ArticlePDF Available

Realizing the full reservoir operation potential during the 2020 Yangtze river floods

Authors:

Abstract and Figures

Five severe floods occurred in the Yangtze River Basin, China, between July and August 2020, and the Three Gorges Reservoir (TGR) located in the middle Yangtze River experienced the highest inflow since construction. The world’s largest cascade-reservoir group, which counts for 22 cascade reservoirs in the upper Yangtze River, cooperated in real time to control floods. The cooperation prevented evacuation of 600,000 people and extensive inundations of farmlands and aquacultural areas. In addition, no water spillage occurred during the flood control period, resulting in a world-record annual output of the TGR hydropower station. This work describes decision making challenges in the cooperation of super large reservoir groups based on a case-study, controlling the 4th and 5th floods (from Aug-14 to Aug-22), the efforts of technicians, multi-departments, and the state, and reflects on these. To realize the full potential of reservoir operation for the Yangtze River Basin and other basins with large reservoir groups globally, we suggest: (i) improve flood forecast accuracy with a long leading time; (ii) strengthen and further develop ongoing research on reservoir group cooperation; and (iii) improve and implement institutional mechanisms for coordinated operation of large reservoir groups.
This content is subject to copyright. Terms and conditions apply.
1
Vol.:(0123456789)
Scientic Reports | (2022) 12:2822 | https://doi.org/10.1038/s41598-022-06801-8
www.nature.com/scientificreports
Realizing the full reservoir
operation potential during the 2020
Yangtze river oods
Hairong Zhang1,2, Yanhong Dou3*, Lei Ye3*, Chi Zhang3, Huaming Yao1,2, Zhengfeng Bao1,2,
Zhengyang Tang1,2, Yongqiang Wang4, Yukai Huang1,2, Shuang Zhu5, Mengfei Xie6,
Jiang Wu4, Chao Shi7, Yufeng Ren1,2, Dongjie Zhang1,2, Biqiong Wu1,2 & Yufan Chen1
Five severe oods occurred in the Yangtze River Basin, China, between July and August 2020, and
the Three Gorges Reservoir (TGR) located in the middle Yangtze River experienced the highest inow
since construction. The world’s largest cascade-reservoir group, which counts for 22 cascade reservoirs
in the upper Yangtze River, cooperated in real time to control oods. The cooperation prevented
evacuation of 600,000 people and extensive inundations of farmlands and aquacultural areas. In
addition, no water spillage occurred during the ood control period, resulting in a world-record
annual output of the TGR hydropower station. This work describes decision making challenges in the
cooperation of super large reservoir groups based on a case-study, controlling the 4th and 5th oods
(from Aug-14 to Aug-22), the eorts of technicians, multi-departments, and the state, and reects
on these. To realize the full potential of reservoir operation for the Yangtze River Basin and other
basins with large reservoir groups globally, we suggest: (i) improve ood forecast accuracy with a long
leading time; (ii) strengthen and further develop ongoing research on reservoir group cooperation;
and (iii) improve and implement institutional mechanisms for coordinated operation of large reservoir
groups.
Floods are the most frequent natural disaster globally aecting countless lives and property1. Reservoirs, one of
the most ecient infrastructures in ood control2, were built extensively, such that, cascade-reservoir groups are
common in large basins, such as the Nile3, the Yangtze River (alias: Changjiang)4, the Yellow River5, etc. When
encountering a severe ood, cascade-order impounding of oods for cascade-reservoir groups can reduce the
ood control pressure of a single reservoir and improve the ood control ability of the whole basin6. However,
each reservoir must manage a balance between ood risk and economic benet such as power generation and
shipping, and benets gained from dierent reservoirs vary between each other7,8. According to the World
Commission on Dams9, most large reservoirs worldwide cannot produce benets the authorities are satised
with. As a result, the cooperation of cascade-reservoir groups has been extensively considered by hydrologists
and decision makers. However, the connection between hydrologists and decision makers is relatively weak,
although there are many studies on reservoir cooperation1013, little feedback and reection has emerged from
users. In this work, we describe challenges, achievements and reections of the cooperation practice of the
world’s largest cascade-reservoir group in the upper Yangtze River when facing a ood larger than that with a
100-year recurrence interval.
e Yangtze River, the third-longest river in the world, plays an paramount role in the economy, energy, and
ecology of China1417; it has a basin area of 1.8 × 106 km2 that serves a population of nearly 50 million people,
generates 40% of the China’s Gross Domestic Product (GDP), and outputs 30% of China’s grain. e Yangtze
River Basin is shown in Fig.1a, where the distribution of population density is developed by Socioeconomic
Data and Applications Center18. Reservoir groups on the upper Yangtze River are vital for ood control in the
middle and lower regions19,20. e largest cooperation system of reservoirs in the world is constructed in the
upper Yangtze River Basin, as shown in Fig.1b, which counts for 22 cascade reservoirs with a total ood control
OPEN
1China Yangtze Power Co., Ltd., Yichang 443133, China. 2Hubei Key Laboratory of Intelligent Yangtze and
Hydroelectric Science, Yichang 443133, China. 3School of Hydraulic Engineering, Dalian University of Technology,
Dalian 116024, China. 4Changjiang River Scientic Research Institute, Wuhan 430074, China. 5School of
Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China. 6Kunming
Power Exchange Center Co., Ltd., Kunming 650011, China. 7Yunnan Power Grid Co., Ltd., Kunming 650011,
China. *email: dou.yhong@gmail.com; yelei@dlut.edu.cn
Content courtesy of Springer Nature, terms of use apply. Rights reserved
2
Vol:.(1234567890)
Scientic Reports | (2022) 12:2822 | https://doi.org/10.1038/s41598-022-06801-8
www.nature.com/scientificreports/
capacity of 38.7 × 109 m321. e system takes the ree Gorges Reservoir (TGR; largest installed capacity in the
world) as the core reservoir, the cascade reservoirs in the lower Jinsha River, including Wudongde (7th), Xiluodu
(4th), and Xiangjiaba (11th), as the main reservoirs, and the cascade reservoir groups in the middle Jinsha River
(six reservoirs), Yalong River (two reservoirs), Min River (two reservoirs), Jialing River (four reservoirs), and
Wu River (four reservoirs) as the coordinating reservoirs.
Challenges
Severe oods of Yangtze river. Rainfall distribution is grossly inhomogeneous in both spatial and tem-
poral aspects in the Yangtze River Basin, beneting from its location in the subtropical monsoon climate zone
on the east coast of Eurasia22,23. As a result, oods occur frequently in the Yangtze River Basin and are usually
characterized by a strong sudden occurrence, signicant areal extent, and massive loss of lives and property24,25.
Figure1. (a) e geographical location, streams, reservoirs and population density of Yangzte River Basin
generated by ArcGIS 10.2. (b) Sketch map of 22 reservoirs on the upper Yangtze River included in the joint
operation until 2020, where the circles represent reservoirs.
Content courtesy of Springer Nature, terms of use apply. Rights reserved
3
Vol.:(0123456789)
Scientic Reports | (2022) 12:2822 | https://doi.org/10.1038/s41598-022-06801-8
www.nature.com/scientificreports/
In 2020, ve severe oods occurred between July and August along the Yangtze River as shown in Fig.2. e
TGR, located in the middle Yangtze River, experienced the highest inow of 74,600 m3/s since its construction.
