Articles | Volume 28, issue 23
https://doi.org/10.5194/hess-28-5229-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-5229-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Determining the threshold of issuing flash flood warnings based on people's response process simulation
Ruikang Zhang
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, China
Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan, China
Bureau of Hydrology, Changjiang Water Resources Commission, Wuhan, China
Dedi Liu
CORRESPONDING AUTHOR
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, China
Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan, China
Department of Earth Science, University of the Western Cape, Robert Sobukwe Road, Bellville 7535, South Africa
Lihua Xiong
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, China
Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan, China
Jie Chen
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, China
Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan, China
Hua Chen
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, China
Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan, China
Jiabo Yin
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, China
Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan, China
Related authors
No articles found.
Jiaoyang Wang, Dedi Liu, Shenglian Guo, Lihua Xiong, Pan Liu, Hua Chen, Jie Chen, Jiabo Yin, and Yuling Zhang
Hydrol. Earth Syst. Sci., 29, 3315–3339, https://doi.org/10.5194/hess-29-3315-2025, https://doi.org/10.5194/hess-29-3315-2025, 2025
Short summary
Short summary
The unclear feedback loops of water supply–hydropower generation–environmental conservation (SHE) nexuses with inter-basin water diversion projects (IWDPs) increase the uncertainty in the rational scheduling of water resources for water receiving and water donation areas. To address the different impacts of IWDPs on dynamic SHE nexuses and explore synergies, a framework is proposed to identify these effects across the different temporal and spatial scales in a reservoir group.
Jiayu Zhang, Dedi Liu, Jiaoyang Wang, Feng Yue, Hanxu Liang, Zhengbo Peng, and Wei Guan
EGUsphere, https://doi.org/10.5194/egusphere-2025-2734, https://doi.org/10.5194/egusphere-2025-2734, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
Water use is often estimated with coarse data that overlook spatial heterogeneity, limiting effective water planning. This study proposes a framework to simulate water use at multiple spatial scales across China, combining a grid-based approach and uncertainty analysis. It finds that both the model structure and spatial scale affect. The framework reveals detailed patterns in water use and can guide smarter water resources management.
Chao Ma, Weifeng Hao, Qing Cheng, Fan Ye, Ying Qu, Jiabo Yin, Fang Xu, Haojian Wu, and Fei Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-79, https://doi.org/10.5194/essd-2025-79, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
Antarctic sea ice albedo is a key factor influencing the energy balance of the cryosphere. Here we present a daily 1 km shortwave albedo product for Antarctic sea ice from 2012 to 2021, based on VIIRS reflectance data. Additionally, we reconstructed the albedo for missing pixels due to cloud cover. This dataset can be used to assess changes in Antarctic sea ice, radiation budget, and the strength of sea ice albedo feedback mechanisms, as well as their potential interconnections.
Kun Xie, Lu Li, Hua Chen, Stephanie Mayer, Andreas Dobler, Chong-Yu Xu, and Ozan Mert Göktürk
Hydrol. Earth Syst. Sci., 29, 2133–2152, https://doi.org/10.5194/hess-29-2133-2025, https://doi.org/10.5194/hess-29-2133-2025, 2025
Short summary
Short summary
We compared hourly and daily extreme precipitation across Norway from HARMONIE Climate models at convection-permitting 3 km (HCLIM3) and 12 km (HCLIM12) resolutions. HCLIM3 more accurately captures the extremes in most regions and seasons (except in summer). Its advantages are more pronounced for hourly extremes than for daily extremes. The results highlight the value of convection-permitting models in improving extreme-precipitation predictions and in helping the local society brace for extreme weather.
