A Systematic Framework of Flash Floods Disaster-Causing Mechanisms in Ungauged Mountainous Micro-Watersheds: Case Study of Qialegeer Village, Xinjiang, China
Qiuyuan Liu , Ranmao Yang , Lin Zhao , Xinxin Li , Gangsheng Wang , Jianjun Wu
International Journal of Disaster Risk Science ›› 2025, Vol. 16 ›› Issue (5) : 843 -857.
A Systematic Framework of Flash Floods Disaster-Causing Mechanisms in Ungauged Mountainous Micro-Watersheds: Case Study of Qialegeer Village, Xinjiang, China
Flash floods are characterized by their destructive power, rapid onset, and unpredictability, often causing severe damage to both natural environments and socioeconomic systems. Understanding the detailed disaster-causing mechanisms of flash floods is critical for effective disaster risk reduction. However, current studies have not captured the comprehensive circumstance of flash floods that integrates environment, hazard, and exposure from the perspective of disaster systems theory. To address the gap, this study established a systematic framework for comprehensively evaluating flash floods disaster-causing mechanisms in ungauged mountainous micro-watersheds by integrating multi-source data, including remote sensing observations, meteorological station data, unmanned aerial vehicle measurements, and participatory geographic information system data, with hydrological-hydrodynamic and statistical models. The proposed framework consists of four interconnected steps: design storm estimation, flash flood process simulation, critical rainfall calculation, and disaster loss evaluation. Through a case study conducted in Qialegeer Village, Xinjiang, China, we demonstrated the framework’s applicability by reconstructing flash flood scenarios, including the 2017 event as well as those of 10 and 20 years return periods. The results demonstrate that our framework robustly and systematically elucidates flash flood disaster process in the region with high reliability. Furthermore, it is adaptable to other ungauged mountainous micro-watersheds. This framework ultimately serves to enhance disaster risk mitigation and build resilience in vulnerable mountainous communities.
Critical rainfall / Disaster-causing mechanism / Disaster loss evaluation / Flash floods / Hydrological-hydrodynamic model
| [1] |
|
| [2] |
|
| [3] |
Allen, G.H., T.M. Pavelsky, E.A. Barefoot, M.P. Lamb, D. Butman, A. Tashie, and C.J. Gleason. 2018. Similarity of stream width distributions across headwater systems. Nature Communications 9(1): Article 610. |
| [4] |
|
| [5] |
|
| [6] |
|
| [7] |
Diakakis, M., N. Boufidis, J.M. Salanova Grau, E. Andreadakis, and I. Stamos. 2020. A systematic assessment of the effects of extreme flash floods on transportation infrastructure and circulation: The example of the 2017 Mandra flood. International Journal of Disaster Risk Reduction 47: Article 101542. |
| [8] |
|
| [9] |
|
| [10] |
El-Bagoury, H., and A. Gad. 2024. Integrated hydrological modeling for watershed analysis, flood prediction, and mitigation using meteorological and morphometric data, SCS-CN, HEC-HMS/RAS, and QGIS. Water 16(2): Article 356. |
| [11] |
|
| [12] |
|
| [13] |
|
| [14] |
Hendrawan, V.S.A., and D. Komori. 2021. Developing flood vulnerability curve for rice crop using remote sensing and hydrodynamic modeling. International Journal of Disaster Risk Reduction 54: Article 102058. |
| [15] |
|
| [16] |
Jia, Y., Z. Li, F. Wang, C. Xu, W. Zhao, M. Sun, and P. Liang. 2024. Characteristics of glacier ice melt runoff in three sub-basins in Urumqi River basin, eastern Tien Shan. Journal of Hydrology: Regional Studies 53: Article 101772. |
| [17] |
Kastridis, A., and D. Stathis. 2020. Evaluation of hydrological and hydraulic models applied in typical Mediterranean ungauged watersheds using post-flash-flood measurements. Hydrology 16(1): Article 12. |
| [18] |
Khan, I.R., S.I. Elmahdy, R. Rustum, Q. Khan, and M.M. Mohamed. 2024. Floods modeling and analysis for Dubai using HEC-HMS model and remote sensing using GIS. Scientific Reports 14(1): Article 25039. |
| [19] |
Lee, C.-C., L. Huang, F. Antolini, M. Garcia, A. Juan, S.D. Brody, and A. Mostafavi. 2024. Predicting peak inundation depths with a physics informed machine learning model. Scientific Reports 14(1): Article 14826. |
| [20] |
|
| [21] |
|
| [22] |
|
| [23] |
|
| [24] |
|
| [25] |
|
| [26] |
|
| [27] |
|
| [28] |
|
| [29] |
Papathoma-Köhle, M., M. Schlögl, L. Dosser, F. Roesch, M. Borga, M. Erlicher, M. Keiler, and S. Fuchs. 2022. Physical vulnerability to dynamic flooding: Vulnerability curves and vulnerability indices. Journal of Hydrology 607: Article 127501. |
| [30] |
|
| [31] |
|
| [32] |
|
| [33] |
Ross, C.W., L. Prihodko, J. Anchang, S. Kumar, W. Ji, and N.P. Hanan. 2018. HYSOGs250m, global gridded hydrologic soil groups for curve-number-based runoff modeling. Scientific Data 5: Article 180091. |
| [34] |
Sekajugo, J., G. Kagoro-Rugunda, R. Mutyebere, C. Kabaseke, D. Mubiru, V. Kanyiginya, L. Vranken, L. Jacobs, et al. 2024. Exposure and physical vulnerability to geo-hydrological hazards in rural environments: A field-based assessment in East Africa. International Journal of Disaster Risk Reduction 102: Article 104282. |
| [35] |
|
| [36] |
|
| [37] |
Tegos, A., A. Ziogas, V. Bellos, and A. Tzimas. 2022. Forensic hydrology: A complete reconstruction of an extreme flood event in data-scarce area. Hydrology 9(5): Article 93. |
| [38] |
Valério, D.P., and E.O. Gerhard. 2024. Learning from a climate disaster: The catastrophic floods in southern Brazil. Science 385(6713): Article eadr8356. |
| [39] |
Wang, L., L. Ye, J. Wu, Q. Chang, and C. Zhang. 2018. Research on multi-hydrological models applicability of flash flood simulation in hilly areas. China Rural Water and Hydropower No. 2: 78–84; 90 (in Chinese). |
| [40] |
Willner, S.N., A. Levermann, F. Zhao, and K. Frieler. 2018. Adaptation required to preserve future high-end river flood risk at present levels. Science Advances 4(1): Article eaao1914. |
| [41] |
|
| [42] |
|
| [43] |
|
| [44] |
|
| [45] |
|
| [46] |
|
| [47] |
Yao, J., Y. Zhao, and X. Yu. 2018. Spatial-temporal variation and impacts of drought in Xinjiang (Northwest China) during 1961–2015. PeerJ 6: Article e4926. |
| [48] |
|
| [49] |
|
| [50] |
|
| [51] |
|
| [52] |
|
| [53] |
|
The Author(s)
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