Among the ve numbered oods, 4th and 5th oods (from Aug-14 to Aug-22) were caused by two continuous
rainfalls characterized by long duration, high intensity, and overlapping rainfall elds which covered most of the
upper Yangtze River. During the rainstorm, the 5-day accumulated rainfall exceeded 400mm, meaning that half
of the average annual rainfall fell in just ve days. As a result, ood peaks of the upper Yangtze River tributaries
would encounter before entering the TGR and a ood larger than that with a 100-year recurrence interval would
be formed without reservoir operation.
Complex operating decision of super large reservoir groups. Cooperation of reservoirs in the main‑
stream and tributaries. According to the joint operation scheme, when a severe ood occurs, the TGR and
the 21 upstream reservoirs will coordinate with each other to control the ood. is means that the upstream
reservoirs would not only perform their own ood control tasks, but also reserve part of their ood control ca-
pacity, known as reserved ood control capacity, to cooperate with the TGR to mitigate ooding in the middle
and lower regions of the Yangtze River. e mainstream ood may be comprised of two or even more oods
in the tributaries owing to the numerous tributaries and their frequent ood encounters in the Yangtze River26.
Considering the complicated composition of mainstream oods, various cooperation schemes should be used
for the reservoirs on the mainstream and tributaries. Additionally, the distance between each reservoir group is
signicant as shown in Fig.1a, which increases the inherent uncertainty of ood routing and rainstorm displace-
ment direction forecasting. erefore, the real-time joint operation of the super large reservoir groups faces the
problem of how to determine the utilization order of the reserved ood control capacity, as well as how much
to use and maintain.
Impact on stable power supply. e cascade hydropower stations on the upper Yangtze River are the key
power sources of China27. e theoretical and exploitable hydropower resources in the Yangtze River Basin
are 2.68 × 109kW and 2.35 × 109kW, respectively, out of which the upper Yangtze River accounts for more than
90%. Considering the Xiluodu-Xiangjiaba-ree Gorges cascade stations as an example, these three stations
are responsible for power supply to nine of the most economically developed provinces and cities in China,
including Guangdong, Jiangsu, Zhejiang, and Shanghai28. However, when cooperating with the downstream or
mainstream reservoirs, the upstream or tributary reservoirs must reduce discharge to release the reserved ood
control capacity, leading to a decrease in the output of the hydropower stations and making it dicult to gener-
ate stable power as specied in the original generation schedule2931. With respect to the status of the cascade
hydropower stations on the upper Yangtze River, erratic hydropower supply aects other power sources in the
power grid like dominoes, particularly by decreasing the output during the peak summer months. erefore,
the second problem that the real-time joint operation of super large reservoir groups faces is how to adjust the
generation schedule.
Impact on safe operation. During a severe ood, the increasing inow and exible discharge of reservoirs
quickly change the water levels of both upstream and downstream dams, impacting the safe operation of water
conservation projects32 and shipping transportation. Taking Xiangjiaba reservoir as an example, if the daily vari-
ation in the water level exceeds 4m, it leads to reservoir bank instability33, and if the water level variation is too
large in the downstream dam, shipping safety is aected8. erefore, precise control of water level variation is
necessary, particularly at night, adding additional uncertainties owing to fewer sta.
Figure2. Outow, inow, and water level of TGR during 2020 ood season.
Content courtesy of Springer Nature, terms of use apply. Rights reserved
4
Vol:.(1234567890)
Scientic Reports | (2022) 12:2822 | https://doi.org/10.1038/s41598-022-06801-8
www.nature.com/scientificreports/
Coordination of multiple departments. Each reservoir included in the upper Yangtze River cooperation system
is responsible for multiple simultaneous missions, such as ood control, power generation, and shipping7,8, etc.
e operation of reservoirs aects the competition-relation benets of multiple departments34. For example,
when facing a ood, the objective of Changjiang Water Resources Commission (CWRC) of the Ministry of
Water Resources (i in the Fig.3) is mitigating the threat of ood to the protection objectives in the basin, such
as populated localities, factories and farmlands. For this purpose, impounding and/or discharging of reservoirs
will cause frequent changes of water level and ow, which aects shipping and power generation signicantly.
Both the Changjiang Waterway Bureau (CWB) of the Ministry of Transport and power grid corporations hope
to reduce the duration of such abnormal operation as much as possible (ii and iii in the Fig.3). Additionally, it
is necessary to consider maintenance schedules and upper limits of transmission for each hydropower station
(iv in the Fig.3). erefore, one problem reservoir cooperation decision making faces, is how to manage and
balance the objectives and requirements of multi-departments.
Achievements of cascade-reservoir cooperation
Flood control. To prevent the 1st, 2nd, and 3rd oods of the Yangtze River in 2020, 20.5 × 109 m3 of the
ood control capacity of the 22 joint-operation reservoirs was used, accounting for 53% of the total ood con-
trol capacity. On this basis, to prevent the 4th and 5th oods, the cascade reservoir groups cooperated on a large
scale again and held up 19.0 × 109 m3 of ood volume. ere is 8.2 × 109 m3 of ood volume held up by the 21
reservoirs upstream of the TGR, as shown in Fig.4, which prevented ood peak encounters of the Jinsha River
(Xiangjiaba Station), Minjiang River (Gaochang Station), and Jialing River (Beibei Station). As a result, before
the ood enters the TGR (Cuntan Station), the ood peak with a 90-year recurrence interval (87,500 m3/s) was
reduced to 20years (74,600 m3/s), the ood volume with a 130-year recurrence interval was reduced to 40years
(36.00 × 109 m3), and the peak river stage was reduced by 3m. In this manner, ood control pressure at the tail
of the TGR was signicantly mitigated. e other 10.8 × 109 m3 of ood volume was held up by the TGR, which
reduced the ood with a 50-year recurrence interval (40.00 × 109 m3) to an ordinary ood and avoided the uti-
lization of the Jingjiang Flood Diversion Area. e above ood control cooperation prevented signicant direct
property loss in the middle Yangtze River, such as the evacuation of 600,000 people and inundation of 330 km3
of farmlands and more than 70 km3 of aquaculture areas.
Hydropower generation. In response to ood control, power grid companies adjusted the hydropower
generation schedules of relevant reservoirs eciently and scientically to ensure stable power supply, ecient
use of water resources, and greater power generation. Taking the operation of the Xiangjiaba Reservoir during
the 4th and 5th ood as an example, the Xiangjiaba Reservoir had to reduce the discharge and hold the ood in
order to cooperate with the TGR, resulting in decreased ow through the turbine and the plummeting power
generation. e State Grid quickly adjusted the power generation schedule, that is, permitted the output of the
Xiangjiaba hydropower station to be reduced to 2.2 × 106 kW at 17:00 on Aug. 17, and subsequently, the output
was increased to the rated power at 9:00 a.m. on Aug. 19. During the entire process, no water spillage occurred.