Qiumei Ma, Chengyu Xie, Zheng Duan, Yanke Zhang, Lihua Xiong, and Chong-Yu Xu
EGUsphere, https://doi.org/10.5194/egusphere-2025-679, https://doi.org/10.5194/egusphere-2025-679, 2025
Short summary
Short summary
We propose a method to estimate the reservoir WLS curve based on the capacity loss induced by sediment accumulation and further assess the potential negative impact caused by outdated design WLS curve on flood regulation risks. The findings highlight that when storage capacity is considerably reduced, continued use of the existing design WLS curve may significantly underestimate, thus posing potential safety hazards to the reservoir itself and downstream flood protection objects.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, Xiang Zhang, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci., 28, 3305–3326, https://doi.org/10.5194/hess-28-3305-2024, https://doi.org/10.5194/hess-28-3305-2024, 2024
Short summary
Short summary
Climate change accelerates the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. We develop a cascade modeling chain to project future bivariate hydrological drought characteristics over China, using five bias-corrected global climate model outputs under three shared socioeconomic pathways, five hydrological models, and a deep-learning model.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024, https://doi.org/10.5194/hess-28-2809-2024, 2024
Short summary
Short summary
Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Jinghua Xiong, Shenglian Guo, Abhishek, Jiabo Yin, Chongyu Xu, Jun Wang, and Jing Guo
Hydrol. Earth Syst. Sci., 28, 1873–1895, https://doi.org/10.5194/hess-28-1873-2024, https://doi.org/10.5194/hess-28-1873-2024, 2024
Short summary
Short summary
Temporal variability and spatial heterogeneity of climate systems challenge accurate estimation of probable maximum precipitation (PMP) in China. We use high-resolution precipitation data and climate models to explore the variability, trends, and shifts of PMP under climate change. Validated with multi-source estimations, our observations and simulations show significant spatiotemporal divergence of PMP over the country, which is projected to amplify in future due to land–atmosphere coupling.
Qian Lin, Jie Chen, and Deliang Chen
EGUsphere, https://doi.org/10.5194/egusphere-2024-826, https://doi.org/10.5194/egusphere-2024-826, 2024
Preprint archived
Short summary
Short summary
Glaciers of the Tibetan Plateau (TP) have experienced widespread retreat in recent decades, but impacts of glacier changes that have occurred on regional climate, including precipitation, is still unknown. Thus, this study addressed this knowledge gap, and found that glacier changes exert a more pronounced impact on summer extreme precipitation events than mean precipitation over the TP. This provides a certain theoretical reference for the further improvement of long-term glacier projection.
Jiabo Yin, Louise J. Slater, Abdou Khouakhi, Le Yu, Pan Liu, Fupeng Li, Yadu Pokhrel, and Pierre Gentine
Earth Syst. Sci. Data, 15, 5597–5615, https://doi.org/10.5194/essd-15-5597-2023, https://doi.org/10.5194/essd-15-5597-2023, 2023
Short summary
Short summary
This study presents long-term (i.e., 1940–2022) and high-resolution (i.e., 0.25°) monthly time series of TWS anomalies over the global land surface. The reconstruction is achieved by using a set of machine learning models with a large number of predictors, including climatic and hydrological variables, land use/land cover data, and vegetation indicators (e.g., leaf area index). Our proposed GTWS-MLrec performs overall as well as, or is more reliable than, previous TWS datasets.
Youjiang Shen, Karina Nielsen, Menaka Revel, Dedi Liu, and Dai Yamazaki
Earth Syst. Sci. Data, 15, 2781–2808, https://doi.org/10.5194/essd-15-2781-2023, https://doi.org/10.5194/essd-15-2781-2023, 2023
Short summary
Short summary
Res-CN fills a gap in a comprehensive and extensive dataset of reservoir-catchment characteristics for 3254 Chinese reservoirs with 512 catchment-level attributes and significantly enhanced spatial and temporal coverage (e.g., 67 % increase in water level and 225 % in storage anomaly) of time series of reservoir water level (data available for 20 % of 3254 reservoirs), water area (99 %), storage anomaly (92 %), and evaporation (98 %), supporting a wide range of applications and disciplines.
