Assessing the role of meteorological and hydrological droughts on the drying up of the Bakhtegan and Tashk lakes

The Bakhtegan and Tashk lakes, as the second largest lakes in Iran, have been faced with a drought since 2007. Consequently, the ecology of the region has been disrupted and the social, health and environmental problems have been appeared. The purpose of this study is to investigate the role of meteorological and hydrological droughts on the drying up of these lakes. For this purpose, temperature and precipitation data measured at 21 rain gauge stations, flow rate measured at three hydrometric stations and the area obtained from the calculation of the normalized water differential index by processing 46 Landsat satellite images. Pearson correlation coefficient was used to determine the relationship between variables and linear regression method was applied to examine the trend each variable time series. Also, to determine the effect of climatic drought and hydrology on changes in the area of lakes, standardized 12-month rainfall and runoff indices were used. A decreasing trend has been discovered in the lakes area since 2008, and most of the lakes have been dried after 2012. Despite an increasing trend in the basin temperature (0.04°C/year), no significant change in this trend was observed in 2008. Moreover, decreasing trends have been detected in precipitation and discharge of the Kor River (the most important inlet of lakes), especially since 2007. The calculated standard precipitation and runoff indices indicated occurring of meteorological and hydrological droughts in the basin since 2008. Precipitation during the drought period decreased by 47%, but the discharge of the river into the lakes decreased by more than 95%. According to the results of this study, although rising in temperature together with the meteorological and hydrological droughts have caused reducing of the lakes area, but other factors could play an important role in this hazard. To determine the role of other effective factors, considering the role of human factors (especially agricultural development and dam construction) is also suggested

Geospatial analysis of urban land use pattern analysis for haemorrhagic fever risk: a review

Human modification of the natural environment continues to create habitats in which vectors of a wide variety of human and animal pathogens (such as Plasmodium, Aedes aegypti, Arenavirus etc.) thrive if unabated with an enormous potential to negatively affect public health. Typical examples of these modifications include impoundments, dams, irrigation systems, landfills and so on that provide enabled environment for the transmission of Hemorrhagic fever such as malaria, dengue, avian flu, Lassa fever etc. Furthermore, contemporary urban dwelling pattern appears to be associated with the prevalence of Hemorrhagic diseases in recent years. These observations are not peculiar to the developing world, as urban expansion also contributes significantly to mosquito and other vectors habitats. This habitats offer breeding ground to some vector virus populations. The key to disease control is developing an understanding of the contribution of human landscape modification to vector-borne pathogen transmission and how a balance may be achieved between human development, public health, and responsible urban land use. A comprehensive review of urban land use Pattern Analysis for Hemorrhagic fever risk has been conducted in this paper. The study found that most of the available literatures dwell more on the impact of urban land use on malaria and dengue fevers; however, studies are yet to be found discussing the implications of urban land use on the risk of Ebola, Lassa and other non-mosquito borne VHFs. A relational model for investigating the influence of urban land use change pattern on the risk of Hemorrhagic fever has been proposed in this study

Geospatial approach using socio-economic and projected climate change information formodelling urban growth

Urban growth and climate change are two interwoven phenomena that are becoming global environmental issues. Using Niger Delta of Nigeria as a case study, this research investigated the historical and future patterns of urban growth using geospatialbased modelling approach. Specific objectives were to: (i) examine the climate change pattern and predict its impact on urban growth modelling; (ii) investigate the historical pattern of urban growth; (iii) embrace some selected parameters from United Nations Sustainable Development Goals (UN SDGs) and examine their impacts on future urban growth prediction; (iv) verify whether planning has controlled urban land use sprawl in the study area; and (v) propose standard operating procedure for urban sprawl in the area. A MAGICC model, developed by the Inter-Governmental Panel on Climate Change (IPCC), was used to predict future precipitation under RCP 4.5 and RCP 8.5 emission scenarios, which was utilized to evaluate the impact of climate change on the study area from 2016 to 2100. Observed precipitation records from 1972 to 2015 were analysed, and 2012 was selected as a water year, based on depth and frequency of rainfall. A relationship model derived using logistic regression from the observed precipitation and river width from Landsat imageries of 2012 was used to project the monthly river width variations over the projected climate change, considering the two emission scenarios. The areas that are prone to flooding were determined based on the projected precipitation anomalies and a suitability map was developed to accommodate the impact of climate change in the projection of future urban growth. Urban landscape changes between 1985 and 2015 were also analysed, which revealed a rapid urban growth in the region. A Cellular Automata/Markov Chain (CA-Markov) model was used to project the year 2030 land cover of the region considering two scenarios; normal projection without any constraint, and using some designed constraints (forest reserves, population and economy) based on some selected UN SDGs criteria and climate change. On validation, overall simulation accuracies of 89.25% and 91.22% were achieved based on scenarios one and two, respectively. The projection using the first scenario resulted to net loss and gains of - 7.37%, 11.84% and 50.88%, while that of second scenario produced net loss and gains of -4.72%, 7.43% and 48.37% in forest, farmland and built-up area between 2015 and 2030, respectively. The difference between the two scenarios showed that the UN SDGs have great influence on the urban growth prediction and strict adherence to the selected UN SDGs criteria can reduce tropical deforestation, and at the same time serve as resilience to climate change in the region