As a result, the Xiluodu-Xiangjiaba cascade hydropower stations and the single station of the TGR generated
Figure3. e relationship between six types of water-related departments, where i to iv indicate the objectives
and/or requirements of each corresponding type of department for reservoir cooperation, and v indicates
the submission of the cooperation scheme ensemble from Cascaded Reservoir Operation Center (CROC) to
Flood Control and Drought Relief Headquarters (FCDRH) considering the above objectives and requirements.
e nal cooperation scheme is determined through multi-department consultation under the leadership of
FCDRH.
Content courtesy of Springer Nature, terms of use apply. Rights reserved
5
Vol.:(0123456789)
Scientic Reports | (2022) 12:2822 | https://doi.org/10.1038/s41598-022-06801-8
www.nature.com/scientificreports/
electricity outputs of 3.20 × 1010 kWh and 1.67 × 1010 kWh, respectively in August 2020, which are 49% and
42%, respectively more than the 10-year average in the same period. In addition, the TGR hydropower station
generated electricity output of 1.12 × 1011 kWh in 2020, hitting a world record for annual output of a single
hydropower station35.
Safe operation. e water level variations of both the upstream and downstream dams met the correspond-
ing regulation during the ood control cooperation owing to the benet derived from the forecast of precipita-
tion and hydrology and the simulation of hydrodynamics and reservoir operation. e daily water level variation
of the Xiluodu and Xiangjiaba reservoirs were 4.95m (5m in regulation) and 3.73m (4m in regulation) respec-
tively, which is the largest since their construction. From July to September 2020, more than 4500 ships and 15
million tons of cargo successfully passed through the waterway in an orderly manner.
Reections
Real-time cooperation was adopted for cascade reservoir groups for controlling oods in 2020, realizing the full
reservoir operation potential. During the real-time cooperation, conventional operation schedules and regula-
tions are always not applicable. Below are three key reections from the reservoir operation during the 2020
Yangtze River ood.
Figure4. e triangles represent the hydrological stations; and naturalized and measured ows of major
hydrological stations in the upper Yangtze River during 4th and 5th oods, where the naturalized ow of the
stations on the Jinsha River (Xiangjiaba), Min River (Gaochang), Jialing River (Beibei), and upstream of the
TGR (Cuntan) is obtained using the Intelligent Changjiang Decision Support System (ICDSS) according to the
actual operational data of upstream reservoirs and considering the ood travel time and water balance.
Content courtesy of Springer Nature, terms of use apply. Rights reserved
6
Vol:.(1234567890)
Scientic Reports | (2022) 12:2822 | https://doi.org/10.1038/s41598-022-06801-8
www.nature.com/scientificreports/
Accurate forecast of precipitation and ow. Technicians from the CROC of China Yangtze Power Co.,
Ltd. forecasted the extreme precipitation and oods two weeks ahead of the 4th ood qualitatively, 2 oods with
both peaks of more than 60,000 m3/s a week ahead qualitatively, and the discharge and appearance times of the
ood peaks 3–5days ahead quantitatively, using the system that is responsible for precipitation and hydrology
forecasting in ICJDSS (details can be seen in “Methods and materials” section). Owing to the lower accuracy
of the forecast with a longer leading time36, the forecast changed from qualitative estimation to quantitative
prediction with the gradual approach of the forecast target. e quantitative forecast performance is presented
in Table1.
Following the qualitative precipitation forecast of the next 7–14days, the water level of the TGR dropped from
163.36m on Jul-29 to 153.03m on Aug-14 (its ood limited water level is 145m) by pre-discharging; further,
17.75 × 109 m3 of the ood control capacity was reserved, accounting for 80% of the total ood control capac-
ity of the TGR, which ensured adequate preparation for ood control and time to adjust the power generation
schedule. Following the quantitative ood forecast of the next 3–5days, the reserved ood control capacity of
upstream reservoirs (mentioned in section“Complex operating decision of super large reservoir groups”) was
released to hold up a portion of the ood and stagger ood peaks through real-time joint operation.
Scientic cooperation of cascade reservoir groups. In recent years, research eorts on the joint oper-
ation and coordinated management of reservoirs in the upstream Yangtze River have continued to increase, and
the application of scientic cooperation of cascade reservoir groups has also been enriched.
In terms of a cooperation scheme, the ood control capacity of the reservoirs in the upper Yangtze River
is reserved for cooperation with other reservoirs, and the reserved capacity is gradually released based on the
ood season stages37,38 and the reservoir classications. Specically, (1) In the main ood season, the necessary
capacity is reserved to hold the possible oods, and gradually released when the inow shows a declining trend
during the post-ood season. (2) e release order of each reservoir depends on ood encounter situations,
its own ood control tasks, and its role in cooperation with the TGR for ood control of the middle and lower
Yangtze River regions.
In terms of real-time cooperation, existing technology is used to predict or identify the ood type39, whereas
the ood control capacity of cascade reservoirs is determined by regulating each type of ood in the entire basin
during the design stage. erefore, in the case where there is no need to prevent various ood types simultane-
ously, some reservoirs have surplus ood control capacity. e surplus capacity of upstream reservoirs share the
ood control tasks of the downstream reservoirs, and as a result, the water levels of the downstream reservoirs
can be raised to increase the benet without increasing the ood risk of the entire basin40. In this manner, reser-
voirs can be compensated by the capacity of each reservoir based on the relatively accurate forecast and the joint
operation pattern, so that the water levels of some reservoirs with signicant benets in the ood season can be
relatively high and exibly controlled without strictly following a single ood limit water level. For instance, with
the most signicant benets in the Yangtze River, the legislative ood limit water level of TGR ranges from 145.0
to 146.5m. Between the 3rd and the 4th ood, the water level of the TGR was reduced to 153.03m by maximum
discharge through turbines, rather than the ood limit water level of 145m with water spillage, as the upstream
reservoirs could hold up part of the ood41,42. In Fig.4, it can be observed from the dierence between the natu-
ralized and measured ows at the Xiangjiaba Station that the Xiangjiaba reservoir and its upstream reservoirs play
an important role in ood storage and ood peak staggering; at the Gaochang and Beibei Stations, the reservoirs
in the Min and Jialing Rivers also hold up part of the ood, so that the ood peaks of the Gaochang and Beibei
Stations with recurrence intervals of 40–50years (40,600 m3/s) and 10–15years (38,400 m3/s), respectively were
reduced to 10–15years (37,500 m3/s) and 10years (37,400 m3/s), respectively.
Regulations for multi-department coordination. e Yangtze River reservoirs can be exibly used to
realize the potential benets safely by joint operation, which is inseparable from the state macro-coordination
(state FCDRH) and the cooperation of the local governments (local FCDRH), the basin management organiza-
tion (CWRC), the transport department (CWB), hydropower stations and power grid companies. As an inter-
mediary of multiple departments, CROC is responsible for the technical support of generating an ensemble
of potential cooperation schemes and information transport and management. During the 4th and 5th ood,
the above departments held 10 consultations on matters including real-time hydro-meteorological monitoring
and forecast information, real-time joint operation of reservoirs, and temporary adjustment of the hydropower
generation schedule. Reservoirs discharged exibly in real-time, rather than strictly following rigid operating
schedules and regulations.
Table 1. Quantitative forecast performance during 4th and 5th oods in 2020.
