Household-level disaster-induced losses and rural–urban migration: Experience from world’s one of the most disaster-affected countries

Losses due to natural disasters induce rural–urban migration throughout the world. It is also a major driver of population influx in Dhaka city, the capital of one of the most disaster-affected countries in the world, Bangladesh. While the relationship between natural disasters and migration is evident, the magnitude of household-level losses inducing rural–urban migration has not been widely discussed. This paper approaches this issue based on an empirical study. Using appropriate sampling procedure, a total of 407 households in Dhaka statistical metropolitan area were interviewed. This research finds out that 18.43% of rural–urban migrants in Dhaka city are disaster induced. A sharp drop in income immediately after the disaster is the predominant reason behind their migration. The river bank erosion-affected migrants encountered as high as 89% drop in income, whereas the flood-affected migrants experienced 70% drop. This article identifies five post-disaster components that ultimately determine migration. To conclude, the paper offers several approaches to minimize mass rural out-migration.

     

Orbital evolution dynamics of two satellites in encounter phase using multiple scales expansion

An approximate solution of the encounter problem of two small satellites describing initially elliptical orbits around a massive oblate primary is obtained. The equations of motion of the center of mass of the two masses are developed in the most general form without any restrictions on the orbital elements. The method of multiple scales which seeks a solution whose behavior depends on several time scales is used. To overcome the singularity the equations of motion are transformed to the Struble variables. An analytical second order theory of the evolution dynamics is obtained. A MATHEMATICA program is constructed. The evolution dynamics of the orbital parameters between the perturbed and the unperturbed cases are plotted. The effect of changing eccentricity and changing inclination on the orbital parameters are highlighted.     

Effect of clayey media parameters on the negative response of a coincident loop1

The aim of this work is to consider the phenomenon of negative response and its detectability in a polarizable half-space formed of Clay-water mixture which commonly exists in water aquifers and which can be used as a simple indicator of the presence of Underground water. We make use of an analytical treatment for the transient voltage induced in a coincident loop lying on a half-space as a basis for our computations. A Cole-Cole model is used to represent the Clay with appropriate parameters. As saturated Clay is characterized by high conductivity and moderate chargeability, it is hardly detectable relative to the practical noise level. However, there are optimum Clay parameters that offer a maximum negative response. It is also observed that for a very short time constant τ in the Cole-Cole model, the amplitude of the negative response decreases with the decrease of the time constant due to the fast decay of the polarization current. Finally, it is found that there is an optimum value for the loop radius which gives the largest value of the negative response and this loop radius depends on the model parameters.     

Third order uranus-neptune planetary theory

We calculate in this paper the secular and critical terms arising from the principal part of the classical planetary Hamiltonian. This is the first step to establish a third order canonical planetary theory of Uranus-Neptune through the Hori-Lie technique. We truncate our expansions at the second degree of eccentricity-inclination. Our planetary theory is expressed in terms of the canonical variables of H. Poincaré.     

Remote Sensing Inversion for Simulation of Soil Salinization Based on Hyperspectral Data and Ground Analysis in Yinchuan,China

The Pingluo area, as an experimental study area in Yinchuan, has been subjected to major environmental degradation due to soil salinization problems. Soil salinization is one of the main problems of land degradation in arid and semiarid regions. In the present study, remote sensing was integrated with mathematical modeling to evaluate soil salinization adequately. To detect soil salinization, soil water content and electrical conductivity of soil samples were analyzed. The reflectance of soil samples was measured using a spectrometer (SR-3500) with 1024 bands. Indices of soil salinity, vegetation and drought were analyzed using Landsat images over the study area. Based on Landsat images, physicochemical analysis, reflectance of sensitive bands for soil salinization and environmental indices, canopy response salinity index (CRSI), perpendicular drought index (PDI) and enhanced normalized difference vegetation index (ENDVI), a new model was established for simulation and prediction of soil salinization in the study area. Correlation analyses and multiple regression methods were used to construct an accurate model. The results showed that green, blue and near-infrared light was significantly correlated with soil salinity and that the spectral parameters improved this correlation significantly. Therefore, the model was more effective when combining spectral parameters with sensitive bands with modeling. After mathematical transformation of soil reflectance, the correlations of bands sensitive to soil salinization were 0.739 and 0.7 for electrical conductivity and water content, respectively. After transformation of vegetation reflectance, the correlation coefficient of soil salinity became 0.577. After inversion of the model based on soil hyperspectral and water content, the significance became 0.871 and 0.726, respectively, which can be used to predict soil salinity and water content. The spectral soil salinity model had a coefficient of 0.739 for soil salinity prediction. Among the salinity indices, the CRSI was selected as the most significant, with R² of 0.571, whereas the R² for PDI reached only 0.484. Among the vegetation indices, the ENDVI had the highest response to soil salinity, with R² of 0.577. After scale conversion, the correlation percentages between CRSI and measured soil salinity and between ENDVI and measured soil salinity increased to 16.2% and 8.5%, respectively. Following the correlation between PDI and soil water content, the percentage of correlation increased to 11.6%. The integration of hyperspectral remote sensing, ground methods and an inversion method for salinity is a very important and effective technique for rapid and nondestructive monitoring of soil salinization.

