From China’s Heavy Precipitation in 2020 to a “Glocal” Hydrometeorological Solution for Flood Risk Prediction

Wu, Huan; Li, Yongming; Schumann, Guy; Alfieri, Lorenzo; Chen, Yongqin David; Xu, Hui; Wu, Zhiyong; Lu, Hong; Hu, Ya-Min; Zhu, Qing; Huang, Zhijun; Chen, Weitian; Hu, Ya

doi:10.1007/s00376-020-0260-y

Cited by 13 publications

(9 citation statements)

References 13 publications

(11 reference statements)

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“…Therefore, the primary objective of this study is to provide an improved understanding of the ENSO effect on basin-scale flood events. An improved understanding of simultaneous and lagged responses of basin-scale river flows/floods to ENSO, in addition to the connections between precipitation and ENSO, could greatly help our efforts of exploring monthly/seasonal flood predictability (e.g., Chiew & McMahon, 2002;Lee et al, 2018a), thus allowing for better preparedness and management of flood risks, such as more appropriately preallocating and prioritizing mitigation resources (Wu et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Exploring the ENSO Impact on Basin‐Scale Floods Using Hydrological Simulations and TRMM Precipitation

Yan

et al. 2020

Geophysical Research Letters

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El Niño-Southern Oscillation (ENSO) is an important driver of interannual climate variability with increasing attention for its impacts on water and flood management. The impact of ENSO on basin-scale floods during the TRMM period (1998-2013) is examined by using the streamflow outputs from the Dominant river Routing Integrated with VIC Environment model (DRIVE). Significant simultaneous correlations between flood indices and Niño 3.4 appear in many flood-prone river basins during peak flood months across both the tropics and midlatitudes especially for flood frequency and flood duration. Gauged by significant lag-correlations between floods and Niño 3.4, significant ENSO-leading-floods relations are found as well in many river basins in South America, south and southeastern Asia, and northern Africa. These ENSO-floods-relations can greatly enhance understanding of physical mechanisms relevant to the ENSO impact and may also improve the skills of basin-scale monthly-to-seasonal flood forecast, thus allowing for better preparedness and management of flood risks. Plain Language Summary As a naturally occurring phenomenon involving quasi-periodic variation of air pressure and sea surface temperature, the ENSO impacts global floods through its modulation of atmospheric circulations, weather, and precipitation. Previous studies on ENSO-floodsrelations are often limited in supporting practical flood disaster preparedness and risk analyses because of the lack of a "complete" reconstruction of past flood events likely due to scattered gauge-based streamflow data and/or coarse-resolution retrospective simulations. Here flood events at model grids and for individual river basins are identified using the outputs from the Dominant river Routing Integrated with VIC Environment model (DRIVE) with a high spatial resolution (0.125°× 0.125°) driven by the state-of-the-art satellite precipitation product TMPA. Simultaneous and lagged responses of basin-scale floods to ENSO are explored to provide an improved knowledge of the ENSO effect on global floods and a guidance for flood disaster planning and risk management for the regions consistently impacted by ENSO.

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Section: Introductionmentioning

confidence: 99%

Exploring the ENSO Impact on Basin‐Scale Floods Using Hydrological Simulations and TRMM Precipitation

Yan

et al. 2020

Geophysical Research Letters

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“…To be part of the GHS-F applications across large to local scales (H. Wu et al, 2021), a balance between model accuracy and computing efficiency has to be taken into account in the DRIVE-Urban model development. Two more complicated approaches, that is, the full shallow water equations based inundation scheme proposed by Hou et al (2013), and the inertial scheme of the simplified shallow water equations proposed by Bates et al (2010), have been implemented as well within the current DRIVE-Urban model version as two other options when necessary.…”

Section: Discussionmentioning

confidence: 99%

“…To be part of the GHS‐F applications across large to local scales (H. Wu et al., 2021), a balance between model accuracy and computing efficiency has to be taken into account in the DRIVE‐Urban model development. Two more complicated approaches, that is, the full shallow water equations based inundation scheme proposed by Hou et al.…”

