The Ningxia Hui Autonomous Region (NX region) of Northwestern China is threatened by increased meteorological drought induced by climate change (CC) and constraints on water supply from the Yellow River. Thus, the NX region is representative of attempts to adapt to CC and variability in China’s arid regions. Field visits, a questionnaire and in situ inspections were conducted in 2012–2014 to understand people’s perception and awareness of drought and its impact, particularly with respect to adaptation strategies. We mainly focused on drought adaptation actions and planning implemented at the government level under the double pressures of drought and allocation. We described a suitable adaptation pathway for socio-economic sustainable development and discussed existing adaptation barriers. Construction of modern efficient water-saving agriculture lies at the core of drought adaptation, with socio-economic sustainable development being the ultimate goal. To achieve this, policies and institutional, engineering, technological, structural and social initiatives and measures—classified into macro adaptation strategies and specific coping measures—are implemented. Adaptation often encounters obstacles, e.g., policy issues from household contract responsibility systems, funding difficulties of low-income farmers, traditional behavioral habits and low education and literacy levels among farmers. The adaptation pathway involves the construction of modern efficient water-saving agriculture. Agricultural water savings are then transferred to developed industries, which back-feed socio-economic sustainable development in the NX region.

The implementation of China’s Beautiful Village Initiative was an extraordinary achievement and aroused extensive public attention. However, existing research mostly focuses on the construction and seldom on public attention towards the Beautiful Village Initiative. For this reason, this paper investigated the spatiotemporal characteristics of public attention based on the Baidu index using time-constrained clustering and the spatial autocorrelation test. Our results showed that the evolutionary process can be divided into three stages: very little national attention (2011–2012), injection of a strong impetus (2013–2015), and rooted in the people’s minds (2016–2020). Spatially, provincial public attention demonstrated obvious spatial differentiation and stable spatial autocorrelation, with Low–Low clusters in Northwest China and High–High Clusters in East, Central, and North China. Spatial econometric models were further utilized to quantify the effects of socioeconomic factors on public attention. The results of the SEM model proved the existence of spatial spillover effects and indicated that the urbanization rate, population density, education level, and network popularity rate all positively affected public attention. The relationship between Beautiful Village construction and public attention was uncoordinated and, in most provinces, advances in public attention were ahead of the construction level. Our findings contribute to the understanding of public attention towards the Beautiful Village Initiative, and policy suggestions we proposed would be applied to increasing public awareness and participation.

As the “Third Pole” of the Earth, the Tibetan Plateau (TP) has been warming significantly, and the instability of extreme events related to climate and weather has enhanced exceptionally in recent decades. These changes have posed increasingly severe impacts on the population over the TP. So far, however, the impacts on the population have not been assessed systematically and comprehensively from the perspective of risk. In this paper, the hazard of climate change was assessed from a fresh look, not only considering extreme changes of air temperature, precipitation, and wind speed, but also their changes in mean and fluctuation, using daily meteorological data from 1961–2015. The population exposure and vulnerability to climate change were then evaluated using demographic data and considering population scale and structure. Finally, the population risk over the TP to climate change was quantitatively assessed within the framework of the Intergovernmental Panel on Climate Change (IPCC). The results showed that the climate change hazard was mainly at medium and heavy levels, in areas accounting for 64.60% of the total. The population exposure was relatively low; the land area at slight and light levels accounted for 83.94%, but high in the eastern edge area of the TP. The population vulnerability was mostly at medium and heavy levels, and the non-agricultural population rate was the key factor affecting the population vulnerability. Generally, the overall population risk over the TP was not very high: the number of counties with heavy and very heavy risk only accounted for 24.29%, and land area was less than 5%. However, more than 40% of the population was in high-risk areas, located in the eastern edge area of the TP. Population exposure was the decisive factor of the population risk to climate change, and high population exposure might lead to high risk. These findings were potentially valuable to improve cognition of risk, develop proactive risk mitigation strategies, and ensure sustainable development.