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To understand the influence mechanism of the total water use evolution in a certain region more deeply, it is necessary to accurately identify the driving effects of the total water use evolution, and quantitatively analyze the influence of the driving effects on the total water use evolution. In this research, we studied the driving effects of the total water use evolution in China from the perspective of multi-year long time-series in the whole country for the first time. Through the logarithmic mean Divisia index (LMDI) decomposition method, we constructed an LMDI decomposition model for the regional total water use evolution, and decomposed the total water use evolution in China and its five stages from 1965 to 2019 into the water use intensity effect (WUIE), sector proportion effect (SPE), per capita total economy effect (PCTEE), and total population effect (TPE). We also considered the driving effects of the total water use evolution when the population or economic proportion changed in the six major districts in China for the first time. Based on the LMDI decomposition method, we separately added the district population proportion variable and the district economic proportion variable to contrast a logarithmic mean Disivia index-population (LMDI-P) decomposition model and a logarithmic mean Divisia index-economic (LMDI-E) decomposition model for the regional total water use evolution. Compared with the LMDI decomposition model, the district population proportion effect (DPPE) and the district economic proportion effect (DEPE) were separately added. We calculated the value and proportion of the driving effects of the total water use evolution in China and analyzed their influence mechanisms. Our findings provide better decision-making reference for water resource planning and management in China. The results show the following: (1) According to the overall situation from 1965 to 2019, the prohibitive role played by the PCTEE (total 22,263.79 × 108 m3) and the TPE (total 2945.38 × 108 m3) with respect to the total water use increasing in China offset the inhibitive role played by the WUIE (total −16,094.31 × 108 m3) and the SPE (total −5930.02 × 108 m3) with respect to the total water use increasing in China; (2) According to the overall situation from 1965 to 2019, both the DPPE and DEPE had heterogeneity in the total water use evolution in the six major districts in China. The DPPE played a prohibitive role in the three population inflow districts (Southeast China, Central South China, and Northwest China) with respect to the total water use increasing (total 291.09 × 108 m3), and an inhibitive role in the other three population outflow districts (North China, Central South China, and Southwest China) with respect to the total water use increasing (total −207.78 × 108 m3). The DEPE played a prohibitive role in the three economically developed districts (North China, Southeast China, and Central South China) with respect to the total water use increasing (total 428.26 × 108 m3), and an inhibitive role in the other three economically underdeveloped districts (Northeast China, Southwest China, and Northwest China) with respect to the total water use increasing (total −477.74 × 108 m3). [ABSTRACT FROM AUTHOR]

The increased impervious surface in an urban system is considered to have significant impacts on hydrological processes, while the impact of the imperviousness spatial distribution on the regional rainstorm flood process is yet to be comprehended. We propose a spatial allocation optimization system coupled with a harmony search algorithm (HS) and storm water management model (SWMM) to search the optimal imperviousness layout. The new optimization system was applied in an experimental site with an area of 0.5 km2. The distribution characteristics of the model-projected optimized imperviousness layout were analyzed. The main findings are as follows: (1) the flood peak in the outlet section can be effectively reduced by 4.01% to 35.62% merely through a reasonable optimized layout, without changing the scale of construction land; (2) in the optimized imperviousness layout scheme set, the pattern where the imperviousness is concentrated at both ends of the catchments is dominant for lighter rainfalls, while the pattern where the imperviousness is centered in the middle reaches is dominant for heavier rainfalls; and (3) in small rainfall events, with the increase of the average flow distance of the imperviousness, the flood peak tends to decrease first and then increase; in intensive rainfall events, it is almost the opposite. The findings can provide scientific guidance for flood control design in new town planning and old city reconstruction. [ABSTRACT FROM AUTHOR]

Clarifying the spatiotemporal variation of crop irrigation water requirement (IWR) under the background of climate change is an essential basis for water resource management, determining the irrigation quota and adjusting the planting structure. Using 61 years of climate data from 205 stations in Northwest China, this study investigated the spatiotemporal variations of climatic factors and IWR during the growth period of five main grain crops (spring wheat, winter wheat, spring maize, summer maize, and rice) and explored the dominant climatic driving factors of IWR variation. Results showed that (1) the IWR of grain crops showed distinct differences. Rice was the highest water consumption crop (mean of 753.78 mm), and summer maize was the lowest (mean of 452.90 mm). (2) The variation trends and average values of IWR of different grain crops have spatial heterogeneity across Northwest China. For most crops, high values and increasing trends of IWR were mainly located in eastern Xinjiang, western Gansu, and western Inner Mongolia. (3) Tmax (maximum temperature), Tmin (minimum temperature), and Peff (effective precipitation) showed an increasing trend during the growth period of each grain crop, while U10 (wind speed at 10 m height), SD (solar radiation), and RH (relative humidity) presented decreasing trends. (4) SD, Tmax, and U10 promoted the increase of grain crops' IWR, while Peff and RH inhibited it. The impacts of climatic factors on the grain crop IWR differed among different regions. Peff was the most influential factor to the IWR of all grain crops in most areas. Therefore, under the premise of a significant increase in T and uncertain precipitation mode in the future, it is urgent to take effective water-saving measures according to the irrigation needs of the region. To cope with the adverse impact of climate change on the sustainable development of agriculture in the northwest dry area, to ensure regional and national food security. [ABSTRACT FROM AUTHOR]