No
Measured Forecasted Evaluation
Peak ow (m3/s) Peak time Leading time Peak ow (m3/s) Peak time Error of peak ow Error of peak time
4 62,000 Aug-15 5 day 50,000 Aug-16 −19.35% 1 day
1 day 62,000 Aug-15 0 0
5 74,600 Aug-20 5 day 62,000 Aug-20 −17.33% 0
1 day 74,600 Aug-20 0 0
Content courtesy of Springer Nature, terms of use apply. Rights reserved
7
Vol.:(0123456789)
Scientic Reports | (2022) 12:2822 | https://doi.org/10.1038/s41598-022-06801-8
www.nature.com/scientificreports/
To ensure a scientic, unied, and coordinated operation of the cascade reservoir groups in the Yangtze River
Basin, a series of relevant regulations have been established in recent years. In the aspect of monitoring and
management, the institutional mechanism dedicated to information sharing, benets compensation43, and risk
control44,45 for the reservoir groups has been established. In terms of the administrative system, the coordination
mechanism dedicated to multiple departments involving water resources, power, shipping, and environmental
protection has been improved46 based on the existing ood control organization47. On the basis of continuous
improvement of the above mechanisms and systems, the legislation of the Law of the People’s Republic of China
on the Protection of the Yangtze River was promoted, which was promulgated on December 26, 2020, and came
into force on March 1, 202148.
Call for action
Largely drawing on the reections reported based on the reservoir cooperation during the 2020 Yangtze River,
we suggest the following action points to realize the full potential of the reservoir operation of the Yangtze River
basin and other basins with large reservoir groups in the world:
1. Improve ood forecast accuracy with a long lead time. Accurate ood forecast is the premise of joint and
precise operation of reservoir groups, adjustment of the power generation schedule, and multi-department
cooperation.
2. Continue to study the cooperation of reservoir groups. As the number of reservoirs included in the joint
operation increases constantly, new situations and challenges with new requirements will gradually become
prominent. It is necessary to conduct research on the cooperation of reservoir groups and to formulate
scientic counter measures.
3. Improve and implement regulations for the coordinated operation of large reservoir groups. A powerful
coordination regulation has the potential to guarantee eective implementation of the scientic operation
of super large reservoir groups.
Methods and materials
Decision making of reservoir cooperation in upper Yangtze River Basin includes three steps. Firstly, the prelimi-
nary ensemble of cooperation schemes is obtained by Cascaded Reservoir Operation Center (CROC) through
Intelligent Changjiang Decision Support System (ICDSS), powered by China Yangtze Power Co., Ltd. Secondly,
departments through rounds of consultation to determine the nal cooperation scheme. Finally, ICDSS reanalysis
will be used to summarize the experience aer the ood.
Intelligent Changjiang decision support system. Intelligent Changjiang Decision Support System
is vital for the reservoir groups to optimally achieve the comprehensive operation objectives of ood control,
power generation, shipping and ecology by building a tailored technology framework. ICDSS includes four
main components: a data acquisition and management system; a set of interlinked models and data-model-user
interactive interface; a socioeconomic evaluation system; and crisis management plans.
Data acquisition and management system. is system is responsible for automatic collecting and managing
unstructured data (e.g., hydro-meteorology data, operation data and grid load data) and semi-structured data
(e.g., operation regulations and instructions). In the upper Yangtze River Basin, there are 1005 hydrological sta-
tions (of which 372 are managed by local Hydrological Bureau and 633 by CRCC), 12,129 precipitation stations
(of which 730 are national stations, 11,000 are local stations and 399 are managed by CROC), and 37 national
ground-based radars. e failure rate of the above stations was 1.7% in the past three years.
Interlinked models and data‑model‑user interactive interface.
a. Simulation of upstream reservoir operation: e operation of cascade hydropower stations in the upper
Yangtze River changes the propagation characteristics of natural ow, as a result, the accuracy of hydrological
forecasting is aected. erefore, this system is responsible for mining rules of impounding and discharging
for upper reservoirs that is not included in joint operation and anticipating discharge of these reservoirs.
b. Hydro-meteorological forecast and discharge routing simulation4952: e system is composed of the
Xin’anjiang model with 377 subunits, the one-dimensional hydrodynamic model, and the error correction
module. Each module of the system runs automatically but can also be supplemented by human–machine
interaction functions depending on the experience of the forecasters.
c. Optimal cooperation of cascade-reservoir groups with dierent leading time5356: is system is responsible
for generating the optimal ensemble of reservoir cooperation based on hydro-meteorological forecast with
dierent leading time. e NSGA-II is used to obtain the optimal cooperation schemes and Pareto solutions
of corresponding objectives. Hedging theory and marginal benet theory are used to analyze the competition
between risk and benet. As the update of forecast information with dierent leading time, the ensemble of
reservoir cooperation is rolling executed.
Socioeconomic evaluation system. is system is responsible for evaluation and reanalysis the cooperation pro-
cess of cascade-reservoir groups. By analyzing the contribution of each reservoir in cascade-reservoir groups
to ood control, power generation, shipping and ecology, the inuence of man-made and natural factors in the
Content courtesy of Springer Nature, terms of use apply. Rights reserved
8
Vol:.(1234567890)
Scientic Reports | (2022) 12:2822 | https://doi.org/10.1038/s41598-022-06801-8
www.nature.com/scientificreports/
comprehensive achievements is claried, and the operation scheme will be revised and improved based the re-
evaluation of results.
Crisis management plans. ere are 22 crisis management plans for failures of automatic control systems,
equipment and power, as well as kinds of accidents and emergencies.
Received: 18 August 2021; Accepted: 2 February 2022
References
1. International Federation of Red Cross and Red Crescent Societies. World Disasters Report. (2020).
2. Someya, K. Collaborative and adaptive dam operation for ood control. J. Disaster Res. 13(4), 660–667 (2018).
3. Wheeler, K. G. et al. Exploring cooperative transboundary river management strategies for the Eastern Nile Basin. Water Resour.
Res. 54, 9224–9254. https:// doi. org/ 10. 1029/ 2017W R0221 49 (2018).
4. Li, H., Liu, P., Guo, S., Cheng, L. & Yin, J. Climatic control of upper Yangtze River ood hazard diminished by reservoir groups.
Environ. Res. Lett. 15, 124013 (2020).
5. Chang, J. et al. Reservoir operations to mitigate drought eects with a hedging policy triggered by the drought prevention limiting
water level. Water Resour. Res. 55, 904–922. https:// doi. org/ 10. 1029/ 2017W R0220 90 (2019).
6. Li, J., Zhong, P., Yang, M. & Zhu, F. Dynamic and intelligent modeling methods for joint operation of a ood control system. J.
Water Resour. Plan. Manag. 145, 1–12 (2019).
7. Chang, J., Meng, X., Wang, Z., Wang, X. & Huang, Q. Optimized cascade reservoir operation considering ice ood control and
power generation. J. Hydrol. 519, 1042–1051 (2014).
8. Yuan, P., Wang, P. & Zhao, Y. Novel model for manoeuvrability of ships advancing in landslide-generated tsunamis. Adv. Civil.
Eng. 2020, 1–15 (2020).
9. World Commission on Dams. Dams and Development: A New Framework for Decision‑Making: e Report of the World Commis
sion on Dams (Earthscan Publications Ltd., 2000).