Youjiang Shen, Dedi Liu, Liguang Jiang, Karina Nielsen, Jiabo Yin, Jun Liu, and Peter Bauer-Gottwein
Earth Syst. Sci. Data, 14, 5671–5694, https://doi.org/10.5194/essd-14-5671-2022, https://doi.org/10.5194/essd-14-5671-2022, 2022
Short summary
Short summary
A data gap of 338 Chinese reservoirs with their surface water area (SWA), water surface elevation (WSE), and reservoir water storage change (RWSC) during 2010–2021. Validation against the in situ observations of 93 reservoirs indicates the relatively high accuracy and reliability of the datasets. The unique and novel remotely sensed dataset would benefit studies involving many aspects (e.g., hydrological models, water resources related studies, and more).
Jinghua Xiong, Shenglian Guo, Abhishek, Jie Chen, and Jiabo Yin
Hydrol. Earth Syst. Sci., 26, 6457–6476, https://doi.org/10.5194/hess-26-6457-2022, https://doi.org/10.5194/hess-26-6457-2022, 2022
Short summary
Short summary
Although the "dry gets drier, and wet gets wetter (DDWW)" paradigm is prevalent in summarizing wetting and drying trends, we show that only 11.01 %–40.84 % of the global land confirms and 10.21 %–35.43 % contradicts the paradigm during 1985–2014 from a terrestrial water storage change perspective. Similar proportions that intensify with the increasing emission scenarios persist until the end of the 21st century. Findings benefit understanding of global hydrological responses to climate change.
Wei Li, Jie Chen, Lu Li, Yvan J. Orsolini, Yiheng Xiang, Retish Senan, and Patricia de Rosnay
The Cryosphere, 16, 4985–5000, https://doi.org/10.5194/tc-16-4985-2022, https://doi.org/10.5194/tc-16-4985-2022, 2022
Short summary
Short summary
Snow assimilation over the Tibetan Plateau (TP) may influence seasonal forecasts over this region. To investigate the impacts of snow assimilation on the seasonal forecasts of snow, temperature and precipitation, twin ensemble reforecasts are initialized with and without snow assimilation above 1500 m altitude over the TP for spring and summer in 2018. The results show that snow assimilation can improve seasonal forecasts over the TP through the interaction between land and atmosphere.
Jing Tian, Zhengke Pan, Shenglian Guo, Jiabo Yin, Yanlai Zhou, and Jun Wang
Hydrol. Earth Syst. Sci., 26, 4853–4874, https://doi.org/10.5194/hess-26-4853-2022, https://doi.org/10.5194/hess-26-4853-2022, 2022
Short summary
Short summary
Most of the literature has focused on the runoff response to climate change, while neglecting the impacts of the potential variation in the active catchment water storage capacity (ACWSC) that plays an essential role in the transfer of climate inputs to the catchment runoff. This study aims to systematically identify the response of the ACWSC to a long-term meteorological drought and asymptotic climate change.
Shanlin Tong, Weiguang Wang, Jie Chen, Chong-Yu Xu, Hisashi Sato, and Guoqing Wang
Geosci. Model Dev., 15, 7075–7098, https://doi.org/10.5194/gmd-15-7075-2022, https://doi.org/10.5194/gmd-15-7075-2022, 2022
Short summary
Short summary
Plant carbon storage potential is central to moderate atmospheric CO2 concentration buildup and mitigation of climate change. There is an ongoing debate about the main driver of carbon storage. To reconcile this discrepancy, we use SEIB-DGVM to investigate the trend and response mechanism of carbon stock fractions among water limitation regions. Results show that the impact of CO2 and temperature on carbon stock depends on water limitation, offering a new perspective on carbon–water coupling.
