Flood risk management in the Yangtze River basin —Comparison of 1998 and 2020 events

Jia, Huicong; Chen, Fang; Pan, Di; Du, Enyu; Wang, Lei; Wang, Ning; Yang, Aqiang

doi:10.1016/j.ijdrr.2021.102724

Cited by 61 publications

(23 citation statements)

References 35 publications

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“…For the YRB (Fig. 10d), daily streamflow detected at the Datong hydrological station reached its 90th percentile in 29 June and eventually peaked in 13 July, with a maximum value of 7.2×10 9 m 3 d −1 , which is in line with the findings in Jia et al (2021). Accordingly, the series of NDFPI reached its 90th percentile in 18 June with a value of 0.58.…”

Section: Monitoring Severe Flood Events Based On the Proposed Ndfpi I...supporting

confidence: 85%

“…For example, in the year 2020, the YRB experienced one of the most extreme flood events on record. According to data from the Ministry of Emergency Management of the People's Republic of China, a total of 38.173 million people were affected, and 27 000 houses collapsed due to the 2020 flood, with 56 deaths or disappearances and a great economic loss of USD 27.68 billion (Jia et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Monitoring the extreme flood events in the Yangtze River basin based on GRACE and GRACE-FO satellite data

Xie

Xu²,

Yu³

et al. 2022

Hydrol. Earth Syst. Sci.

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Abstract. Gravity Recovery and Climate Experiment (GRACE) and its successor GRACE Follow-on (GRACE-FO) satellite provide terrestrial water storage anomaly (TWSA) estimates globally that can be used to monitor flood in various regions at monthly intervals. However, the coarse temporal resolution of GRACE and GRACE-FO satellite data has been limiting their applications at finer temporal scales. In this study, TWSA estimates have been reconstructed and then temporally downscaled into daily values based on three different learning-based models, namely a multi-layer perceptron (MLP) model, a long-short term memory (LSTM) model and a multiple linear regression (MLR) model. Furthermore, a new index incorporating temporally downscaled TWSA estimates combined with daily average precipitation anomalies is proposed to monitor the severe flood events at sub-monthly timescales for the Yangtze River basin (YRB), China. The results indicated that (1) the MLP model shows the best performance in reconstructing the monthly TWSA with root mean square error (RMSE) = 10.9 mm per month and Nash–Sutcliffe efficiency (NSE) = 0.89 during the validation period; (2) the MLP model can be useful in temporally downscaling monthly TWSA estimates into daily values; (3) the proposed normalized daily flood potential index (NDFPI) facilitates robust and reliable characterization of severe flood events at sub-monthly timescales; (4) the flood events can be monitored by the proposed NDFPI earlier than traditional streamflow observations with respect to the YRB and its individual subbasins. All these findings can provide new opportunities for applying GRACE and GRACE-FO satellite data to investigations of sub-monthly signals and have important implications for flood hazard prevention and mitigation in the study region.

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Section: Monitoring Severe Flood Events Based On the Proposed Ndfpi I...supporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Monitoring the extreme flood events in the Yangtze River basin based on GRACE and GRACE-FO satellite data

Xie

Xu²,

Yu³

et al. 2022

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…About three million people were forced to temporarily relocate and 39,00 km2 of cropland was affected. The economic loss was 110 billion Yuan (17 billion US$) (Jia et al, 2022). This event, as with other severe floods, followed a winter El Nino.…”

Section: Flood After Completion Of the Three Gorges Dammentioning

confidence: 93%

Severe flood probability on the middle Changjiang (Yangtze River) after completion of the Three Gorges Dam

Shankman

Lai

2022

Front. Earth Sci.

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A major justification for building the Three Gorges Dam on the Changjiang is flood control. The dam can reduce peak discharge during severe floods. These floods, however, cannot be prevented by operation of the Three Gorges Dam alone. During the most severe floods abnormally high rainfall occurs throughout the Changjiang basin. The Three Gorges Dam can only affect discharge from the upper basin. Large tributaries on the middle Changjiang are unaffected by the dam. The cumulative impact of high discharge from large tributaries on the middle Changjiang increase flood severity with distance downstream. Also, Changjiang-lake interaction is affected by decreasing volume of Poyang and Dongting Lakes that occurred during the past few decades. These are the largest freshwater lakes in China. As a result of reduced floodwater storage capacity during summer high discharge periods, tributaries flow into the lakes with a higher base level than previously occurred. Instead of Changjiang back flowing into the lakes as previously expected during major floods, high Changjiang discharge occurs at the same time as high tributary discharge that increases peak river stage.

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“…In the 21st century, adapting to climate change and coastal flooding is a critical challenge for coastal cities. The human response to the impacts of flooding largely depends on the allocation of urban facilities and managers' planning for future urban development (Hunt and Watkiss, 2011;Jia et al, 2022). Shanghai is considered one of the most protected Chinese cities in terms of flood protection, yet the expected annual disruption (EAD) / GDP ratio (EAD is the direct damage to buildings and vehicles) is as much as 5 times that in New York (Aerts et al, 2014).…”

Section: Recommendations For Strategies and Policies For Urban Adapta...mentioning

confidence: 99%

Multi-scenario urban flood risk assessment by integrating future land use change models and hydrodynamic models

Sun

Fang

Dang

et al. 2022

Nat. Hazards Earth Syst. Sci.

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Abstract. Urbanization and climate change are critical challenges in the 21st century. Flooding by extreme weather events and human activities can lead to catastrophic impacts in fast-urbanizing areas. However, high uncertainty in climate change and future urban growth limit the ability of cities to adapt to flood risk. This study presents a multi-scenario risk assessment method that couples a future land use simulation (FLUS) model and floodplain inundation model (LISFLOOD-FP) to simulate and evaluate the impacts of future urban growth scenarios with flooding under climate change (two representative concentration pathways (RCP2.6 and RCP8.5)). By taking the coastal city of Shanghai as an example, we then quantify the role of urban planning policies in future urban development to compare urban development under multiple policy scenarios (business as usual, growth as planned, growth as eco-constraints). Geospatial databases related to anthropogenic flood protection facilities, land subsidence and storm surge are developed and used as inputs to the LISFLOOD-FP model to estimate flood risk under various urbanization and climate change scenarios. The results show that urban growth under the three scenario models manifests significant differences in expansion trajectories, influenced by key factors such as infrastructure development and policy constraints. Comparing the urban inundation results for the RCP2.6 and RCP8.5 scenarios, the urban inundation area under the growth-as-eco-constraints scenario is less than that under the business-as-usual scenario but more than that under the growth-as-planned scenario. We also find that urbanization tends to expand more towards flood-prone areas under the restriction of ecological environment protection. The increasing flood risk information determined by model simulations helps us to understand the spatial distribution of future flood-prone urban areas and promote the re-formulation of urban planning in high-risk locations.

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Flood risk management in the Yangtze River basin —Comparison of 1998 and 2020 events

Cited by 61 publications

References 35 publications

Monitoring the extreme flood events in the Yangtze River basin based on GRACE and GRACE-FO satellite data

Monitoring the extreme flood events in the Yangtze River basin based on GRACE and GRACE-FO satellite data

Severe flood probability on the middle Changjiang (Yangtze River) after completion of the Three Gorges Dam

Multi-scenario urban flood risk assessment by integrating future land use change models and hydrodynamic models

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