
1.南方海洋科学与工程广东省实验室(珠海),广东 珠海 519082
2.中山大学水资源与环境研究中心,广东 广州 510275
3.广东省华南地区水安全调控工程技术研究中心,广东 广州 510275
4.中电建生态环境集团有限公司,广东 深圳 518101
Received:08 January 2026,
Revised:2026-02-05,
Accepted:09 February 2026,
Online First:01 April 2026,
Published:25 September 2026
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李妙琳,涂新军,李若琰,等.极端气候条件下滨海城市内涝损失评估[J].人民珠江,2026,47(9):78-88.
LI Miaolin,TU Xinjun,LI Ruoyan,et al.Assessment of Waterlogging Losses in Coastal Cities under Extreme Climate Conditions[J].PEARL RIVER,2026,47(09):78-88.
李妙琳,涂新军,李若琰,等.极端气候条件下滨海城市内涝损失评估[J].人民珠江,2026,47(9):78-88. DOI: 10.3969/j.issn.1001-9235.2026.09.008.
LI Miaolin,TU Xinjun,LI Ruoyan,et al.Assessment of Waterlogging Losses in Coastal Cities under Extreme Climate Conditions[J].PEARL RIVER,2026,47(09):78-88. DOI: 10.3969/j.issn.1001-9235.2026.09.008.
快速城市化过程中,内涝及带来的灾损问题是城市安全面临的重要挑战。以粤港澳大湾区深圳西部为典型研究区,基于城市内涝一二维耦合模型,模拟了重现期2、5、10、20、50、100 a的设计暴雨、水库泄洪及深隧工程排涝等多情景多工况的内涝淹没过程。结合城市土地利用分类,以及淹没过程中不同土地利用上覆建筑物、车辆等资产类型,通过建立多类型淹没水深-资产损失曲线,开展了较为精细化土地利用类型的资产损失评估。结果表明,设计暴雨重现期从2 a增加到100 a,受灾范围显著加大,灾损程度明显加剧,内涝淹没的受灾面积、资产损失分别由3.98 km
2
增加到6.75 km
2
、2.55亿元增加到9.12亿元。淹没水深以小于0.5 m为主,占比为54.1%~64.7%;淹没的土地利用类型主要为道路,占比90.2%~91.5%。灾损占比较大主要为住宅用地和车辆,分别为25.8%~35.2%和18.0%~33.7%。铁岗水库泄洪影响下受灾面积和资产损失分别增加了6.1%和5.6%,深隧工程排涝的资产损失减少了21.0%。研究成果为多情境多工况下的滨海城市内涝损失评估和当地洪涝防灾减灾提供了科学依据。
Urban waterlogging occurs when surface water cannot be drained in a timely manner due to heavy rainfall. This issue not only disrupts
residents' travel but also causes significant economic losses. With rapid urbanization
waterlogging and its associated disaster impacts pose a great challenge to urban safety. The assessment of socio-economic losses caused by urban waterlogging often requires detailed classification of urban land use in the inundated area. Shenzhen
as one of the core cities in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA)
is densely populated and economically developed. Under extreme climatic conditions
urban waterlogging has become a common issue. This paper takes the western part of Shenzhen city as a typical study area and simulates waterlogging inundation processes under multiple scenarios
including design rainstorms with return periods of 2a
5a
10a
20a
50a and 100a
and multiple engineering situations such as reservoir flood discharge
and deep tunnel drainage. A one-dimensional (1D) and two-dimensional (2D) coupled model of urban waterlogging was used for these simulations. By classifying urban land use and assets such as buildings and cars according to different land use types during the inundation processes
this study conducted a refined asset loss assessment by establishing multiple types of inundation depth-asset loss curves. The results demonstrate that as the design return period of rainstorm increases from 2a to 100a
the disaster-affected area significantly expands from 3.98 km
2
to 6.75 km
2
and asset losses dramatically increase from 255-million-yuan to 912-million-yuan
Inundation depths are primarily less than 0.5 m accounting for 54.1% -64.7% of the total area affected. Roads make up the majority of the inundation land use types
accounting for 90.2% -91.5%. Asset losses are mainly concentrated in residential land and vehicles
accounting for 25.8%-35.2% and 18.0%-33.7%
respectively. Furthermore
the study evaluates the impact of water engineering plans: the inundated area and asset losses increase by 6.1% and 5.6%
respectively
under reservoir flood discharge scenarios
while asset losses decrease by 21.0% when considering deep tunnel drainage projects. These findings provide a scientific basis for assessing waterlogging losses and implementing local flood prevention and mitigation strategies in coastal cities under multiple extreme climate conditions and engineering plans.
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