10. Li, C., Zhou, J., Ouyang, S., Wang, C. & Liu, Y. Water resources optimal allocation based on large-scale reservoirs in the upper
reaches of Yangtze river. Water Resour. Manag. 29, 2171–2187. https:// doi. org/ 10. 1007/ s11269- 015- 0934-x (2015).
11. Jia, B., Zhong, P., Wan, X., Xu, B. & Chen, J. Decomposition-coordination model of reservoir group and ood storage basin for
real-time ood control operation. Hydrol. Res. 46, 11–25. https:// doi. org/ 10. 2166/ nh. 2013. 391 (2015).
12. Meng, X., Chang, J., Wang, X., Wang, Y. & Wang, Z. Flood control operation coupled with risk assessment for cascade reservoirs.
J. Hydrol. 572, 543–555 (2019).
13. He, Y., Xu, Q., Yang, S. & Liao, L. Reservoir ood control operation based on chaotic particle swarm optimization algorithm. Appl.
Math. Model. 38, 4480–4492 (2014).
14. Piao, S. et al. e impacts of climate change on water resources and agriculture in China. Nature 467, 43–51 (2010).
15. Immerzeel, W. W., van Beek, L. P. H. & Bierkens, M. F. P. Climate change will aect the asian water towers. Science 328, 1382–1385
(2010).
16. Geng, Y., Wei, Z., Zhang, H. & Maimaituerxun, M. Analysis and prediction of the coupling coordination relationship between
tourism and air environment: Yangtze river economic zone in china as example. Discret. Dyn. Nat. Soc. 2020, 1–15 (2020).
17. Xia, C., Zhang, A., Wang, H., Zhang, B. & Zhang, Y. Bidirectional urban ows in rapidly urbanizing metropolitan areas and their
macro and micro impacts on urban growth: A case study of the Yangtze River middle reaches megalopolis, China. Land Use Policy
82, 158–168 (2019).
18. Gridded Population of the World. Version 4 (GPWv4): Population density adjusted to match 2015 revision UN WPP country
totals, revision 11. Cent. Int. Earth Sci. Inf. Netw. https:// doi. org/ 10. 7927/ H4F47 M65 (2018).
19. Zhang, S., Jing, Z., Li, W., Yi, Y. & Zhao, Y. Study of the ood control scheduling scheme for the ree Gorges Reservoir in a
catastrophic ood. Hydrol. Process. 32, 1625–1634 (2018).
20. Zhou, C. et al. Optimal operation of cascade reservoirs for ood control of multiple areas downstream: A case study in the Upper
Yangtze River Basin. Water https:// doi. org/ 10. 3390/ w1009 1250 (2018).
21. Xia, J. & Chen, J. A new era of ood control strategies from the perspective of managing the 2020 Yangtze River ood. Sci. China
Earth Sci. 64, 1–9. https:// doi. org/ 10. 1007/ S11430- 020- 9699-8 (2020).
22. L i, Z. et al. East Asian study of tropospheric aerosols and their impact on regional clouds, precipitation, and climate (EAST-
AIRCPC). J. Geophys. Res. Atmos. 124, 13026–13054 (2019).
23. Zhang, Y. et al. Changes in ood regime of the upper Yangtze river. Front. Earth Sci. 9, 1–13 (2021).
24. Zhou, Z., Xie, S. & Zhang, R. Historic Yangtze ooding of 2020 tied to extreme Indian Ocean conditions. Proc. Natl. Acad. Sci. U.
S. A. 118, 1–7 (2021).
25. Wei, K. et al. Reections on the Catastrophic 2020 Yangtze River Basin Flooding in Southern China. Innovation 1, 100038 (2020).
26. Li, J., Yu, J. L. & Hou, Y. Flood encounter analysis of main and tributary of the upper Yangtze river based on improved set pair
situation ordering method. J. Catastrophol. 35, 85–92 (2020).
27. Chu, P., Liu, P. & Pan, H. Prospects of hydropower industry in the Yangtze River Basin: China’s green energy choice. Renew. Energy
131, 1168–1185 (2019).
28. Wu, C., Wei, Y. D., Huang, X. & Chen, B. Economic transition, spatial development and urban land use eciency in the Yangtze
River Delta, China. Habitat Int. 63, 67–78 (2017).
29. Zhamg, G., Quan, X., Yu, B. & Zhang, Y. Optimal daily operation model and algorithm for ere Gorges cascade hydropower
plants. J. Yangtze River Sci. Res. Inst. 20, 10–12 (2003).
30. Jiang, Z., Li, R., Li, A. & Ji, C. Runo forecast uncertainty considered load adjustment model of cascade hydropower stations and
its application. Energy 158, 693–708 (2018).
31. Tufegdzic, N., Frowd, R. J. & Stadlin, W. O. A Coordinated approach for real-time short term. IEEE Trans. Power Syst. 11, 1698–1704
(1996).
32. Tang, H., Wasowski, J. & Juang, C. H. Geohazards in the three Gorges Reservoir Area, China: Lessons learned from decades of
research. Eng. Geol. 261, 105267 (2019).
33. Wu, L. & Wang, Z. ree Gorges reservoir water level uctuation inuents on the stability of the slope ’ s analysis. Adv. Mater. Res.
739, 283–286 (2013).
34. Chen, Y., Hu, Z., Liu, Q. & Chen, S. Evolutionary game analysis of tripartite cooperation strategy under mixed development
environment of cascade hydropower stations. Water Resour. Manag. 34, 1951–1970 (2020).
35. Ruoting, W. ree Gorges dam sets new world record of power generation in 2020. State‑owned Assets Supervi sion and Administra
tion Commission of the State Council http:// en. sasac. gov. cn/ 2021/ 01/ 05/c_ 6354. htm (2021).
36. Kasiviswanathan, K. S., He, J., Sudheer, K. P. & Tay, J. Potential application of wavelet neural network ensemble to forecast stream-
ow for ood management. J. Hydrol. 536, 161–173 (2016).
Content courtesy of Springer Nature, terms of use apply. Rights reserved
9
Vol.:(0123456789)
Scientic Reports | (2022) 12:2822 | https://doi.org/10.1038/s41598-022-06801-8
www.nature.com/scientificreports/
37. Jiang, H. et al. Hydrological characteristic-based methodology for dividing ood seasons: an empirical analysis from China.
Environ. Earth Sci. 78, 1–9 (2019).
38. Liu, P. et al. Optimal design of seasonal ood limited water levels and its application for the ree Gorges Reservoir. J. Hydrol. 527,
1045–1053 (2015).
39. Ran, Q. et al. Evaluation of quantitative precipitation predictions by ECMWF, CMA, and UKMO for ood forecasting: Application
to two basins in China. Nat. Hazards Rev. 19, 05018003 (2018).
40. Zhou, Y., Guo, S., Chang, F. J., Liu, P. & Chen, A. B. Methodology that improves water utilization and hydropower generation
without increasing ood risk in mega cascade reservoirs. Energy 143, 785–796 (2018).
41. Zhou, Y., Guo, S., Liu, P. & Xu, C. Joint operation and dynamic control of ood limiting water levels for mixed cascade reservoir
systems. J. Hydrol. 519, 248–257 (2014).