Yujie Zeng, Dedi Liu, Shenglian Guo, Lihua Xiong, Pan Liu, Jiabo Yin, and Zhenhui Wu
Hydrol. Earth Syst. Sci., 26, 3965–3988, https://doi.org/10.5194/hess-26-3965-2022, https://doi.org/10.5194/hess-26-3965-2022, 2022
Short summary
Short summary
The sustainability of the water–energy–food (WEF) nexus remains challenge, as interactions between WEF and human sensitivity and water resource allocation in water systems are often neglected. We incorporated human sensitivity and water resource allocation into a WEF nexus and assessed their impacts on the integrated system. This study can contribute to understanding the interactions across the water–energy–food–society nexus and improving the efficiency of resource management.
Jiacheng Chen, Jie Chen, Xunchang John Zhang, Peiyi Peng, and Camille Risi
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-460, https://doi.org/10.5194/essd-2021-460, 2022
Manuscript not accepted for further review
Short summary
Short summary
To make full use of the advantages of isotope observations and simulations, this study generates a new dataset by integrating multi-GCM data based on data fusion and bias correction methods. This dataset contains monthly δ18Op over mainland China for the 1870–2017 period with a spatial resolution of 50–60 km. The built isoscape shows similar spatial and temporal distribution characteristics to observations, which is reliable and useful to extend the time and space of observations in China.
Jinghua Xiong, Shenglian Guo, Jie Chen, and Jiabo Yin
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-645, https://doi.org/10.5194/hess-2021-645, 2022
Manuscript not accepted for further review
Short summary
Short summary
Although the “dry gets drier and wet gets wetter” (DDWW) paradigm is widely used to describe the trends in wetting and drying globally, we show that 27.1 % of global land agrees with the paradigm, while 22.4 % shows the opposite pattern during the period 1985–2014 from the perspective of terrestrial water storage change. Similar percentages are discovered under different scenarios during the future period. Our findings will benefit the understanding of hydrological responses under climate change.
Wei Li, Lu Li, Jie Chen, Qian Lin, and Hua Chen
Hydrol. Earth Syst. Sci., 25, 4531–4548, https://doi.org/10.5194/hess-25-4531-2021, https://doi.org/10.5194/hess-25-4531-2021, 2021
Short summary
Short summary
Reforestation can influence climate, but the sensitivity of summer rainfall to reforestation is rarely investigated. We take two reforestation scenarios to assess the impacts of reforestation on summer rainfall under different reforestation proportions and explore the potential mechanisms. This study concludes that reforestation increases summer rainfall amount and extremes through thermodynamics processes, and the effects are more pronounced in populated areas than over the whole basin.
Ren Wang, Pierre Gentine, Jiabo Yin, Lijuan Chen, Jianyao Chen, and Longhui Li
Hydrol. Earth Syst. Sci., 25, 3805–3818, https://doi.org/10.5194/hess-25-3805-2021, https://doi.org/10.5194/hess-25-3805-2021, 2021
Short summary
Short summary
Assessment of changes in the global water cycle has been a challenge. This study estimated long-term global latent heat and sensible heat fluxes for recent decades using machine learning and ground observations. The results found that the decline in evaporative fraction was typically accompanied by an increase in long-term runoff in over 27.06 % of the global land areas. The observation-driven findings emphasized that surface vegetation has great impacts in regulating water and energy cycles.
Cited articles
Ambühl, J.: Customer oriented warning systems, Veröffentlichung Meteoschweiz Nr. 84, 1–86, https://www.meteosvizzera.admin.ch/dam/jcr:74b518b0-e768-4b06-b6bb-d8dd2286e066/veroeff84.pdf (last access: 3 December 2024), 2010.
Anshuka, A., van Ogtrop, F. F., Sanderson, D., and Leao, S. Z.: A systematic review of agent-based model for flood risk management and assessment using the ODD protocol, Nat. Hazards, 112, 2739–2771, 2022.
Bodoque, J. M., Diez-Herrero, A., Amerigo, M., Garcia, J. A., and Olcina, J.: Enhancing flash flood risk perception and awareness of mitigation actions through risk communication: A pre-post survey design, J. Hydrol., 568, 769–779, 2019.
