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As the world’s largest urban area in both size and population, the rapid development of the Pearl River Delta (PRD) during past three decades has been accompanied by worsening water problems
. This paper examines the water-economy nexus of the PRD from the perspectives of both water use and water quality between 1999 and 2015, with a Logarithmic Mean Divisia Index decomposition model as well as an Environmental Kuznets Curve model, in order to assess the sustainable transition of the area. The results show that in this period, while the water dependency of economic development went down by a significant extent, the efficiency gains did not prevail over problems caused by economic scale expansion. However, at the city level, the 2008 financial crisis stimulated an economic transformation of the main economies from being scale-dominated to being efficiency-dominated. From 2009 to 2015, the sewage decreases driven by water dependency of Guangzhou, Shenzhen, and Dongguan outweighed the sewage increases driven by economic scale. While sewage discharge increased, the river water quality of the PRD kept improving. We found an inverted “U”-shaped relationship between GDP per capita and water quality of the PRD, with GDP per capita = ¥14,228.27 as the inflection point for river water quality. Once dubbed the “factory floor” of the world, the PRD has moved into a less environmentally impactful phase of development, with more expenditure on environmental protection and policy reform. However, given the huge and ever-increasing economic and population scales, ensuring a sufficient and safe water supply through industrial recycling and public education, along with even further pollution abatement, will be particularly important
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Seasonally variable thermal conductivity in active layers is one important factor that controls the thermal state of permafrost
. The common assumption is that this conductivity is considerably lower in the thawed than in the frozen state, ?t/?f??1.5?m) active layers with strong seasonal total water content changes in the regions with summer-monsoon-dominated precipitation pattern. The conductivity ratio can be further increased by typical soil architectures that may lead to a dry interlayer. The unique pattern of soil hydraulic and thermal dynamics in the active layer can be one important contributor for the rapid permafrost warming at the study site. These findings suggest that, given the increase in air temperature and precipitation, soil hydraulic properties, particularly soil architecture in those thick active layers must be properly taken into account in permafrost models
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The Tarim river basin in China is a huge inland arid basin, which is expected to be highly vulnerable to climatic changes, given that most water resources originate from the upper mountainous headwater regions
. This paper focuses on one of these headwaters: the Kaidu river subbasin. The climate change impact on the surface and ground water resources of that basin and more specifically on the hydrological extremes were studied by using both lumped and spatially distributed hydrological models, after simulation of the IPCC SRES greenhouse gas scenarios till the 2050s. The models include processes of snow and glacier melting. The climate change signals were extracted from the grid-based results of general circulation models (GCMs) and applied on the station-based, observed historical data using a perturbation approach. For precipitation, the time series perturbation involves both a wet-day frequency perturbation and a quantile perturbation to the wet-day rainfall intensities. For temperature and potential evapotranspiration, the climate change signals only involve quantile based changes. The perturbed series were input into the hydrological models and the impacts on the surface and ground water resources studied. The range of impact results (after considering 36 GCM runs) were summarized in high, mean, and low results. It was found that due to increasing precipitation in winter, snow accumulation increases in the upper mountainous areas. Due to temperature rise, snow melting rates increase and the snow melting periods are pushed forward in time. Although the qualitive impact results are highly consistent among the different GCM runs considered, the precise quantitative impact results varied significantly depending on the GCM run and the hydrological model
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