This paper aims to achieve the coordination between resource development and utilization and ecological environment protection in the Yangtze River Basin during its participation in the "Belt and Road" construction.It constructs a multi-objective decision support system for the comprehensive management of the Yangtze River Basin oriented towards the "Belt and Road".Firstly, the current situation of resource utilization and ecological environment protection in the Yangtze River Basin is analyzed, along with the mechanism and coordinated countermeasures for the contradiction between development and protection.Coordinated countermeasures combining regulation, compensation, and policy incentives are proposed.Secondly, a multi-objective decision model considering the objectives of different decision-making entities is constructed to balance the relationship between ecological protection and economic development.Then, data collection and intelligent analysis methods that support decision-making, as well as multiobjective optimization algorithms, are designed to enhance the scientificity of decisionmaking and provide technical and methodological support for the Yangtze River Basin to achieve green development.
Integrated watershed management plays an important role in achieving sustainable utilization of watersheds.Still, there are problems in current management processes such as insufficient data collection, limited model expressiveness, and reliance on personal experience in decision-making.These have become bottlenecks in advancing refined and intelligent watershed management.To resolve this contradiction, this study constructs an intelligent watershed management system based on artificial intelligence technologies.The system achieves efficient, comprehensive intelligent monitoring of the watershed environment by deploying sensor networks and using mobile measuring devices.Meanwhile, knowledge-based technologies are utilized to represent, store, and manage multi-source heterogeneous data.On this basis, techniques such as deep learning are used to establish digital twin and predictive models of the watershed to achieve accurate representations of the operating mechanisms of complex systems.Finally, the system can perform multi-scenario comparative analysis to assist decision-makers in scientifically formulating management strategies.Case studies demonstrate that the constructed system can make up for the deficiencies of traditional management methods and significantly improve the scientific and intelligent levels of watershed management.This research provides a systematic framework and technical approach for constructing an intelligent watershed management system, with important theoretical value and practical significance.
本文基于淮河流域吴家渡水文监测站1950-2007年月径流量资料,通过定义长、短周期径流旱涝急转指数,分析了淮河流域汛期径流旱涝急转现象(分旱转涝和涝转旱两种类型),研究结果表明:1)长周期径流旱涝急转在1986年以前发生次数较多,而1986年以后发生次数相对较少;2)各相邻月间的短周期旱涝急转的年际振荡以6-7月最多,且其长期变化规律与长周期旱涝急转年际振荡变化相似;3)长、短周期旱涝急转频次呈现不断减少的趋势,但全旱和全涝频次则有增加的趋势;4)2000s汛期长周期旱转涝、短周期6-7月旱转涝有逐渐增加的趋势,分析认为这种旱涝急转变化是导致淮河流域汛期径流量增加的主要原因之一.;Based on the monthly runoff data during 1950-2007 at Wujiadu Hydrologic Station in the Huaihe River Basin, the drought-flood abrupt alternation phenomena(including drought to flood and flood to drought) based on runoff was analyzed during the main rainy season(MJJA) by using long-and short-cycle runoff drought-flood abrupt alternation index(RDFAI). The results are as follows:1) the frequency of long-cycle runoff drought-flood abrupt alternations was higher in the period before 1986, and then decreased after the late 1980s; 2) Inter-annual changes of the short-cycle runoff drought-flood abrupt alternation phenomena between the adjacent months varied from each other, with the change between June and July being the most obvious one, and the long-term changes are similar to that of the long-cycle runoff drought-flood abrupt alternation phenomena; 3) Both the occurrence of long-and short-cycle runoff drought-flood abrupt alternation phenomena showed decreasing trends during the past 57 years, however, the total drought and total flood phenomena were on the rise; 4) During the 2000s, both the long-cycle and short-cycle runoff drought to flood abrupt alternation in June and July increased, and this might be one of the major reasons for the runoff increase during the rainy season at the same period.
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