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© 2018 by the authors
. Poverty eradication is currently a central issue within the national economic development strategy in developing countries. Understanding the spatial changes and possible drivers of poverty from different geographical perspectives has the potential to provide a policy-relevant understanding of the trends in poverty. By district-level data, poverty incidence (PI), and a statistical analysis of the period from 2005 to 2011 in Nepal, we used the location quotient (LQ), as well as the Lorenz curve, to inspect the poverty concentration and the spatial-temporal variation of poverty in Nepal. As such, this study analyzed the change in identified typologies of poverty using an approach, which accounts for inter-regional and three identified terrain components. The PI methodological approach was applied in order to (i) compare the spatial change in poverty for Nepal during the study period from a geographical-administrative perspective and (ii) to develop Lorenze curves which show the change of poverty concentration over the study period. Within the Foster-Greer-Thorbecke (FGT) approach, PI was further used, in combination with the indices of poverty gap (PG) and squared poverty gap (SPG), in order to highlight the unidimensional poverty (UP), that is the incidence, depth, and severity of poverty between 2005 and 2011. Simultaneously, the spatial relationship between UP and economic development was assessed, leading to five specific economic modes or typologies of poverty. Our findings identified that proportional poverty appears to have grown in mountainous areas as well as more urbanized and developed regions, while the mid hill regions have steadily reduced proportions of poverty. We propose a hypothesis, for further examination, which suggests that the increase in proportional poverty in the mountain regions is as a result of the migration to the urban areas of Nepal of the relatively less poor, leaving behind a trapped poorer population. This migration to urban areas of the relatively less poor, rather counterintuitively, produced an increase in proportional poverty in the urban areas. This is due to the fact that while this population represents the wealthier mountain communities, they are still relatively poor in an urban setting
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Zhen, J.; Wang, X.; Meng, Q.; Song, J.; Liao, Y.; Xiang, B.; Guo, H.; Liu, C.; Yang, R.; Luo, L.
The accelerating impact of climate change on giant panda (Ailuropoda melanoleuca) habitats have become an international research topic
. Recently, many studies have also focused on medium-sized mountain ranges or entire giant panda habitats to predict how habitats will change as the climate warms, but few say in detail what to do or where to focus efforts. To fill this gap, this paper presents a new method to take comprehensive, fine-scale evaluations incorporating climate change, human disturbance, and current conservation networks and translate them into practical countermeasures in order to help decision-makers set priority regions for conservation. This study looked at the core area of the Sichuan Giant Panda Sanctuaries United Nations Educational, Scientific and Cultural Organisation (UNESCO)World Natural Heritage site, namely Ya'an Prefecture, as a case study. The research employs the Maximum Entropy (MaxEnt) modeling algorithm to analyze how climate change will affect the habitats by 2050 under two scenarios: only considering the influence of climate change, and thinking about the coupled influence of climate change and human disturbance together. The results showed the following: (1) only considering climate change, the overall habitat that can be used by giant pandas in this region will increase, which differs from most of the previous results showing a decrease; (2) the new suitable habitat will shift westward, northward and eastward in this region; (3) conversely, the suitable habitat will be significantly reduced (about 58.56%) and fragmentized when taking into account human disturbance factors; (4) at present, the three small nature reserves are far from each other and cannot cover the present habitat well nor protect the potentially suitable habitats. Based on the comprehensive analysis of habitat shifts and our two field investigations, we suggest two regions that can be expanded into the conservation network to contain more potentially suitable habitats in the future. Furthermore, we used a geographical information system to incorporate high-resolution remote-sensing images from the GF-1 satellite, land-cover maps, and a digital elevation model (DEM) to verify the possibility of our two suggested regions. © 2018 by the authors
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This paper summarizes the main flash flood early-warning systems of America, Europe, Japan, and Taiwan China and discusses their advantages and disadvantages
. The latest development in flash flood prevention is also presented. China’s flash flood prevention system involves three stages. Herein, the warning methods and achievements in the first two stages are introduced in detail. Based on the worldwide experience of flash flood early-warning systems, the general research idea of the third stage is proposed from the viewpoint of requirements for flash flood prevention and construction progress of the next stage in China. Real-time dynamic warning systems can be applied to the early-warning platform at four levels (central level, provincial level, municipal level, and county level) . Through this, soil moisture, peak flow, and water level can be calculated in real-time using distributed hydrological models, and then flash flood warning indexes can be computed based on defined thresholds of runoff and water level. A compound warning index (CWI) can be applied to regions where rainfall and water level are measured by simple equipment. In this manner, flash-flood-related factors such as rainfall intensity and antecedent and cumulative rainfall depths can be determined using the CWI method. The proposed methodology for the third stage could support flash flood prevention measures in the 13th 5-Year Plan for Economic and Social Development of the People’s Republic of China (2016–2020). The research achievements will serve as a guidance for flash flood monitoring and warning as well as flood warning in medium and small rivers
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Stream flow plays a crucial role in environmental, social and economic contexts
. It is of significance to investigate the causes of change in runoff for better water resources management. This study detects the variation trend of recorded runoff of the Gushan River, a tributary of the Yellow River located on the Loess Plateau with severe soil and water losing, and investigates the impacts of climate change and human activities on runoff using hydrological simulation approach. Results show that the recorded runoff at Gaoshiya station on the Gushan River has experienced a significant declining trend from 1954–2013 with an abrupt change occurring in 1973. SimHyd rainfall runoff model performs well for monthly discharge simulation with Nash–Sutcliffe coefficient of 82.6 % and relative error of 0.32 %. Runoff depth over the catchment in 1980–2013 reduced by 52.4 mm compared to the previous period, in which human activities and climate change contribute 61.5 and 38.5 % of the total runoff reduction, respectively. However, the human-induced impact tends to increase. Therefore, efforts to improve the ecology of the Loess Plateau should give sufficient attention to the impacts of human activity
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Hao, L.; Sun, G.; Liu, Y.; Wan, J.; Qin, M.; Qian, H.; Liu, C.; John, R.; Fan, P.; Chen, J.