42. Tan, Q. et al. e dynamic control bound of ood limited water level considering capacity compensation regulation and ood
spatial pattern uncertainty. Water Resour. Manag. 31, 143–158 (2017).
43. Shen, Z. et al. Deriving optimal operating rules of a multi-reservoir system considering incremental multi-agent benet allocation.
Water Resour. Manag. 32, 3629–3645 (2018).
44. Ding, W., Zhang, C., Cai, X., Li, Y. & Zhou, H. Multiobjective hedging rules for ood water conservation. Water Resour. Res. 53,
1963–1981 (2017).
45. Ding, W. et al. An analytical framework for ood water conservation considering forecast uncertainty and acceptable risk. Wate r
Resour. Res. 51, 4702–4726 (2015).
46. Feng, M. et al. Adapting reservoir operations to the nexus across water supply, power generation, and environment systems: An
explanatory tool for policy makers. J. Hydrol. 574, 257–275 (2019).
47. Liu, D., Wang, H. W., Qi, C. & Wang, J. ORECOS: An open and rational emergency command organization structure under extreme
natural disasters based on Chinas national conditions. Disaster Adv. 5, 63–73 (2012).
48. China’s Yangtze River Protection Law enters force. China Global Television Network (2021) https:// news. cgtn. com/ news/ 2021- 03-
01/ China-s- Yangt ze- River- Prote ction- Law- enters- force- YgXES iyNmo/ index. html.
49. Feng, Z., Niu, W., Tang, Z., Xu, Y. & Zhang, H. Evolutionary articial intelligence model via cooperation search algorithm and
extreme learning machine for multiple scales nonstationary hydrological time series prediction. J. Hydrol. 595, 126062 (2021).
50. Zhou, J., Zhang, H., Zhang, J. & Zeng, X. WRF model for precipitation simulation and its application in real-time ood forecasting
in the Jinshajiang River Basin. Meteorol. Atmos. Phys. 130, 635–647 (2018).
51. Jiang, Z., Wu, W., Qin, H., Hu, D. & Zhang, H. Optimization of fuzzy membership function of runo  forecasting error based on
the optimal closeness. J. Hydrol. 570, 51–61 (2019).
52. Feng, Z. et al. Monthly runo  time series prediction by variational mode decomposition and support vector machine based on
quantum-behaved particle swarm optimization. J. Hydrol. 583, 124627 (2020).
53. He, Z., Wang, C., Wang, Y., Wei, B. & Zhou, J. Dynamic programming with successive approximation and relaxation strategy for
long-term joint power generation scheduling of large-scale hydropower station group. Energy 222, 119960 (2021).
54. He, Z., Zhou, J., Xie, M., Jia, B. & Bao, Z. Study on guaranteed output constraints in the long term joint optimal scheduling for the
hydropower station group. Energy 185, 1210–1224 (2019).
55. Liu, Y. et al. Optimization of energy storage operation chart of cascade reservoirs with multi-year regulating reservoir. Energies
12, 3814 (2019).
56. Jiang, Z., Liu, P., Ji, C., Zhang, H. & Chen, Y. Ecological  ow considered multi-objective storage energy operation chart optimiza-
tion of large-scale mixed reservoirs. J. Hydrol. 577, 123949 (2019).
Acknowledgements
is work was supported by the National Natural Science Foundation of China (Nos. 51925902, 51909010)
and the Fundamental Research Funds for the Central Universities (No. DUT20RC(3)019). All data, models, or
code generated or used during the study are available from the corresponding author upon reasonable request.
Author contributions
All authors contributed extensively to the work presented in this paper. H.Z., Y.D., and L.Y. conceived of and
designed the paper. Y.D. and L.Y. performed some of the analysis and prepare the manuscript. H.Z., Y.D., and
C.Z. provided nancial support. H.Y, Z.B., Z.T., Y.W., Y.H., S.Z., M.X., J.W., C.S., Y.R., D.Z., B.W., and Y.C. con-
tributed to the real-time reservoir cooperation. All co-authors contributed to the editing of the manuscript and
to the discussion and interpretation of the results.
Competing interests
e authors declare no competing interests.
Additional information
Correspondence and requests for materials should be addressed to Y.D.orL.Y.
Reprints and permissions information is available at www.nature.com/reprints.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and
institutional aliations.
Open Access is article is licensed under a Creative Commons Attribution 4.0 International
License, which permits use, sharing, adaptation, distribution and reproduction in any medium or
format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the
Creative Commons licence, and indicate if changes were made. e images or other third party material in this
article are included in the articles Creative Commons licence, unless indicated otherwise in a credit line to the
material. If material is not included in the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from
the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
© e Author(s) 2022
Content courtesy of Springer Nature, terms of use apply. Rights reserved
1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”), for small-
scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are maintained. By
accessing, sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of use (“Terms”). For these
purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal
subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription
(to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will
apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within
ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not
otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as
detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that Users may
not:
use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access
control;
use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is
otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association unless explicitly agreed to by Springer Nature in
writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal
content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue,
royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal
content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any
other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not obligated to publish any information or
content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature
may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied
with respect to the Springer nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law,
including merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed
from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not
expressly permitted by these Terms, please contact Springer Nature at
onlineservice@springernature.com
... Analyzing floods and water scarcity together will help management communities to take the advantages in the similarities of management methods such reservoir operation to reduce the impacts (Kreibich et al. 2022). Also, the tradeoff between water supply and flood mitigation during events of the flood is rarely studied and in need to utilize the reservoirs to its full potential (Zhang et al. 2022). Thus, there is a need for a simplified modelling approach to study this tradeoff in reservoir operation. ...
... Analyzing floods and water scarcity together will help management communities to take the advantages in the similarities of management methods such reservoir operation to reduce the impacts (Kreibich et al. 2022). Also, the tradeoff between water supply and flood mitigation during events of the flood is rarely studied and in need to utilize the reservoirs to its full potential (Zhang et al. 2022). Thus, there is a need for a simplified modelling approach to study this tradeoff in reservoir operation. ...
... In the reservoir impact analysis of this study, the results of the hydrological frequency analysis considering reservoir impacts have obtained better simulations (Figures 8, 9) and the change-point results correspond to the time of completion of large reservoirs in the basin. These results demonstrated that the hydrological series in the basin is mainly influenced by the operation of large reservoirs in the Yangtze River basin Li H. et al., 2020;Li et al., 2022;Zhang et al., 2022). ...
Article
Full-text available
When large reservoirs are built and put into operation, the downstream hydrological processes will be altered significantly, and ecology and agricultural irrigation water of the basin will be affected to some extent. The reservoir index (RI) and the sediment trapping efficiency (TE) of reservoirs are defined to quantify the reservoir impacts on the water flow and sediment by considering the static storage capacity. However, the regulating effect of reservoirs on hydrological variables is not only related to static storage capacity, but also to dynamic reservoir operation. Thus, in this paper, a general rainfall-reservoir index (GRRI) is developed by coupling reservoir regulation indicator (RR, including RI and TE) and effective rainfall affecting the dynamic operation of reservoirs, and the GRRI is used as the covariate to carry out the nonstationary frequency analysis of flood (Q) and annual sediment load (S) at Gaochang (GC) station in Min River, Wulong (WL) station in Wu River, Ankang (AK), Huangjiagang (HJG) and Huangzhuang (HZ) station in Han River, and Cuntan (CT) station on the main stream of the upper Yangtze River. It is found that Q and S at six stations have obvious changes induced by reservoirs, the mean of Q decreases by 22.8%–60.6%, and S drops by 47.7%–89.5% after the change-point of time series. The nonstationary probability distribution models with GRRI as the covariate have better fitting effects than nonstationary models with RR as the covariate. With the incorporation of the impacts of effective rainfall, the GRRI can more accurately capture the occurrence of nonstationarity in the downstream hydrological frequency. These results might be helpful for exploring the impact mechanism of the reservoir regulation on the downstream hydrological variables as well as ecological management of basin.