Boelee, L., Lumbroso, D. M., Samuels, P. G., and Cloke, H. L.: Estimation of uncertainty in flood forecasts-A comparison of methods, J. Flood Risk Manag., 12, e12516, https://doi.org/10.1111/jfr3.12516, 2019.
Borga, M., Comiti, F., Ruin, I., and Marra, F.: Forensic analysis of flash flood response, WIREs Water, 6, e1338, https://doi.org/10.1002/wat2.1338, 2019.
Brazdova, M. and Riha, J.: A simple model for the estimation of the number of fatalities due to floods in central Europe, Nat. Hazards Earth Syst. Sci., 14, 1663–1676, https://doi.org/10.5194/nhess-14-1663-2014, 2014.
Cheng, W.: A review of rainfall thresholds for triggering flash floods, Adv. Water Sci., 24, 901–908, 2013.
Coccia, G. and Todini, E.: Recent developments in predictive uncertainty assessment based on the model conditional processor approach, Hydrol. Earth Syst. Sci., 15, 3253–3274, https://doi.org/10.5194/hess-15-3253-2011, 2011.
Collier, C. G.: Flash flood forecasting: What are the limits of predictability?, Q. J. Roy. Meteor. Soc., 133, 3–23, 2007.
Confalonieri, R., Bellocchi, G., Bregaglio, S., Donatelli, M., and Acutis, M.: Comparison of sensitivity analysis techniques: A case study with the rice model WARM, Ecol. Model., 221, 1897–1906, 2010.
Cools, J., Innocenti, D., and O'Brien, S.: Lessons from flood early warning systems, Environ. Sci. Policy, 58, 117–122, 2016.
Creutin, J. D., Borga, M., Lutoff, C., Scolobig, A., Ruin, I., and Créton-Cazanave, L.: Catchment dynamics and social response during flash floods: the potential of radar rainfall monitoring for warning procedures, Meteorol. Appl., 16, 115–125, 2009.
Cuite, C. L., Shwom, R. L., Hallman, W. K., Morss, R. E., and Demuth, J. L.: Improving coastal storm evacuation messages, Weather Clim. Soc., 9, 155–170, 2017.
Du, E., Cai, X., Sun, Z., and Minsker, B.: Exploring the role of social media and individual behaviors in flood evacuation processes: an agent-based modeling approach, Water Resour. Res., 53, 9164–9180, 2017.
Du, E., Wu, F., Jiang, H., Guo, N., Tian, Y., and Zheng, C.: Development of an integrated socio-hydrological modeling framework for assessing the impacts of shelter location arrangement and human behaviors on flood evacuation processes, Hydrol. Earth Syst. Sci., 27, 1607–1626, https://doi.org/10.5194/hess-27-1607-2023, 2023.
Duc Anh, D., Kim, D., Kim, S., and Park, J.: Determination of flood-inducing rainfall and runoff for highly urbanized area based on high-resolution radar-gauge composite rainfall data and flooded area GIS data, J. Hydrol., 584, 124704, 2020.
Han, S. S. and Coulibaly, P.: Bayesian flood forecasting methods: A review, J. Hydrol., 551, 340–351, 2017.
Hicks, F. E. and Peacock, T.: Suitability of HEC-RAS for flood forecasting, Can. Water Resour. J., 30, 159–174, 2005.
Janssen, M. A. and Ostrom, E.: Empirically based, agent-based models, Ecol. Soc., 11, 37, https://www.jstor.org/stable/26265994 (last access: 3 December 2024), 2006.
Jauernic, S. T. and Van den Broeke, M. S.: Tornado warning response and perceptions among undergraduates in Nebraska, Weather Clim. Soc., 9, 125–139, 2017.
Ke, Q., Tian, X., Bricker, J., Tian, Z., Guan, G., Cai, H., Huang, X., Yang, H., and Liu, J.: Urban pluvial flooding prediction by machine learning approaches-a case study of Shenzhen city, China, Adv. Water Resour., 145, 103719, https://doi.org/10.1016/j.advwatres.2020.103719, 2020.
