Proper water use requires its monitoring and evaluation. An indexes system of overall water use efficiency is constructed here that covers water consumption per 10,000 yuan GDP, the coefficient of effective utilization of irrigation water, the water consumption per 10,000 yuan of industrial value added, domestic water consumption per capita of residents, and the proportion of water function zone in key rivers and lakes complying with water-quality standards and is applied to 31 provinces in China. Efficiency is first evaluated by a projection pursuit cluster model. Multidimensional efficiency data are transformed into a low-dimensional subspace, and the accelerating genetic algorithm then optimizes the projection direction, which determines the overall efficiency index. The index reveals great variety in regional water use, with Tianjin, Beijing, Hebei, and Shandong showing highest efficiency. Shanxi, Liaoning, Shanghai, Zhejiang, Henan, Shanxi, and Gansu also use water with high efficiency. Medium efficiency occurs in Inner Mongolia, Jilin, Heilongjiang, Jiangsu, Hainan, Qinghai, Ningxia, and Low efficiency is found for Anhui, Fujian, Jiangxi, Hubei, Hunan, Guangdong, Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, and Xinjiang. Tibet is the least efficient. The optimal projection direction is a* = (0.3533, 0.7014, 0.4538, 0.3315, 0.1217), and the degree of influence of agricultural irrigation efficiency, water consumption per industrial profit, water used per gross domestic product (GDP), domestic water consumption per capita of residents, and environmental water quality on the result has decreased in turn. This may aid decision making to improve overall water use efficiency across China.
The three-river headwater region (TRHR) supplies the Yangtze, Yellow, and Lantsang rivers, and its ecological environment is fragile, hence it is important to study the surface vegetation cover status of the TRHR to facilitate its ecological conservation. The normalized difference vegetation index (NDVI) can reflect the cover status of surface vegetation. The aims of this study are to quantify the spatial heterogeneity of the NDVI, identify the main driving factors influencing the NDVI, and explore the interaction between these factors. To this end, we used the global inventory modeling and mapping studies (GIMMS)-NDVI data from the TRHR from 1982 to 2015 and included eight natural factors (namely slope, aspect, elevation, soil type, vegetation type, landform type, annual mean temperature, and annual precipitation) and three anthropogenic factors (gross domestic product (GDP), population density, and land use type), which we subjected to linear regression analysis, the Mann-Kendall statistical test, and moving t-test to analyze the spatial and temporal variability of the NDVI in the TRHR over 34 years, using a geographical detector model. Our results showed that the NDVI distribution of the TRHR was high in the southeast and low in the northwest. The change pattern exhibited an increasing trend in the west and north and a decreasing trend in the center and south; overall, the mean NDVI value from 1982 to 2015 has increased. Annual precipitation was the most important factor influencing the NDVI changes in the TRHR, and factors, such as annual mean temperature, vegetation type, and elevation, also explained the vegetation coverage status well. The influence of natural factors was generally stronger than that of anthropogenic factors. The NDVI factors had a synergistic effect, exhibiting mutual enhancement and nonlinear enhancement relationships. The results of this study provide insights into the ecological conservation of the TRHR and the ecological security and development of the middle and lower reaches.
The Yellow River is one of the rivers with the largest amount of sediment in the world. The amount of incoming sediment has an important impact on water resources management, sediment regulation schemes, and the construction of water conservancy projects. The Loess Plateau is the main source of sediment in the Yellow River Basin. Floods caused by extreme precipitation are the primary driving forces of soil erosion in the Loess Plateau. In this study, we constructed the extreme precipitation scenarios based on historical extreme precipitation records in the main sediment-yielding area in the middle reaches of the Yellow River. The amount of sediment yield under current land surface conditions was estimated according to the relationship between extreme precipitation and sediment yield observations in the historical period. The results showed that the extreme rainfall scenario of the study area reaches to 159.9 mm, corresponding to a recurrence period of 460 years. The corresponding annual sediment yield under the current land surface condition was range from 0.821 billion tons to 1.899 billion tons, and the median annual sediment yield is 1.355 billion tons, of which more than 91.9% of sediment yields come from the Hekouzhen to Longmen sectionand the Jinghe River basin. Therefore, even though the vegetation of the Loess Plateau has been greatly improved, and a large number of terraces and check dams have been built, the flood control and key project operation of the Yellow River still need to be prepared to deal with the large amount of sediment transport.
A water rights trading scheme in China is currently in its initial stage of development, but is without a complete pricing mechanism. This paper proposes a pricing model for transfers of water rights from agriculture to industry in water-deficient areas of China. Both the cost price and the earnings price are considered and incorporated into the model. The cost price includes construction costs, operation and maintenance costs, renewal and reconstruction costs, and economic compensation for ecological damage. The earnings price is calculated according to a reasonable return coefficient and the difference in economic value of the water resources to the buyer and seller. The value of water resources was estimated based on emergy theory in accordance with the principle of mutual benefits equilibrium. This pricing model is then applied to the transfer of surplus water rights arising from agricultural water conservation schemes to industrial uses in the Southbank Ordos Irrigation Zone of the Inner Mongolia Autonomous Region. The results indicate that this pricing model could provide technical support to the scientific and reasonable pricing of water rights transactions in water-deficient areas and that it could play an active role in promoting the healthy development of future water markets.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.