Gender-based differences in flood vulnerability among men and women in the char farming households of Bangladesh

Natural Hazards - Gender and vulnerability are important issues to examine in the context of flooding caused by climate change. Men and women around the world adapt differently to climate change...     

Flood risk perception and its determinants among rural households in two communities in Khyber Pakhtunkhwa,Pakistan

Natural Hazards - Risk perception plays a vital part in flood risk management and mitigation strategies. Therefore, this study aims at first to measure the risk perception of the vulnerable...     

Poverty and environmental nexus in rural Pakistan: a multidimensional approach

The study examines the relationship between poverty and forest cover degradation in rural areas of Pakistan. The area selected for the study District Upper Dir is a rural and relatively backward region located in northwestern Pakistan, in Khyber-Pakhtunkhwa province. The study area is undergoing severe deforestation and natural disasters in the recent past. The study consists of two stages, in first stage the traditional Geographical information system image was used to analyze the spatial–temporal situation of the surroundings. In the second stage, well-designed questionnaire was used to collect the primary information from 420 randomly selected households of research areas. A multidimensional poverty index has been used to measure the poverty profile of the population. It has been found that 55% households were below the poverty line. Almost, 95% households are using wood for cooking purposes. High dependence on natural resources causes forest cover degradation while burning off too much wood causes CO₂ emission and leads to environmental degradation. A major portion of population is living on steeply sloped areas with certain risks. It is found that frequency of flash flood is 53% and agricultural land (54%) is at high risk and often flows with flash floods. It is concluded that there is strong correlation between multidimensional poverty and forest cover degradation which leads to climate and environmental risks.

     

Felsic dykes in the Neoproterozoic Nagar Parkar Igneous Complex,SE Sindh,Pakistan: geochemistry and tectonic settings

The Nagar Parkar Igneous Complex consists of Neoproterozoic igneous and metamorphic rocks dissected by mafic, felsic, and rhyolitic dykes. The latter can be classified broadly into porphyritic felsic dykes intruding gray and pink granites at Nagar Parkar and the surrounding areas, and the orthophyric felsic dykes intruding amphibolites, deformed pink granites, and the alkaline mafic dykes in the Dhedvero area, north of Nagar Parkar. The porphyritic felsic dykes are composed of perthites, quartz, and albitic plagioclase whereas the orthopheric felsic dykes contain K-feldspar (dominant), plagioclase, and minor quartz. Geochemically, the porphyritic and orthophyric felsic dykes are subalkaline and alkaline demonstrating post-orogenic A2- and OIB-A1-type characteristic on Nb–Y–Ce and Nb–Y–3Ga ternary plots, respectively. One orthophyric felsic dyke contains normative acmite and sodium metasilicate. This study suggests two distinct tectonic regimes for the origin of the felsic dykes of the area. The porphyritic felsic dykes show similarities with the ~800–700 Ma granites of the area, the rhyolite dykes of the Mount Abu, western Rajasthan in India, and the granites of the Seychelles microcontinent. The orthophyric felsic dykes show chemical resemblance with the Tavidar volcanic suite of western Rajasthan and the Silhouette and North islands of the Seychelles microcontinent. This study confirms spatial and temporal links among the Rodinian fragments exposed in the Nagar Parkar area of Pakistan, western Rajasthan of India, and the Seychelles microcontinent.     

Forecasting scheme for swan coastal river streamflow using combined model of IOHLN and Niño4

The study aims to investigate the possible relationship between Niño 4 and Indian Ocean high longitude (IOHLN) with the Swan coastal river flow by constructing a regression model which predict streamflow patterns and which enables to obtain long time lead to forecasting, in a period when there was not much rainfall. Many streamflow forecast models use rainfall and runoff relationship, which is dependent on basin response time and hence cannot provide large forecasting lead time. For water resource management, this lead time of predictability is not capable for a long period of drying trend. Significant findings of this study suggest that Niño 4 and Indian Ocean high pressure longitude (IOHLN) can be used for forecasting of flow in Swan river. In this study not only qualitative forecast of Swan coastal river is presented based on the conditional probability, but also a quantitative forecast is done by combining Niño.4 and IOHLN indices using multiple regression, which shows enhancement over other climate indicators when used alone. The Conditional probability model correctly predict 7 years category of flow out of 8 years flow.