Krzysztofowicz, R.: The case for probabilistic forecasting in hydrology, J. Hydrol., 249, 2–9, 2001.
LeClerc, J. and Joslyn, S.: The cry wolf effect and weather-related decision making, Risk Anal., 35, 385–395, 2015.
Lei, X., Wang, H., Liao, W., Yang, M., and Gui, Z.: Advances in hydro-meteorological forecast under changing environment, J. Hydraul. Eng., 49, 9–18, 2018.
Lim, J. R., Liu, B. F., and Egnoto, M.: Cry wolf effect? evaluating the impact of false alarms on public responses to tornado alerts in the southeastern United States, Weather Clim. Soc., 11, 549–563, 2019.
Lindell, M. K., Arlikatti, S., and Huang, S. K.: Immediate behavioral response to the June 17, 2013 flash floods in Uttarakhand, North India, Int. J. Disaster Risk Reduct., 34, 129–146, 2019.
Lo, S. M., Fang, Z., Lin, P., and Zhi, G. S.: An evacuation model: the SGEM package, Fire Saf. J., 39, 169–190, 2004.
Maidment, D. R.: Conceptual framework for the national flood interoperability experiment, J. Am. Water Resour. Assoc., 53, 245–257, 2017.
Mileti, D. S.: Factors related to flood warning response, U.S.-Italy Research Workshop on the Hydrometeorology, Impacts, and Management of Extreme Floods, November 1995, Perugia, Italy, 1–17, 1995.
Morss, R. E., Cuite, C. L., Demuth, J. L., Hallman, W. K., and Shwom, R. L.: Is storm surge scary? The influence of hazard, impact, and fear-based messages and individual differences on responses to hurricane risks in the USA, Int. J. Disaster Risk Reduct., 30, 44–58, 2018.
Oakley, J. E. and O'Hagan, A.: Probabilistic sensitivity analysis of complex models: a Bayesian approach, J. R. Stat. Soc. Ser. B-Stat. Methodol., 66, 751–769, 2004.
O'Hagan, A.: Bayesian analysis of computer code outputs: A tutorial, Reliab. Eng. Syst. Safe, 91, 1290–1300, 2006.
Oleyiblo, J. O. and Li, Z.: Application of HEC-HMS for flood forecasting in Misai and Wan'an catchments in China, Water Sci. Eng., 3, 14–22, 2010.
Papagiannaki, K., Petrucci, O., Diakakis, M., Kotroni, V., Aceto, L., Bianchi, C., Brázdil, R., Gelabert, M. G., Inbar, M., Kahraman, A., Kiliç, Ö., Krahn, A., Kreibich, H., Llasat, M. C., Llasat-Botija, M., Macdonald, N., de Brito, M. M., Mercuri, M., Pereira, S., Rehor, J., Geli, J. R., Salvati, P., Vinet, F., and Zêzere, J. L.: Developing a large-scale dataset of flood fatalities for territories in the Euro-Mediterranean region, FFEM-DB, Sci. Data, 9, 166, https://doi.org/10.1038/s41597-022-01273-x, 2022.
Parker, D. J., Priest, S. J., and Tapsell, S. M.: Understanding and enhancing the public's behavioural response to flood warning information, Meteorol. Appl., 16, 103–114, 2009.
Penning-Rowsell, E., Floyd, P., Ramsbottom, D., and Surendran, S.: Estimating injury and loss of life in floods: A deterministic framework, Nat. Hazards, 36, 43–64, 2005.
Petrucci, O.: Review article: Factors leading to the occurrence of flood fatalities: a systematic review of research papers published between 2010 and 2020, Nat. Hazards Earth Syst. Sci., 22, 71–83, https://doi.org/10.5194/nhess-22-71-2022, 2022.
