China’s Yangtzi River is the longest in Eurasia and the third longest on the planet, which flows more than 6,000 kilometers from the Tibetan plateau to the eastern China Sea. Its basin is about fifth of China’s land area and is home to hundreds of crore. More than 52,000 reservoirs have been constructed on Yangtzi and its tributaries since the 1950s, which to reduce floods, generate hydropower, stabilize water supply and protect the ecology.
There is a host of challenges in the management of this giant basin to continue to develop water sources and to support sometimes protestable goals of protecting ecosystems. Population growth, growth and urbanization in the region are continuously increasing the demand for water, while increasing pressure on water pollution and biodiversity. Although the average annual rainfall of the Yangtzi River Basin has changed relatively low in the last two decades, there has been an increase in drought and flood frequency and severity due to changes in the use of rainfall and landscape.
For example, the hydropower company China Yangtzi Power, located in Beijing, found that the average drought duration in 2000 is now two weeks more than two weeks. In 2020, Yuchang had the highest current rate in 2003 due to unusually heavy rains. Estimated US $ 16.5 million caused in loss1,
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A more clever, more strong system of trekking, modeling and water management in this basin will help reduce such issues, resulting in operation safety and low cost. To end this, Changjiang Water Resources Commission (CJW) Smart Yangtzi River Project (See (See) go.nature.com/4h51xzf), Under the aegis of the Ministry of Chinese Water Resources. The project was proposed in 2022 and is now with a planned completion date of 2035 for the initial design, a basin-wide, full-coverage water-lower system for dedicated government investment, for 597 million yuan (US $ 82 million) dedicated government investment. Many hydroelectric companies are also contributing hundreds of crores of yuan to this initiative.
The center of the project is a digital twin of the Yangtzi River Basin. This twin contains an advanced 3D simulation of the entire region, which uses data on weather, water flow, ecology, sedimentary properties, topography, energy demand and more, which offers an estimated flood routing, water engineering, scheduling, shipping, ecological effects and real time modeling of other results.
The interface with intuitive knowledge provides a reliable evaluation of the sustainable development and the impact of resource-management decisions and watershed-preservation works on sustainable development and biodiversity health. It can be used for forecasting, initial warnings, emergency-system rehearsals and casual planning. The first version of this digital twin is already present and in use (see ‘Yangtzi River Basin’, and go.nature.com/3wvchj1), Including two supplements watershed (of Han and Lishui rivers) and four dams (The Three Gorj, Danziangakau, Jiangya and Joshi). This will be greatly improved and expanded with more data and modeling in the coming years.
Source: World Bank
Currently, about 2,700 water-level monitoring stations and more than 37,000 rainfall stations are collecting data in the Yangtzi River Basin. In April 2023, work began on new and existing hydrological-station networks in major areas such as Yangtzi River, Donging Lake and Poyang Lake with increased monitoring methods including video and remote sensing. On completion, the Smart Yangtzi river project will also include hundreds of monitoring stations for water quality and groundwater level, and tens of thousand water consumption points.
The very related work has been completed in the last five years-for example, China Yangtzi Power now uses a wise decision-support system for reservoir-shadeuling simulation and flood practice. Yangtzi River simulator, Zia, developed by Zia June, is a device for monitoring, simulation and analysis of a hygienic, flood control, power generation and biodiversity conservation in Wuhan University, China.2,3,
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Although the use of digital twin children has increased for everything from industrial construction to transport in the last decade, there are relatively some digital-twin representations used for intelligent watershed management. The Yangtzi project can represent such an initiative so far. This huge effort presents adequate challenges in the context of improving the existing data collection and management as well as improvement in models and services.
Researchers have already deposited the treasure of data and experience. But the entire capacity of the Smart Yangtzi River Project is still away from feeling. Lack of funding is an issue: Many departments, companies and research institutes engaged in the project need to secure their own money. More data is required to collect and digitize; Data and model formats need to be standardized and shared in industry and academics.
Many companies have yet to engage in the project due to cost or technical barriers, or perhaps because they fear that it may affect their profits. Further cooperation should solve these challenges, so that the managers have enough guidance to make decisions.
Here, we recommend four stages that will help ensure the success of the program.
Unite data and model standards
A digital twin requires a variety of data, which is taken at different time intervals and in different formats. For example, a broad and precise rainfall and run-off model may require data on atmospheric temperature, humidity from meteorological satellites and cloud distribution and surface vegetative coverage and land use from optical remote-sensing satellites. It may also require information on river morphology and laser-based radar, or lidar from the area from drone-mounted cameras. A digital twin requires sufficient data to run high-resolution modeling, but not so that it creates transmission bottlenecks.
Lack of universal methods, standards and specifications is challenging to integrate data from many monitoring networks. Data is often fragmented in various institutions and stored in diverse formats. For example, meteorological and run-off data are conducted by the Chinese Bureau of Hydrology; Reservoir-conducting data by hydroelectric companies; And Water Resources Committee Data by CJW. Inside the government, many data formats are used: Water-Classic Department uses HDF, uses environmental security department CSV, meteorological department depends on NETCDF and the electricity department uses commentade.
Digital twins, such as one of the zoshi dam, can help with real -time water management.Credit: Dr. Geopeng Wang
All desired information is also not digitized. For example, information about electricity demand, electricity market data, power-line restrictions and emergency information, still sometimes recorded and analyzed without the use of computers. The existing reservoir remittance rules, projects and schemes are usually documented in hand -written form rather than digital.
It is also important to develop standards for models used to process all these figures, to ensure that they are versatile, reusable and inter -qualified. It is necessary to create a common design and development platform for the Smart Yangtzi River Project System, enabling all models to operate originally. The project is building integrated data and model standards. Nevertheless, many areas are insufficiently compatible.
There are some global examples that show how digital twins with good standards to be developed strongly – in general, the concept of digital twinning is more advanced in industrial construction than river management. One such example is a virtual shared scope established by American aircraft manufacturer Boeing to facilitate cooperation among its corporate partners. European Digital Twin Ocean Project (See) go.nature.com/3cdab5p)) The data-governance structure has been installed in a wide swath of the material to determine the standards for data and models, including satellite observation data, ocean-model output,, Besides Measurement and data from historical, industrial and civilian-science sources.
Share data and models
Currently, the Yangtz Digital-Twin platform is hosted by the Yangtzi River Commission and the internal network of several companies, and it is not fully accessible to scientists and others that work around the basin. The interaction between industry and academics is minimal, obstructed by obstacles in information and access to resources, which is often attributed to commercial privacy. An issue lies in data ownership. The Regional Water management departments and companies are usually reluctant to share commercially sensitive information. Similarly, hydropower companies may find it difficult to get power dispatch data from power-grid companies.
