How to measure and quantitatively assess hydrological drought (HD) in the inland river basins of Northwest China is a difficult problem because of the complicated geographical environment and climatic processes. To address this problem, we conducted a comprehensive approach and selected the Aksu River Basin (ARB) as a typical inland river basin to quantitatively assess the hydrological drought based on the observed data and reanalysis data during the period of 1980–2010. We used two mutual complementing indicators, i.e., the standardized runoff index (SRI) and standardized terrestrial water storage index (SWSI), to quantitatively measure the spatio-temporal pattern of HD, where the SRI calculated from the observed runoff data indicate the time trend of HD of the whole basin, while SWSI extracted from the reanalysis data indicate the spatial pattern of HD. We also used the auto-regressive distribution lag model (ARDL) to show the autocorrelation of HD and its dependence on precipitation, potential evapotranspiration (PET), and soil moisture. The main conclusions are as follows: (a) the western and eastern regions of the ARB were prone to drought, whereas the frequency of drought in the middle of the ARB is relatively lower; (b) HD presents significant autocorrelation with two months’ lag, and soil moisture is correlated with SWSI with two months’ lag, whereas PET and precipitation are correlated with SWSI with 1 month’ lag; (c) the thresholds of HD for annual PET, annual precipitation, and annual average soil moisture are greater than 844.05 mm, less than 134.52 mm, and less than 411.07 kg/m², respectively. A drought early warning system that is based on the thresholds was designed.

Complex temperature processes are the coupling results of natural and human processes, but few studies focused on the interactive effects between natural and human systems. Based on the dataset for temperature during the period of 1980–2012, we analyzed the complexity of temperature by using the Correlation Dimension (CD) method. Then, we used the Geogdetector method to examine the effects of factors and their interactions on the temperature process in the Yangtze River Delta (YRD). The main conclusions are as follows: (1) the temperature rose 1.53 °C; and, among the dense areas of population and urban, the temperature rose the fastest. (2) The temperature process was more complicated in the sparse areas of population and urban than in the dense areas of population and urban. (3) The complexity of temperature dynamics increased along with the increase of temporal scale. To describe the temperature dynamic, at least two independent variables were needed at a daily scale, but at least three independent variables were needed at seasonal and annual scales. (4) Each driving factor did not work alone, but interacted with each other and had an enhanced effect on temperature. In addition, the interaction between economic activity and urban density had the largest influence on temperature.

The Plum Rains process is a complex process, and its spatiotemporal variations and influencing factors on different time scales still need further study. Based on a dataset on the Plum Rains in the Yangtze River Delta, from 33 meteorological stations during the period of 1960 to 2012, we investigated the spatiotemporal variations of Plum Rains and their relation with the East Asian Summer Monsoon (EASM), the El Niño-Southern Oscillation (ENSO), and the Pacific Decadal Oscillation (PDO) using an integrated approach that combines ensemble empirical mode decomposition (EEMD), empirical orthogonal function (EOF), and correlation analysis. The main conclusions were as follows: (1) the plum rainfall (i.e., the rainfall during the period of Plum Rains) showed a trend of increasing first and then decreasing, and it had a three-year and six-year cycle on the inter-annual scale and a 13-year and 33-year cycle on the inter-decadal scale. The effect of the onset and termination of Plum Rains and the daily intensity of plum rainfall on plum rainfall on the inter-annual scale was greater than the inter-decadal scale, (2) the EOF analysis of plum rainfall revealed a dominant basin-wide in-phase pattern (EOF1) and a north-south out-of-phase pattern (EOF2), and (3) ENSO and EASM were the main influencing factors in the three-year and six-year periods, respectively.