     

Engaging indigenous people as geo-crowdsourcing sensors for ecotourism mapping via mobile data collection: a case study of the Royal Belum State Park

ABSTRACT

Web 2.0 and the proliferation of built-in Global Positioning System (GPS) on smartphones have influenced the increase of geo-crowdsourcing activities in a number of different contexts. The aim of this paper is to evaluate the performance of indigenous people’s use of mobile collection applications that are embedded in a smartphone to facilitate ecotourism asset mapping. In order to achieve this, field usability testing was conducted where structured observational method was used to assess the performance. The findings indicate majority of them can complete the data entry tasks using mobile data collection. The performance of data entries using radio button, icons, camera and audio methods were identified as better than free text and drop-down list methods. There was a correlation between the level of education with the ability of using radio button, drop-down list and image icon as data entry methods. The paper also discusses the extent of local knowledge relating to ecotourism within the community. The findings should be useful in the understanding of the design of mobile geo-crowdsourcing tools for use within other contexts that focus on data collection by semiliterate and indigenous groups.     

Generation of a stochastic precipitation model for the tropical climate

Theoretical and Applied Climatology - A tropical country like Malaysia is characterized by intense localized precipitation with temperatures remaining relatively constant throughout the year. A...     

Hydrochemical assessment of groundwater from shallow aquifers in parts of Wadi Al Hamad,Madinah, Saudi Arabia

The present study was carried out in the Mulaylih area which forms a part of Wadi Al Hamad in the Madinah Province of Saudi Arabia. Thirty groundwater samples from agricultural farms were collected and analyzed for various physio-chemical parameters including trace elements. The area is occupied by the Quaternary alluvium deposits which form shallow unconfined aquifers. Evaporation and ion exchange are the major processes which control the major ion chemistry of the area. The extreme aridity has results in high total dissolved solid values (average of 9793.47 mg/l). Trace element concentrations are low and are mainly attributed to geogenic sources (silicate weathering). Na-Cl groundwater type is the main hydrochemical facies found in the area. The waters are found to be oversaturated with calcite/aragonite and dolomite. The average nitrate concentration was found to be 134.10 mg/l and is much higher than the WHO recommended limit of 50 mg/l in drinking water. Their high values are mainly associated with the application of N-fertilizers on the agricultural farms. The average fluoride concentration in the study was found to be 1.54 mg/l. The relation between F and Cl and Cl and Na reveals that the fluoride concentrations are mainly attributed to geogenic sources. A comparison of the groundwater quality with the Saudi drinking water standards shows that the water is unfit for drinking. The high salinity and sodicity of the groundwater make it unfit for irrigation. Principal component analysis resulted in extraction of four principal components accounting for 79.5% of the total data variability and supports the fact that the natural hydrochemical processes (evaporation and ion exchange) control the overall groundwater chemistry.     

Fitting optimum order of Markov chain models for daily rainfall occurrences in Peninsular Malaysia

The analysis of the daily rainfall occurrence behavior is becoming more important, particularly in water-related sectors. Many studies have identified a more comprehensive pattern of the daily rainfall behavior based on the Markov chain models. One of the aims in fitting the Markov chain models of various orders to the daily rainfall occurrence is to determine the optimum order. In this study, the optimum order of the Markov chain models for a 5-day sequence will be examined in each of the 18 rainfall stations in Peninsular Malaysia, which have been selected based on the availability of the data, using the Akaike’s (AIC) and Bayesian information criteria (BIC). The identification of the most appropriate order in describing the distribution of the wet (dry) spells for each of the rainfall stations is obtained using the Kolmogorov-Smirnov goodness-of-fit test. It is found that the optimum order varies according to the levels of threshold used (e.g., either 0.1 or 10.0 mm), the locations of the region and the types of monsoon seasons. At most stations, the Markov chain models of a higher order are found to be optimum for rainfall occurrence during the northeast monsoon season for both levels of threshold. However, it is generally found that regardless of the monsoon seasons, the first-order model is optimum for the northwestern and eastern regions of the peninsula when the level of thresholds of 10.0 mm is considered. The analysis indicates that the first order of the Markov chain model is found to be most appropriate for describing the distribution of wet spells, whereas the higher-order models are found to be adequate for the dry spells in most of the rainfall stations for both threshold levels and monsoon seasons.