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The acceleration of urbanization and climate change has increasingly impacted the health level of urban dual water cycles. In order to accurately evaluate the health status of urban water cycles, the evaluation system covers four standard layers of water ecology, water abundance, water quality and water use, including 19 basic indicators such as water storage change and annual average precipitation. Three-scale AHP and EFAST algorithms are adopted to set the criterion and index layer weights. Water-cycle health assessment models are based on the improved TOPSIS model. The model evaluated Zhengzhou’s water cycle health from 2011 to 2021. We compared the TOPSIS model and FCE method to ensure the scientific objectivity of the evaluation results. The evaluation results indicated that the water cycle in Zhengzhou City improved annually, and the relative progress in 2020 was 0.567 in a sub-health state. The eco-environmental water demand, green coverage rate of the built district, water resources amount, and industry’s water consumption per unit of value added (CNY 10,000) were the major obstacles. These four factors have preponderantly influenced Zhengzhou City’s water cycle health. Our research results provide scientific reference for Zhengzhou to achieve a healthy urban water cycle and regional sustainable development.

Though with abundant water resources in China, unevenly geographical and temporal distribution of water resources have constantly resulted in many severe water issues in various cities, such as inundation, drought, urban flooding, water shortage, water pollution, and inaccessibility of safe drinking water, in addition to the negative impacts of climate change. Intensive industrialization, fast urbanization, and prompt modernization have aggravated the water conflicts between different stakeholders. Furthermore, nearly 60% of Chinese population is agglomerated in urban area to exacerbate the water stress in cities, especially in megacities. In order to evaluate the performance of the integrated water resources management (IWRM) in major cities in China, and to reveal the key obstacles and challenges to the IWRM in these cities for future improvement, the modified City Blueprint® Approach, in combining with the hierarchical cluster analysis (HCA), were applied to examine the efficiency, effectiveness, and capability of the IWRM in 32 selected major cities in China, including 4 municipalities directly under the Central Government, 27 provincial capitals, and Shenzhen (a fast-emerging city located on the Pearl River Delta). The City Blueprint® Approach, consisting of three complementary frameworks, is a systematic analytic and diagnostic tool to assess the major challenges to cities (Trends and Pressures Framework, TPF), to appraise the management of urban water cycle (City Blueprint Framework, CBF), and to identify the paths of water governance improvement (Governance Capacity Framework, GCF). Significant differences have been observed between various districts and different cities. For TPF, in general, environmental pressures increase as the city scale expands, where river peak discharges and urban drainage flood are two common environmental challenges encountered by all cities. Social pressures decline and the financial pressures slightly decrease as city scale enlarged, where economic pressure and education rate are dominant indicators within each city category, respectively. For CBF, all cities have realized a great achievement in providing good basic water services, in addition to excellent performance of five indicators, drinking water quality, access to drinking water, access to sanitation, wastewater treatment, and management and action plans. In contrast, nutrient and energy recovery, public participation, and solid waste recycling, are the most critical issues to be resolved by all cities. For GCF, higher score in Enabling symbolizes the good performance of governance capacity to result in well management and action plans. Unfortunately, low score in Knowing, especially in the condition of useful knowledge, has caused the poor performance of public participation. Through HCA, the similarities and disparities between cities within diverse city categories were also revealed. In order to enhance the IWRM in major cities in China, various recommendations for future improvement were then provided, accordingly.

With a powerful capability in nonlinear mapping, the neural network has been applied widely in patter recognition and nonlinear estimation. Based on the theoretical model of vegetation ecological water requirement in arid areas, this article has estimated the vegetation ecological water requirement in lower Heihe River reaches, by use of back propagation (BP) network and radial basis function (RBF) network in Matlab.

This article established the assessment model of Fuzzy Comprehensive Assessment (FCA) and Analytic Hierarchy Process (AHP), based on the methods of AHP and FCA, and applied this model in the comprehensive profit assessment (CPA) of ecological water compensation in Heihe River basin. The result of this research is realistic and able to be popularized.