, K and Ca was in the normal range (US EPA permissible limit), but the levels of Cr in water were much higher than the permissible limit. The SO₄ ion content was well below the pollution level. The concentration of Pb in the bed sediment was within the permissible limit for the standard International Atomic Energy Agency (IAEA) Soil-5a, but the concentration of Cr in the bed sediment was significantly higher than the permissible limit for the standard IAEA Soil-5a. Thus the Padma river water was polluted with Cr. The occurrence of some ions showed a monthly variation. Received: 19 August 1999 · Accepted: 12 October 1999     

Cohesive strength and seismogenic stress pattern along the active basement faults of the Precordillera-Sierras Pampeanas ranges, western Argentina: An experimental analysis by means of numerical model

A two-dimensional finite element method （FEM） model that incorporates faults, elastic rock physical properties, topographical load due to gravity and far-field plate velocity boundary conditions was used to recognize the seismogenic stress state along the fold-and-thrust belt of the Precordillera-Sierras Pampeanas ranges of western Argentina. A plane strain model with nine experiments was presented here to examine the fault strength with two major rock phyical properties： cohesion and angle of internal friction. Mohr-Coulomb failure criterion with bulk rock properties were applied to analyse faults. The stress field at any point of the model was assumed to be comprised of gravitational and tectonic components. The analysis was focused to recognize the seismogenic shear strain concentrated in the internal-cristaline domain of the orogene shown by the modeling. Modeling results are presented in terms of four parameters, i. e., （i） distributions, orientations, and magnitudes of principal stresses （σ1 and σ3）, （ii） displacement vector1 （iii） strain distribution, and （iv） maximum shear stress （τmax） contour line within the model. The simulation results show that the compressive stress is distributed in and around the fault systems. The overall orientation of of σ1 is in horizontal directions, although reorientations do occur within some stress weaker parts, especially subsequent to the faults. A large-scale shear stress is accumulating along the active faults of Tapias-Villicum Fault （TVF）, Salinas-Berros Fault （SBF）, Ampacama-Niquizanga Fault （ANF） and Las Charas Fault （CF）, which could act as local stress and strain modulators to localize the earthquakesoccurrence.     

Adsorption of cadmium ion using a new composite cation-exchanger polyaniline Sn(IV) silicate: kinetics, thermodynamic and isotherm studies

A new organic–inorganic composite cation exchanger polyaniline Sn(IV) silicate has been synthesized. The physicochemical properties of this ion exchanger were determined using different analytical techniques including fourier transform infrared spectroscopy, simultaneous thermogravimetry–differential thermogravimetry analyses, X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray spectroscopy and elemental analysis studies. Ion exchange capacity and effect of heating temperature on ion exchange capacity were also carried out on this ion exchange material. Adsorption properties for different metal ions have been investigated and the results revealed that polyaniline Sn(IV) silicate had the highest adsorption capacity for Cd²⁺ ion. It’s selectivity was tested by achieving some important binary separations. Dependence of adsorption on contact time, temperature, pH of the solution and exchanger dose had been studied to achieve the optimum conditions. Adsorption kinetic study showed that the adsorption process followed the first order kinetics. Adsorption data were fitted to linearly transformed Langmuir isotherm with R ² (correlation coefficient) >0.99. The maximum removal of Cd²⁺ was found at pH 9. The adsorption was fast and the equilibrium established within 40 min. Thermodynamic parameters viz- entropy change, enthalpy change and Gibb’s free energy change were also calculated.     

GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms

Hazards and disasters have always negative impacts on the way of life.Landslide is an overwhelming natural as well as man-made disaster that causes loss of natural resources and human properties throughout theworld.The present study aimed to assess and compare the prediction efficiency of different models in landslide susceptibility in the Kysuca river basin,Slovakia.In this regard,the fuzzy decision-making trial and evaluation laboratory combining with the analytic network process(FDEMATEL-ANP),Na?ve Bayes(NB)classifier,and random forest(RF)classifier were considered.Initially,a landslide inventory map was produced with 2000 landslide and nonlandslide points by randomly dividedwith a ratio of 70%:30%for training and testing,respectively.The geospatial database for assessing the landslide susceptibility was generated with the help of 16 landslide conditioning factors by allowing for topographical,hydrological,lithological,and land cover factors.The ReliefF methodwas considered for determining the significance of selected conditioning factors and inclusion in the model building.Consequently,the landslide susceptibility maps(LSMs)were generated using the FDEMATEL-ANP,Na?ve Bayes(NB)classifier,and random forest(RF)classifier models.Finally,the area under curve(AUC)and different arithmetic evaluation were used for validating and comparing the results and models.The results revealed that random forest(RF)classifier is a promising and optimum model for landslide susceptibility in the study area with a very high value of area under curve(AUC=0.954),lower value of mean absolute error(MAE=0.1238)and root mean square error(RMSE=0.2555),and higher value of Kappa index(K=0.8435)and overall accuracy(OAC=92.2%).