The strategy of “Basing city, land, population and production on water resources”, clarifying the water uses of each province and the influencing factors are crucial to the conservation and intensive use of water resources for the Yellow River basin. In this study, physical water use, the production-based water footprint, and the consumption-based water footprint of nine provinces in the Yellow River Basin from 2007 to 2017 are measured. Then, the key influencing factors of three kinds of water use are analyzed by the random forest model. The results show that (1) the three kinds of water use in the Yellow River basin all showed a trend of first increasing and then decreasing. Physical water use and the production-based water footprint present the geographical differentiation in the declining order from the upper reach to the lower reach, and then the middle reach, while the order for the consumption-based water footprint is the lower reach, the upper reach, and the middle reach. (2) Agriculture, forestry, animal husbandry, fisheries, electricity and hot water production, supply, and chemicals are the dominant sectors of physical water use. Agriculture, forestry, animal husbandry, fisheries, food processing, tobacco, and construction are the key sectors for production-based and consumption-based water footprints. (3) The results of the random forest model show the influencing factors and their interactions of three kinds of water use in the Yellow River basin present obvious sectoral differences. The key influencing factors exhibit a linear or nonlinear response to water use in the three perspectives. The influencing factors of water use are also differentiated among the three perspectives.

Controling river water pollution is one of the complex ecoenvironmental challenges facing China’s development today. The river chief information-sharing system (RCISS) in China is an institutional innovation carried out by the government to promote collaborative water governance in the era of big data. In order to explore the mechanism of the RCISS in China, this paper analyzed this system by establishing a theoretical analysis framework from the perspective of government data governance. Using this framework, this paper discussed the mechanism, institutional context and driving forces of the current river chief information-sharing system. Provincial-level practices of the RCISS were then analyzed in terms of information content, information transmission paths, intelligent platform and practice achievements, and finally the advantages and problems of the RCISS were summarized. The conclusions were drawn as follows: the river chief information-sharing system has huge advantages regarding the coordinated management of rivers, but there are problems regarding the imbalanced sharing of power among subjects and also disputes in terms of information security, fairness, authenticity and legality. This study provides insights into the operation of the RCISS and serves as a reference for other countries seeking a suitable solution to manage water environments.

China has made significant progress in solving absolute poverty and has now entered a phase dedicated to addressing multidimensional relative poverty. Tackling multidimensional relative poverty is essential to facilitating social equity and achieving sustainable development. In this study, a Multidimensional Relative Poverty Index (MRPI) including both subjective and objective indicators was developed across three dimensions: economic, social, and environmental. The Alkire-Foster (AF) method was applied to assess the status of multidimensional relative poverty in Xinjiang using data from eight counties and cities. The results show that the multidimensional relative poverty incidence in Xinjiang is 5.73% (k = 15), with few households experiencing extreme multidimensional relative poverty. The environmental dimension is the largest contributor to MRPI (k = 10), accounting for 40.97%, while the economic dimension contributes the least at 20.83%. There are significant differences between objective and subjective indicator scores. In the economic and environmental dimensions, most objective indicators contribute significantly more than subjective ones. Conversely, in the social dimension, subjective indicators play a more substantial role. Therefore, future configurations of the MRPI should reasonably determine the indicators for the economic, social, and environmental dimensions while enhancing the incorporation of subjective indicators.