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According to the methodology of prediction for ungauged basins (PUB) as documented elsewhere, borrowing, substituting and generating (BSG) are the main methods people used to acquire the discharge at ungauged stations
. Two of substituting (modelling and disaggregation) methods with the combination with borrowing idea are compared for simulating discharge for Upper Salween and Mekong River Basin (USMRB). It is seen that simple borrowing/disaggregating method can reach the Nash-Sutcliffe Efficiency (NSE) being 0.82. The similarity in seasonal variation pattern is an important requirement to identify if the two stations are in hydrological similarity. From the experience we get from USMRB, upstream stations with shorter geographical distance may be more in hydrological similarity than the stations in the far downstream. NSE is quite low when borrowing occurs within the low altitude downstream region. The efficiency is low when information is borrowed from stations which are not in hydrological similarity
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Summary The Tibetan Plateau (TP) is the “water tower of Asia” and strongly influences both the hydrology and climate of southern and eastern Asia
. Exploring the impact of climate change on the runoff of TP rivers is critical to improve water resources management. However, thorough studies on the runoff response to climate change are seldom conducted on large TP river systems. To complement the current body of work, this study uses two rainfall–runoff models (SIMHYD and GR4J) to simulate the monthly and annual runoff across the Yarlung Tsangpo River (YTR) basin in the southeastern TP (i.e., upstream of the Brahmaputra) under historical (1962–2002) and future (up to approximately 2030) climate conditions. The future climate series are obtained by using 20 Global Climate Models (GCMs) outputs from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) to reflect a 1 °C increase in the global average surface air temperature. The two rainfall–runoff models successfully simulate the historical runoff for the eight catchments in the YTR basins with median monthly runoff Nash–Sutcliffe Efficiencies (NSE) of 0.86 for SIMHYD and 0.83 for GR4J. The mean annual future precipitation and runoff across the region are projected to increase by most of the modeling results. The mean annual precipitation changes obtained from the 20 GCMs are −15%, 7% and 16% for the 10th percentile, median and 90th percentile of GCM outputs, respectively, and the corresponding changes in the simulated mean annual runoffs are −24%, 13% and 29% for the SIMHYD model outputs and −22%, 11% and 26% for the GR4J model outputs. The projected increase in the runoff at the median percentile mainly occurs in the middle reaches of the YTR and its two tributaries, the Lhasa River and the Nyangqu River, with a 12% increase in annual runoff that mainly occurs in the wet season from May to September. The present work is the first comprehensive study on the hydrological response to climate change covering the entire upstream area of the Brahmaputra, and the results found in this study are not only helpful for local water resource management but also for the lower reaches of the Brahmaputra
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The world's third-largest river -- stretching from the Himalayas thousands of miles to the east meeting the sea -- has been experiencing its worst drought in decades
. The drought is withering farmers' wallets, threatening a Chinese species even rarer than the panda and raising questions about a clean energy source that China hopes to bank its energy future on
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Piao, S.; Ciais, P.; Huang, Y.; Shen, Z.; Peng, S.; Li, J.; Zhou, L.; Liu, H.; Ma, Y.; Ding, Y.; Friedlingstein, P.; Liu, C.; Tan, K.; Yu, Y.; Zhang, T.; Fang, J.
Global warming or the increase of the surface and atmospheric temperatures of the Earth, is increasingly discernible in the polar, sub-polar and major land glacial areas
. The Himalayan and Tibetan Plateau Glaciers, which are the largest glaciers outside of the Polar Regions, are showing a large-scale decrease of snow cover and an extensive glacial retreat. These glaciers such as Siachen and Gangotri are a major water resource for Asia as they feed major rivers such as the Indus, Ganga and Brahmaputra. Due to scarcity of ground measuring stations, the long-term observations of atmospheric temperatures acquired from the Microwave Sounding Unit (MSU) since 1979–2008 is highly useful. The lower and middle tropospheric temperature trend based on 30 years of MSU data shows warming of the Northern Hemisphere's mid-latitude regions. The mean month-to-month warming (up to 0.048±0.026°K/year or 1.44°K over 30 years) of the mid troposphere (near surface over the high altitude Himalayas and Tibetan Plateau) is prominent and statistically significant at a 95% confidence interval. Though the mean annual warming trend over the Himalayas (0.016±0.005°K/year), and Tibetan Plateau (0.008±0.006°K/year) is positive, the month to month warming trend is higher (by 2–3 times, positive and significant) only over a period of six months (December to May). The factors responsible for the reversal of this trend from June to November are discussed here. The inequality in the magnitude of the warming trends of the troposphere between the western and eastern Himalayas and the IG (Indo-Gangetic) plains is attributed to the differences in increased aerosol loading (due to dust storms) over these regions. The monthly mean lower-tropospheric MSU-derived temperature trend over the IG plains (dust sink region; up to 0.032±0.027°K/year) and dust source regions (Sahara desert, Middle East, Arabian region, Afghanistan-Iran-Pakistan and Thar Desert regions; up to 0.068±0.033°K/year) also shows a similar pattern of month-to-month oscillation and six months of enhanced and a statistically significant warming trend. The enhanced warming trend during the winter and pre-monsoon months (December–May) may accelerate glacial melt. The unequal distribution of the warming trend over the year is discussed in this study and is partially attributed to a number of controlling factors such as sunlight duration, CO2 trends over the region (2003–2008), water vapor and aerosol distribution
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