... Previous studies Zhang et al., 2022) have shown that large cascade reservoirs retain flooding, thereby affecting the runoff process. For example, the MRI value of the Yichang Station changed from 0.001 in 2005 to 0.283 in 2006, which indicates that the flood control capacity changed greatly after construction. ...
Article
Full-text available
Currently, there is a lack of investigating moisture sources for precipitation over the upstream catchment of the Three Gorges Dam (UCTGD), the world’s largest dam. Using the dynamical recycling model (DRM), trajectory frequency method (TFM), and the Climate Forecast System Reanalysis (CFSR), this study quantifies moisture sources and transport paths for UCTGD summer precipitation from 1980 to 2009 based on two categories of sources: region-specific and source-direction. Overall, the land and oceanic sources contribute roughly 63% and 37%, respectively, of the moisture to UCTGD summer precipitation. UCTGD and the Indian Ocean are the most important land and oceanic sources, respectively, in which the southern Indian Ocean with over 10% of moisture contribution was overlooked previously. Under the influence of the Asian monsoon and prevailing westerlies, the land contribution decreases to 57.3% in June, then gradually increases to 68.8%. It is found that for drought years with enhanced southwest monsoon, there is a weakening of the moisture contribution from the C-shaped belt along the Arabian Sea, South Asia, and UCTGD, and vice versa. TFM results show three main moisture transport paths and highlight the importance of moisture from the southwest. Comparison analysis indicates that, generally, sink regions are more affected by land evaporation with their locations more interior to the center of the mainland. Furthermore, correlations between moisture contributions and indices of general circulation and sea surface temperature are investigated, suggesting that these indices affect precipitation by influencing moisture contributions of the subregions. All of these are useful for comprehending the causes of summer UCTGD precipitation. Significance Statement Quantitative research on the moisture sources of summer precipitation has been implemented for the upstream catchment of the Three Gorges Dam (UCTGD), which is of particular hydrological significance but has not been investigated previously. The dynamical recycling model (DRM)–trajectory frequency method (TFM) approach is used to quantify and interpret the results of the moisture sources both in different specific subregions and directions, which produce more meaningful results than a single method for the areal division of moisture sources. Furthermore, antecedent indices that significantly influence the following moisture contributions of the subregions and then summer UCTGD precipitation are studied in terms of large-scale general circulation indices, which would help our understanding of precipitation forecast for UCTGD.
Article
Full-text available
Global warming will significantly affect the frequency and intensity of extreme precipitation and further affect the spatio-temporal pattern of disaster-causing risk of extreme precipitation. This study analyzes the spatio-temporal trends of extreme precipitation and projects its disaster-causing risk under different climate scenarios in the Yangtze River Basin from 2021 to 2100. The results indicate that the extreme precipitation in the Yangtze River Basin shows an increasing trend in the future. Annual precipitation (PRCPTOT) increases by 33.05–42.56% under five scenarios compared with the historical period. The future change in heavy precipitation (R95p) also shows a significant increase, but heavy rain days (R50) and 5-day maximum precipitation (RX5day) decrease. The disaster-causing risk of extreme precipitation in the Yangtze River Basin is mainly Levels III and IV, accounting for 57.23–65.99% of the total basin area. The area with Level V is mainly distributed in the Poyang Lake Basin and the lower main stream of the Yangtze River. Moreover, the changes in disaster-causing risk of extreme precipitation are mainly manifested in the decrease of areas with low risk (Levels I and II) and the increase of areas with medium risk (Levels III and IV) in different periods. HIGHLIGHTS An assessment model of the disaster-causing risk of extreme precipitation was established.; All indices of extreme precipitation present a fluctuating upward trend in the future.; The distribution of disaster-causing risk in the Yangtze River Basin is mainly in Levels III and IV.; The spatio-temporal pattern of risk levels is attributed to the changes in extreme precipitation.; Poyang Lake Basin has the highest risk in the future.;
Article
Full-text available
River flooding affects more people worldwide than other natural hazards. Thus, analysis of the changes in flood regime caused by global warming and increasing anthropogenic activities will help us make adaptive plans for future flood management. The nonstationary flood behavior in the upper Yangtze River was examined comprehensively in terms of trend, change point, and periodicity with co-usage of different methods. Results show that there are decreasing tendencies in the corresponding series of annual maximum flood peak flow and flood volume in four out of six control stations, except Pingshan and Wulong stations in the Jinsha River and the Wu River, respectively, and the flood peak occurrence time appears earlier mostly. The uniformity of flood process increases in four main tributaries, while it decreases in mainstream of the Yangtze River (Yichang and Pingshan stations). The rates of both rising limb and recession limb of all the typical flood process flowing through the six stations were analyzed. 77.8% of the rates of rising limb decrease, while 61.1% of the rates of recession limb increase, which is almost consistent with the variation reflected by the uniformity. The change points of most evaluation indicators happened in 1970s–1990s. The first main periodicity of evaluation indicators in Yichang is about 45 years, while that of other stations is about 20 years. Invalidity of stationarity in the flood series can be attributed to the intensified construction on major water conservancy projects, changes of underlying surface, and influences of climatic variables. The contributions of both climatic control and the Three Gorges Dam (TGD) to the variation of the annual flood peak in Yichang station were further quantitatively evaluated, which has verified that the construction of the TGD has played a positive role in peak-flood clipping.
Article
Full-text available
Significance Summer rainfall along the Yangtze River in 2020 was the heaviest since 1961, with devastating socioeconomic impacts. While official forecasts based on tropical Pacific state failed, we show that dynamic models, when initialized with ocean observations globally, succeed in predicting the extreme rainfall. Slowly propagating oceanic Rossby waves in the South Indian Ocean are the source of predictability, which are in turn tied to the record-breaking Indian Ocean Dipole in late 2019. The identification of antecedent subsurface conditions of the Indian Ocean as a key predictor represents an important conceptual advance in Asian summer monsoon dynamics, helping improve disaster preparation that saves lives and properties.
Article
Full-text available
Over recent decades, concern has grown regarding the effects of climate change and artificial river projects on the variability of river floods. Specifically, it has been demonstrated that the Mississippi River flood hazard has been amplified by river engineering. In contrast, the world’s largest reservoir group with the Three Gorges Reservoir at its core has been built along the upper reaches of the Yangtze River, but the question of whether there has been a positive effect on flood control is worthy of discussion. Here, we revisit nine paleofloods from the ancient stone inscriptions for the first time and show that while annual peak discharge in the upper reaches of the Yangtze River is dominated by sunspot numbers and the North Atlantic Oscillation, the magnitude of flooding has been decreased by the reservoir group, which diminished flood hazard through reversing or strengthening the direction of climate control on the flood.