Section: Discussionmentioning

confidence: 99%

A Coupled River Basin‐Urban Hydrological Model (DRIVE‐Urban) for Real‐Time Urban Flood Modeling

Chen

Kimball

et al. 2022

Water Resources Research

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Reliable urban flood modeling is highly demanded in emergency response, risk management, and urban planning related to urban flooding. In this paper, the Storm Water Management Model (SWMM) is adapted to simulate urban rainfall‐runoff and pipe drainage processes within the Dominant river tracing‐Routing Integrated with VIC Environment (DRIVE) model which accounts for natural river basin runoff generation and routing processes. The integrated DRIVE‐SWMM model (referred to as DRIVE‐Urban) allows to explicitly delineate the mass‐energy interactions between urban drainage system (e.g., pipes and dikes) and river networks. This presents a further step model development for accurate urban flooding prediction which is lacking in existing urban flood models and traditional hydrological models. The validity of the DRIVE‐Urban model is evaluated for three case studies in Haikou City, China, with camera observations of street inundation during typhoon landfalls and heavy rainfall events. The results show that the DRIVE‐Urban model successfully captures 62%, 69%, and 77% of the total observed inundated road‐sections for the three cases respectively. The third case study with severe flooding situation shows that the DRIVE‐Urban performance is further improved when given reliable river and tidal level information, indicating the importance of integrating river‐basin with urban hydrological and hydraulic modeling.

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“…For example, floods in 1998 caused about $36 billions of total losses and over 3000 flood-related fatalities (NCC 1998). Heavy precipitation in 2020 caused flash flooding, urban flooding, and landslides particularly along the Yangtze River basin (Wu et al 2021). Such catastrophes are likely to become more frequent.…”

Section: Introductionmentioning

confidence: 99%

Physical processes of summer extreme rainfall interannual variability in eastern China: Part I—observational analysis

Tian

Dong

et al. 2022

Clim Dyn

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Extreme precipitation can have catastrophic effects in China by triggering floods, landslides, and other natural disasters. We measure extreme precipitation over eastern China by the maximum of five-day precipitation amount (Rx5day) in June, July, and August (JJA), which contributes more than 20% of the climate mean of JJA regional total precipitation. Based on the empirical orthogonal teleconnection (EOT) method, this work identifies four dominant regions of observed Rx5day interannual variability in eastern China: north-eastern China (EOT1), the southern lower reaches of the Yangtze valley (EOT2), southern China (EOT3) and the northern lower reaches of the Yangtze valley (EOT4). EOT1 extreme precipitation is related to a strong East Asian Summer Monsoon (EASM), a weak monsoon front and a northward displaced upper-tropospheric westerly jet. EOT2 and EOT4 extreme precipitation are related to an enhanced and stable monsoon front and a strong western North Pacific subtropical high (WNPSH). The WNPSH associated with EOT4 is stronger than that associated with EOT2, which pushes the monsoon front further north. EOT3 represents extreme precipitation that is related to anomalous southerlies around the western ridge of the WNPSH. The southerlies transport warm and moist air to southern China and increase precipitation there. The four key regions and the related mechanisms are not sensitive to the EOT technique, as the EOT-based extreme precipitation patterns and circulation anomalies are confirmed using Self-Organising Maps (SOMs).

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From China’s Heavy Precipitation in 2020 to a “Glocal” Hydrometeorological Solution for Flood Risk Prediction

Cited by 13 publications

References 13 publications

Exploring the ENSO Impact on Basin‐Scale Floods Using Hydrological Simulations and TRMM Precipitation

Exploring the ENSO Impact on Basin‐Scale Floods Using Hydrological Simulations and TRMM Precipitation

A Coupled River Basin‐Urban Hydrological Model (DRIVE‐Urban) for Real‐Time Urban Flood Modeling

Physical processes of summer extreme rainfall interannual variability in eastern China: Part I—observational analysis

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