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Drought is a major factor affecting the sustainable development of society and the economy. Research on drought assessment is of great significance for formulating drought emergency policies and drought risk early warning and enhancing the ability to withstand drought risks. Taking the Yellow River Basin as the object, this paper utilizes data fusion, copula function, entropy theory, and deep learning, fuses the features of meteorological drought and hydrological drought into a drought assessment index, and establishes a long short-term memory (LSTM) network for drought assessment, based on deep learning theory. The results show that (1) after extracting the features of meteorological drought and hydrological drought, the drought convergence index (DCI) built on the fused features by copula function can accurately reflect the start and duration of the drought; (2) the drought assessment indices were effectively screened by judging the causality of the drought system, using the transfer entropy; (3) drawing on the idea of deep learning, LSTM for drought assessment, which was established on DCI and the drought assessment factors, can accurately assess the drought risks of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Sanjiangyuan region is located in the hinterland of Qinghai-Tibet plateau, covering an area of 30.25 square kilometers, with the total population of 556000 people, including Tibetans, constituting more than 90%. Since it is the source of the Yangtze River, Yellow River, Lancang River catchment area, biodiversity concentration, and a beautiful environment, known as the "Chinese water tower," occupy an irreplaceable strategic position in national development. Although Sanjiangyuan region is blessed with unique natural landscape and rich tourism resources, its ecological environment has been seriously deteriorated due to long-term man-made destruction, backward economic development, and increasing poverty, which have seriously affected and restricted the survival and development of local ethnic groups. Since the 18th National Congress of the Communist Party of China, General Secretary Xi Jinping has repeatedly emphasized that "Lucid waters and lush mountains are invaluable assets." China advocates harmonious coexistence between humans and nature and sticks to the path of green and sustainable development. At the 19th National Congress of the Communist Party of China, the rural revitalization strategy was clearly proposed, which includes not only industrial revitalization but also ecological revitalization. In this paper, the area belonging to Sanjiangyuan National Park is taken as the main research object. By constructing economic, tourism, and ecological environment (TEE) evaluation indexes, the coupling degree and coupling coordination degree models are established, and the data from 2000 to 2019 are measured. The relationship of the three indicators is analyzed, and corresponding proposals for its development are put forward, such as implementing ecological compensation mechanism to improve the level of ecosystem management; blending into ethnic cultural elements to create a unique tourist resort; paying attention to economic development quality, building energy conservation and emissions reduction green engine; Doing a good job in the top-level design of ecological economy, and promoting the coordinated development of various indicators, etc. We will focus on quality control of economic development and build green engines for energy conservation and emission reduction. We will do a good job in top-level ecological and economic design and promote coordinated development of various indicators. [ABSTRACT FROM AUTHOR]

The traditional development model of high consumption and low efficiency approaches the threshold of resource and environmental carrying capacity, bringing a series of severe social and ecological environmental problems, and it is urgent to realize green development transformation. Based on a multidimensional perspective, this paper constructed a comprehensive evaluation system for urban green development along the Yellow River Basin (YRB). Entropy method, exploratory spatial data analysis (ESDA) model, and trend analysis were used to measure and characterize the spatiotemporal evolution of urban green development index (UGDI) along the YRB in 2008, 2013, and 2018, and geographically weighted regression (GWR) model was used to explore the influencing factors of urban green development. The results are as follows: (1) the UGDI along the YRB showed a slow upward trend, but the absolute value was relatively low, mainly concentrated in 0.2699–0.3799. (2) The UGDI had obvious regional differences, and cities such as Baotou and Zibo showed a "high-high" agglomeration, while most cities in the midstream showed a "low-low" agglomeration, and in terms of space, they were "high in the east and west, low in the middle" and "high in the north and low in the south." (3) Influencing factors had different degrees of impact on the UGDI. Economic, industrial, urbanization, and green infrastructure factors played a positive role in promoting the urban green development, while the relationship between governance, technological factors, and green development varies from city to city. [ABSTRACT FROM AUTHOR]

The Yellow River Basin (YRB) is an important ecological defense and economic zone in China and occupies a very important position in the economy and society of China. Premise condition of ecological protection and development of high quality in YRB is the greening of the industry. Based on the data of 35 cities in YRB in 2012, 2015, and 2018, this paper constructs an evaluation index system for the industrial green development (IGD) and explores spatial differentiation characteristics of the IGD by the exploratory spatial data analysis (ESDA) method. On this basis, this paper uses the geographical weighted regression (GWR) model to analyze the influencing factors. The results indicate the following: (1) in general, IGD in YRB shows an upward trend. (2) The Global Moran's I index of IGD shows a small increase; the distribution of local spatial correlation is basically unchanged. (3) There are obvious regional differences in the influencing factors of IGD. The degree of influence of each factor on IGD is openness > industrial upgrading index > urbanization rate > science and technology expenditures > reduction rate of energy consumption. [ABSTRACT FROM AUTHOR]

Meteorological drought poses a frequent challenge in the Nile River basin, yet its comprehensive evaluation across the basin has been hindered by insufficient recorded rainfall data. Common indices like the standard precipitation index, coefficients of variation, and precipitation concentration index serve as pivotal tools in gauging drought severity. This research aimed to assess the meteorological drought status in the Nile River basin by using the Power Data Access Viewer product rainfall data. Bias correction procedures were implemented to refine the monthly rainfall data for Bahirdar, Markos, Nekemt, and Muger stations, resulting in notable improvements in the coefficient of determination ( R 2 ) that were increased from 0.74 to 0.93, 0.72 to 0.89, 0.71 to 0.96, and 0.69 to 0.84, respectively. The average spatial distribution of drought in the Nile basin was classified as extremely wet (3.81%), severely wet (9.01%), moderately wet (7.36%), near normal (9.97%), moderately drought (21.20%), severely drought (17.11%), and extremely drought (31.54%). Approximately 10.33% of the Nile River basin was situated in regions characterized by high rainfall variability, while around 21.17% was located in areas with a notably irregular precipitation concentration index. Overall, this study sheds light on the prevailing meteorological drought patterns in the Nile River basin, emphasizing the significance of understanding and managing these phenomena for the sustainable development of the region. [ABSTRACT FROM AUTHOR]

China's economic development has shifted from a high-speed growth stage to a high-quality development stage, which promotes the sustainable economic development of the Yangtze River (YR) and also improves the response capacity of the YR basin's resilience system to floods. Flood resilience (FR) is not only just the achievement of high-quality economic development (HQED) but also the key to mitigating flood damage (FD). Therefore, based on panel data from 2000 to 2019 from provincial administrative regions (PARs) in the Yangtze River basin (YRb), the entropy weight method and the quantitative regression analysis method were used to empirically investigate the impact of HQED and FR on FD in the YRb. The empirical analysis results show the following. (i) HQED has an inverted U-shaped effect on FD in the YRb, meaning that HQED will reach a certain point and reduce flood losses. (ii) The HQED model, which has been pushed forward, will significantly improve the level of FR. Various mediating effect test methods revealed that FR has a significant negative mediating effect on the process of HQED to mitigate FD. Taken together, this reveals the importance of insisting on implementing an HQED model to mitigate FD in the YRb, gradually deriving an FR that is adapted to floods and has a high self-organizing and self-restoring capacity through high-quality development. [ABSTRACT FROM AUTHOR]