Rural entrepreneurship is an important means to solve the problem of “rural decline” and is also the focus of the “rural revitalization” strategy. The rural entrepreneurship ecosystem directly affects entrepreneurial performance. Based on the configurational perspective, using the fuzzy-set qualitative comparative analysis (fsQCA) method, taking 85 typical rural innovation and entrepreneurship demonstration counties in China as research samples, this study explores the impact path of the rural entrepreneurship ecosystem composed of multiple factors on entrepreneurial performance and the complex causal mechanisms behind it. The results show that market size, human capital, financial capital, infrastructure (both hardware and software), and government scale cannot individually constitute the necessary conditions for high or non-high rural entrepreneurial performance; there exist two pathways driving high entrepreneurial performance in rural areas: a market-driven financing-and-intelligence integration pathway and a government-supported infrastructure-assisted pathway. Under certain conditions, there is a substitution relationship between rural entrepreneurial market allocation and government intervention; there are two paths driving non-high rural entrepreneurial performance, which are summarized into market–financing suppression and market–government suppression according to the core driving factors. By systematically analyzing the impact of the rural entrepreneurial ecosystem on entrepreneurial performance, and explaining the intrinsic logic and path of high and non-high entrepreneurial performance based on the configurational perspective, this paper provides a decision-making reference for further enhancing the entrepreneurial performance in rural China and realizing rural revitalization.

In this study, we explore the evolution and formation mechanism of innovation ecosystem niche fitness from three perspectives: theoretical analysis, model construction, and empirical testing. Based on the niche theory, a theoretical framework for the innovation ecosystem is constructed. Spatiotemporal analysis and qualitative comparison methods are employed to estimate the innovation niche fitness of nine provinces located in the Yellow River Basin, and their spatiotemporal characteristics and differences in terms of formation mechanism differences are then explored. The results show that: (1) temporally, from 2000 to 2017, the innovation niche fitness in the Yellow River Basin experienced minor fluctuations. However, since 2017, there has been a considerable increase. Spatially, the midstream and downstream regions, particularly in the provinces of Shandong, Henan, and Sichuan, have a higher innovation fitness. Conversely, the upstream regions of Qinghai, Ningxia, Gansu, and Inner Mongolia display a lower fitness because of the lack of advantages in innovation elements. (2) The innovation niche fitness is heavily influenced by several factors, including the number of industrial enterprises above designated size, R&D personnel, higher education institutions, scientific research institutions, expenditure for technical renovation, sales revenue of new products, total expenditure on R&D, and the total retail sales of consumer goods. (3) Four mechanisms explain high innovation niche fitness, each of which corresponds to different regions. The formation mechanisms of low innovation niche fitness can be categorized into two paths, which have an asymmetric relationship with the formation mechanisms of high innovation niche fitness. Therefore, provinces and regions should focus on these advantages to enhance the innovation niche fitness. Our research will serve as a theoretical reference to enhance the overall innovation capacity of the Yellow River Basin in the future.

低空经济作为发展新质生产力的重要载体，已成为推动中国文旅产业数字化转型和空间拓展的重要动能。论文以面板固定效应模型、机制检验模型与空间杜宾模型为主要方法，以2010—2023年中国30个省份(西藏和港澳台地区数据暂缺)面板数据为分析依据，在系统构建低空经济和文旅产业多维评价体系的基础上，以消费扩容提质与绿色技术创新为双重视角，检验了低空经济对文旅产业的赋能效应、作用机制及空间溢出特征。结果表明：① 低空经济与文旅产业在中国分别呈现“双阶段跃升”与“持续性优化”的差异性上升态势。空间上均表现出“东南高—西北低”的梯度分布格局，二者的正向空间关联性正日益增强。② 低空经济对文旅产业发展具有显著直接赋能效应，在经过多种稳健性检验后结论依然成立；进一步，低空经济赋能效应在不同地理区位、通信水平以及人口密度地区存在异质性。③ 机制检验表明，低空经济通过消费扩容提质与绿色技术创新两条传导路径推动文旅产业发展，回归系数分别为0.347和0.955，均通过了显著性检验。④ 低空经济对文旅产业发展存在空间溢出效应，溢出强度呈先升后降的“倒U”型轨迹，超出300 km阈值后随地理距离延伸而逐步减弱。论文通过构建“消费扩容提质+绿色技术创新”的双重传导机制框架，揭示低空经济赋能文旅产业的内在逻辑，同时为推动中国低空经济与文旅产业的深度融合提供了理论依据和决策参考。