Petrucci, O., Aceto, L., Bianchi, C., Bigot, V., Brázdil, R., Pereira, S., Kahraman, A., Kiliç, Ö., Kotroni, V., Llasat, M. C., Llasat-Botija, M., Papagiannaki, K., Pasqua, A. A., Rehor, J., Geli, J. R., Salvati, P., Vinet, F., and Zêzere, J. L.: Flood Fatalities in Europe, 1980–2018: Variability, Features, and Lessons to Learn, Water, 11, 1682, https://doi.org/10.3390/w11081682, 2019.
Potter, S., Harrison, S., and Kreft, P.: The benefits and challenges of implementing impact-based severe weather warning systems: perspectives of weather, flood, and emergency management personnel, Weather Clim. Soc., 13, 303–314, 2021.
Ramos Filho, G. M., Rabelo Coelho, V. H., Freitas, E. D. S., Xuan, Y., and Neves Almeida, C. S.: An improved rainfall-threshold approach for robust prediction and warning of flood and flash flood hazards, Nat. Hazards, 105, 2409–2429, 2021.
Ripberger, J. T., Silva, C. L., Jenkins-Smith, H. C., Carlson, D. E., James, M., and Herron, K. G.: False alarms and missed events: the impact and origins of perceived inaccuracy in tornado warning systems, Risk Anal., 35, 44–56, 2015.
Roberts, T., Seymour, V., Brooks, K., Thompson, R., Petrokofsky, C., O'Connell, E., and Landeg, O.: Stakeholder perspectives on extreme hot and cold weather alerts in England and the proposed move towards an impact-based approach, Environ. Sci. Policy, 136, 467–475, 2022.
Roulston, M. S. and Smith, L. A.: The Boy who Cried Wolf revisited: The impact of false alarm intolerance on cost-loss scenarios, Weather Forecast., 19, 391–397, 2004.
Salvati, P., Petrucci, O., Rossi, M., Bianchi, C., Pasqua, A. A., and Guzzetti, F.: Gender, age and circumstances analysis of flood and landslide fatalities in Italy, Sci. Total Environ., 610, 867–879, 2018.
Sawada, Y., Kanai, R., and Kotani, H.: Impact of cry wolf effects on social preparedness and the efficiency of flood early warning systems, Hydrol. Earth Syst. Sci., 26, 4265–4278, https://doi.org/10.5194/hess-26-4265-2022, 2022.
Shanghai Meteorological Bureau: Rainstorm warning signal, http://sh.cma.gov.cn/sh/news/yjjz/zhtqyj/201903/t20190329_243098.html (last access: 3 December 2024), 2019.
Shaojun, X., Yangsheng, J., Hao, J., Qiuju, L., Qi, X., Yi, L., Jun, Z., Feng, W., and Lingsheng, M.: Investigation and reflection on “2021.8.12” flood disaster in Liulin Town, Sui County, Hubei Province, China Flood & Drought Management, 32, 54–58, 2022.
Simmons, K. M. and Sutter, D.: False alarms, tornado warnings, and tornado casualties, Weather Clim. Soc., 1, 38–53, 2009.
Sivapalan, M. and Bloeschl, G.: Time scale interactions and the coevolution of humans and water, Water Resour. Res., 51, 6988–7022, 2015.
Slater, L., Villarini, G., Archfield, S., Faulkner, D., Lamb, R., Khouakhi, A., and Yin, J.: Global changes in 20-year, 50-year, and 100-year river floods, Geophys. Res. Lett., 48, e2020GL091824, https://doi.org/10.1029/2020GL091824, 2021.
Spitalar, M., Gourley, J. J., Lutoff, C., Kirstetter, P. E., Brilly, M., and Carr, N.: Analysis of flash flood parameters and human impacts in the US from 2006 to 2012, J. Hydrol., 519, 863–870, 2014.
Takahashi, S., Endoh, K., and Muro, Z. I.: Experimental study on people's safety against overtopping waves on breakwaters, Report on the Port and Harbour Institute, 34, 4–31, 1992.