• Introducing the DPSIRM model to establish an evaluation indicator system. • Utilize the Extension Cloud Model to assess the health status of the water cycle. • Introduced the Degree of Obstacle Model to analyze the main obstacle factors in 11 provinces and cities. • Utilized the ARIMA model to forecast the future health of water circulation. • Put forward relevant suggestions according to the evaluation results. The regional water cycle reflects the dual processes of nature and society. A healthy and benign water cycle is a fundamental guarantee for achieving regional sustainable development.The Yangtze River Economic Belt, as a densely populated urban cluster with abundant water resources in China, plays a crucial role in promoting the sustainable development of Chinese urban clusters. It is of significant importance to optimize the water cycle health of the Yangtze River Economic Belt and explore its primary obstacles.This study integrates the natural-social attributes of the water cycle and selects 25 evaluation indicators from six dimensions: Drivers (D), Pressures (P), States (S), Impacts (I), Responses (R), and Management (M), to construct the water cycle evaluation system for the Yangtze River Economic Belt.Combining Analytic Hierarchy Process (AHP), Decision-Making Trial and Evaluation Laboratory (DEMATEL), and the Criteria Importance Through Intercriteria Correlation (CRITIC) method, the comprehensive weights of subjective and objective factors are obtained based on the principle of minimum relative entropy.Based on this, an Extended Cloud Model is constructed to evaluate the water cycle health status of the region from 2012 to 2022.Furthermore, the Obstacle Degree Model is introduced to identify the primary obstacles affecting the water cycle health in the region. Finally, the ARIMA model is applied to forecast the water cycle health status in the region from 2023 to 2030.The results indicate that the comprehensive water cycle health level in the region improved gradually from initially sub-pathological to sub-healthy status from 2012 to 2022.Per capita GDP, industrial water consumption per ten thousand yuan of industrial value added, per capita water consumption, forest coverage rate, sediment transport module, proportion of environmental protection investment to GDP, and proportion of water resources management investment to GDP are the primary obstacles affecting the improvement of health in this region.The forecast indicates that the overall water cycle health status in the region will remain at a sub-healthy level from 2023 to 2030.The research results can provide a scientific reference for further promoting the high-quality development of the Yangtze River Economic Belt, better supporting and serving China's modernization, and providing scientific reference basis. [ABSTRACT FROM AUTHOR]

[Display omitted] • A Water-economy-ecology concept framework is established. • An evaluation index system of 3 aspects including 15 indicators is constructed. • EFAST-Cloud model is innovatively proposed and applied in regional WRCC evaluation. • The WRCC of Henan Province is evaluated at the watershed scale and municipal scale. Water is the basic need for human survival and the development of economy and ecology. Water resources carrying capacity (WRCC) modelling is a fundamental task to explore the interaction mechanism between economy-ecology development and water resources carrying system. To reasonably quantify the regional WRCC, an evaluation method based on Water-economy-ecology (WEE) concept framework and EFAST-Cloud model is proposed in this study, and Henan Province of China is selected as a typical study area. It can both identify the inter-feeding relationships between sub-systems and evaluate the proportion of each grade in detail by reflecting the randomness and fuzziness of the evaluation. A total of 15 indicators including water system, economy system, and ecology system are constructed. The study analyzes the sensitivity of indicators by using Simlab software and then calculates the weight of indicators by using EFAST method. Compared with other traditional methods, EFAST algorithm is a special method for model sensitivity analysis, which can fully consider the coupling effect between indicators. According to the statistical data of 2010, 2015, and 2020, the WRCC at the watershed scale and municipal scale in Henan Province are evaluated through the EFAST-Cloud model. At the watershed scale, the ecology system criterion layer performs best over the multiple years, the Huaihe and Yangtze River basin have better WRCC at the target layer. At the municipal scale, Xuchang, Luohe, and Zhumadian have better WRCC, Puyang, Zhoukou, and Jiaozuo are slightly worse. The results show that WRCC of the study area has shown an overall improvement, but there is still much space for its development. Therefore, targeted recommendations are made for the water, economy, and ecology system respectively. The conclusion of this paper can provide a reference for the government in making water resources management policies. [ABSTRACT FROM AUTHOR]