Article
Full-text available
The rock and soil on the shore of the bank are unsteady and slide in a poor environment, affecting the water body in the river channel and forming landslide-generated tsunamis. This directly impacts the navigation of vessels in the river. In this study, the river course and sailing ships in the Wanzhou section of the Three Gorges Reservoir area were taken as the research objects. Through a physical model test with a large scale ratio, the variation of the water level at the monitoring points in the channel was determined, and the variation law of the water level in the whole channel was derived and converted into a prototype through the scale ratio. A model of the ship’s manoeuvring motion was established, and the ship’s manoeuvring motion characteristics in still water were verified. The correlations between the maximum roll angle and the navigation position, sailing speed, and rudder angle were investigated in detail. A safety risk response theory of navigation in the area of landslide-generated tsunamis was proposed, and a scientific basis was provided for the safe navigation of ships in the Three Gorges Reservoir area.
Article
Full-text available
In July 2020, a big basin flood occurred in the Yangtze River's middle and lower reaches due to persistent heavy rainfall. We carefully compare this event with the rainfall-induced big flood in 2008. The influencing factors of floods were analyzed. The measures and important issues in future are suggested in reducing the flood risk. In summary, despite the record-breaking rainfall and flood in southern China in 2020, the magnitude of the disaster was much lower than in 1954 or 1998. The response to this disaster has provided a reference for both developed and developing countries to cope with the more extreme consequences of climate change.
Article
Full-text available
Joint operation of cascade hydropower stations maximizes the utilization rate of water resources of a river basin and the benefit of the entire river system. However, under mixed development environment of cascade hydropower stations, i.e. simultaneous existence of operating and under-construction hydropower stations, the difficulty of the joint operation is increased. Moreover, this difficulty is further enhanced due to the cooperation among multiple stakeholders and uncertain evolutionary characteristic of stakeholder’s strategy. To handle these problems, this paper takes two upstream operating hydropower stations and one downstream hydropower station under construction as research objects, where one of upstream hydropower station locates in a tributary. First, all possible strategy combinations among these three stakeholders are comprehensively analyzed, and the benefit of each stakeholder strategy under each strategy combination is respectively calculated. A tripartite evolutionary game model is then established. It aims at exploring directions and conditions of cooperative and non-cooperative strategies evolving into stable states. Finally, the exploration results find that the strategy evolution of a stakeholder relies on its partners’ behaviors and net benefit of self-behavior; the tripartite cooperation will eventually form four stable states; the conditions for cooperation between upstream and downstream hydropower stations are that the compensation paid by downstream hydropower station is greater than the loss of upstream power generation and downstream project benefit is greater than the sum of compensation expenditure and risk benefit.
Article
Full-text available
The results show that the comprehensive development degree (CDD) of the tourism-air environment system mainly maintains stable with fluctuation and the gap among different reaches in the Zone is declining; the coupling coordination degree’s (CCD) tendency in most regions remains similar as in the previous decade. The results illustrate that the method combing information entropy weight and the technique for order preference by similarity to an ideal solution (IEW-TOPSIS), coupling coordination degree model (CCDM), and gray GM (1, 1) prediction model is effective in evaluating the coupling coordination relationship between the subsystems of tourism and air environment and in proposing specific countermeasures for tourism development and air environment governance.
Article
Reliable and stable hydrological prediction plays a vitally crucial role in the scientific operation of water resources system. As a famous artificial intelligence method for hydrological forecasting, extreme learning machine (ELM) has the virtues of fast training efficiency and strong generalization performance but is easily trapped into local optima because the preset computation parameters often remain unchanged in the learning process. In order to overcome this shortcoming, a practical evolutionary artificial intelligence model is developed for multiple scales nonstationary hydrological time series prediction. In the proposed method, an emerging evolutionary method called cooperation search algorithm (CSA) is used to search for the optimal input-hidden weights and hidden biases of the ELM model for the first time. The proposed method is used to forecast the runoff time series of three real-world hydrological stations in China. The experimental results show that the CSA approach can effectively determine satisfying network parameters of the ELM model, while our method can produce better results than the traditional ELM method in terms of all the performance evaluation indexes. Taking 1-step-ahead runoff forecasting at station B as an example, our method betters the ELM method with 15.69% and 10.52% improvements in both root mean squared error and mean absolute percentage error at the testing phase. Thus, a novel multiscale nonstationary hydrological prediction tool is developed to support the decision-making of water resource system.
Article
The joint optimal operation of large-scale hydropower station group (LHSG) is faced with the higher dimension than that of cascade hydropower station, the demand for the efficient optimization techniques of the above problem is urgent. Integrating the characteristics of problem into optimization techniques is an effective way. Therefore, based on some previous research results, the approximate concavity and monotonicity characteristics of power generation utility function of dynamic programming with successive approximation (DPSA) in each stage is analyzed. Then, an improved DPSA with relaxation strategy (named DPSARS) based on the above mathematical derivations is proposed to solve the long-term joint power generation scheduling (LJPGS) of LHSG. Compared with DPSA, the time complexity exhibits quadratic increase with the number of discrete states, while DPSARS only exhibits linear increase. Then, in order to further test the convergence accuracy and efficiency of the proposed DPSARS, the model of the LJPGS problem of LHSG, composed of 61 hydropower stations in the upper reaches of the Yangtze River, is established. The experimental results show that DPSARS represents its competitive performance in solving the LJPGS problem of LHSG compared with other methods.
Article
Flood control of the Yangtze River is an important part of China’s national water security. In July 2020, due to continuous heavy rainfall, the water levels along the middle-lower reaches of the Yangtze River and major lakes constantly exceeded the warning levels, in which Taihu Lake exceeded its highest safety water level and some stations of Poyang Lake reached their highest water levels in its history. In August 2020, another huge flood occurred in the Minjiang River and the Jialing River in the upper Yangtze River, and some areas of Chongqing Municipality and other cities along the rivers were inundated, resulting in great pressure on flood control and high disaster losses. The 2020 Yangtze River flood has received extensive media coverage and raised concerns on the roles of the Three Gorges Dam and other large reservoirs in flood control. Here we analyze the changes in the pattern of the Yangtze River flood control by comparing the strategies to tackle the three heavy floods occurring in 1954, 1998, and 2020. We propose that the overall strategy of the Yangtze River flood control in the new era should adhere to the principle of “Integration of storage and drainage over the entire Yangtze River Basin, with draining floods downstream as the first priority” by using both engineering and non-engineering measures. On the basis of embankments, the engineering measures should use the Three Gorges Dam and other large reservoirs as the major regulatory means, promote the construction of key flood detention areas, keep the floodways clear, and maintain the ecosystem services of wetlands and shoals. In terms of non-engineering measures, we should strengthen adaptive flood risk management under climate change, standardize the use of lands in flood detention areas, give space to floods, and promote the implementation of flood risk maps and flood insurance policies. The ultimate goal of this new flood control system is to enhance the adaptability to frequent floods and increase the resilience to extreme flood disasters.