Tekeli, A. E. and Fouli, H.: Reducing false flood warnings of trmm rain rates thresholds over Riyadh city, Saudi Arabia by utilizing AMSR-E soil moisture information, Water Resour. Manag., 31, 1243–1256, 2017.
Terti, G., Ruin, I., Anquetin, S., and Gourley, J. J.: A Situation-Based Analysis of Flash Flood Fatalities in the United States, B. Am. Meteorol. Soc., 98, 333–345, https://doi.org/10.1175/BAMS-D-15-00276.1, 2017.
Todini, E.: Flood Forecasting and Decision Making in the new Millennium. Where are We?, Water Resour. Manage., 31, 3111–3129, 2017.
Wang, L., Nie, R. H., Slater, L. J., Xu, Z. H., Guan, D. W., and Yang, Y. F.: Education can improve response to flash floods, Science, 377, 1391–1392, 2022.
Wang, Z. Q., Huang, J., Wang, H. M., Kang, J. L., and Cao, W. W.: Analysis of flood evacuation process in vulnerable community with mutual aid mechanism: an agent-based simulation framework, Int. J. Env. Res. Pub. He., 17, 560, https://doi.org/10.3390/ijerph17020560, 2020.
Wei, L.: Extreme heavy rainfall in Liulin Town, Suixian County, Hubei Province has resulted in 21 deaths and 4 missing persons, https://baijiahao.baidu.com/s?id=1707934363237110140&wfr=spider&for=pc (last access: 3 December 2024), 2021.
Wu, S., Lei, Y., Yang, S., Cui, P., and Jin, W.: An agent-based approach to integrate human dynamics into disaster risk management, Front. Earth Sci., 9, 818913, https://doi.org/10.3389/feart.2021.818913, 2022.
Yang, L. E., Scheffran, J., Suesser, D., Dawson, R., and Chen, Y. D.: Assessment of flood losses with household responses: agent-based simulation in an urban catchment area, Environ. Model. Assess., 23, 369–388, 2018.
Yin, J., Gao, Y., Chen, R., Yu, D., Wilby, R., Wright, N., Ge, Y., Bricker, J., Gong, H., and Guan, M.: Flash floods: why are more of them devastating the world's driest regions? Nature, 615, 212–215, 2023.
Young, A., Bhattacharya, B., and Zevenbergen, C.: A rainfall threshold-based approach to early warnings in urban data-scarce regions: A case study of pluvial flooding in Alexandria, Egypt, J. Flood Risk Manag., 14, e12702, https://doi.org/10.1111/jfr3.12702, 2021.
Younis, J., Anquetin, S., and Thielen, J.: The benefit of high-resolution operational weather forecasts for flash flood warning, Hydrol. Earth Syst. Sci., 12, 1039–1051, https://doi.org/10.5194/hess-12-1039-2008, 2008.
Zhai, X., Guo, L., Liu, R., and Zhang, Y.: Rainfall threshold determination for flash flood warning in mountainous catchments with consideration of antecedent soil moisture and rainfall pattern, Nat. Hazards, 94, 605–625, 2018.
Zhang, R., Liu, D., Du, E., Xiong, L., Chen, J., and Chen, H.: An agent-based model to simulate human responses to flash flood warnings for improving evacuation performance, J. Hydrol., 628, 130452, https://doi.org/10.1016/j.jhydrol.2023.130452, 2024.
Zhuo, L. and Han, D. W.: Agent-based modelling and flood risk management: A compendious literature review, J. Hydrol., 591, 125600, https://doi.org/10.1016/j.jhydrol.2020.125600, 2020.
Short summary
Flash flood warnings cannot be effective without people’s responses to them. We propose a method to determine the threshold of issuing warnings based on a people’s response process simulation. The results show that adjusting the warning threshold according to people’s tolerance levels to the failed warnings can improve warning effectiveness, but the prerequisite is to increase forecasting accuracy and decrease forecasting variance.
Flash flood warnings cannot be effective without people’s responses to them. We propose a method...