Research on the Construction of a Flood Control Four-Forecast Application System Based on Large-Model Intelligent Agent Application Architecture
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Abstract
This study presents the design and implementation of a flood control “Four Predictions” (forecasting, early warning, simulation, contingency planning) application system tailored in flood-prone areas, based on a Large-Model Intelligent Agent Application Architecture. The system integrates multimodal flood control data, including meteorological observations, hydrological measurements, satellite remote sensing imagery, and social media reports, processed through a dynamic data fusion framework. The model layer combines domain-adapted large language models (BERT) with specialized micro-model clusters for precipitation forecasting, dam breach simulation, and regional vulnerability assessment. Perception agents employ Isolation Forest and Kalman filtering for real-time anomaly detection, cognitive agents utilize dynamic Bayesian networks and DQN-based adaptive warning thresholds, and action agents manage emergency resource allocation via an auction mechanism and optimized evacuation routing. Multiscale 3D simulations, ST-ConvNet forecasting, and uncertainty quantification through Monte Carlo sampling provide precise, high-resolution support for decision-making. Technical validation against historical extreme rainfall events confirms the system’s ability to enhance flood response accuracy and reduce false alarms. The framework leverages 5G-enabled wireless communication, edge-cloud computing collaboration, and antenna-supported sensing platforms, offering an engineering-oriented solution for rapid, adaptive, and robust flood control operations in industrial environments.
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References
J. Lv, J. Hou, T. Wang, W. Zhou, D. Li, Y. Tong, et al., “The research on narrow-valley city flood control mode based on hydrodynamic-hydrological coupling model,” Journal of Hydrology, vol. 640, no. 0, p. 13, 2024, doi: 10.1016/j.jhydrol.2024.131584.
L. Zhou, L. Kang, S. Hou, and J. Guo, “Research on Flood Risk Control Methods and Reservoir Flood Control Operation Oriented towards Floodwater Utilization,” Water, vol. 16, no. 1, p. 15, 2024, doi: 10.3390/w16010043.
Y. Wu, S. Zheng, Q. Liu, A. Dong, and Q. Li, “Structural and empirical knowledge driven multi-objective evolutionary algorithm for urban drainage system design,” Expert Systems with Applications, vol. 249, p. 123461, 2024, doi: 10.1016/j.eswa.2024.123461.
Y. Zhang, S. Wang, W. Ge, Z. Li, H. Li, W. Du, et al., “A Calculation Method for Flood Control Benefits of River Treatment Projects Considering the Uncertainty of Flood Peak and Flood Frequency,” Water Resources Management, vol. 39, no. 8, 2025, doi: 10.1007/s11269-025-04153-2.
R. Itsukushima, K. Ohtsuki, and T. Sato, “Significance of land use as a flood control measure: Unveiling the historical and contemporary strategies in the unique case of Kofu basin alluvial fan, Japan,” International Journal of Disaster Risk Reduction, vol. 109, no. c, p. 104578, 2024, doi: 10.1016/j.ijdrr.2024.104578.
G. Al-Rawas, M. R. Nikoo, and M. Al-Wardy, “A review on the prevention and control of flash flood hazards on a global scale: Early warning systems, vulnerability assessment, environmental, and public health burden,” International Journal of Disaster Risk Reduction, vol. 115, p. 105024, 2024, doi: 10.1016/j.ijdrr.2024.105024.
Z. Q, T. Yan, G. Siyuan, J. Zhou, X. He, W. He, et al., “Stability behavior of the Lanxi ancient flood control levee after reinforcement with upside-down hanging wells and grouting curtain,” Journal of Mountain Science, vol. 21, no. 1, pp. 84-99, 2024, doi: 10.1007/s11629-023-8239-7.
M. Tanhapour, J. Soltani, H. Shakibian, B. Malekmohammadi, K. Hlavcova, and S. Kohnova, “Development of a Multi-objective Optimal Operation Model of a Dam using Meteorological Ensemble Forecasts for Flood Control,” Water Resources Management, vol. 39, no. 6, pp. 2743-2761, 2025, doi: 10.1007/s11269-024-04089-z.
C. Xu, P. Zhong, F. Zhu, L. Li, Q. Lu, and L. Yang, “Stochastic multi-criteria decision making framework based on SMAA-VIKOR for reservoir flood control operation,” Hydrological Sciences Journal, vol. 68, pp. 886-901, 2023, doi: 10.1080/02626667.2022.2154161.
F. Chai, S. Liu, Y. Sun, and F. Huo, “Research and application of the flood simulation and operation model in Beijing,” E3S Web of Conferences, p. 16504018, 2020, doi: 10.1051/e3sconf/202016504018.
Y. Peng, X. Yu, L. Yao, S. Luo, and Z. Zhang, “Including dynamic capacity impact in an improved model for optimal flood control operation in river-type reservoirs,” Journal of Hydrology, vol. 645, p. 132163, 2024, doi: 10.1016/j.jhydrol.2024.132163.
L. Sun, J. Xia, D. She, W. Ding, J. Jiang, B. Liu, et al., “A predictive fuzzy logic and rule-based control approach for practical real-time operation of urban stormwater storage system,” Water Research, vol. 266, p. 122437, 2024, doi: 10.1016/j.watres.2024.122437.
L. Yao, Y. Peng, X. Yu, Z. Zhang, and S. Luo, “Improving Flood Control Optimal Operation of River-Type Cascade Reservoirs through Coupling with 1D Hydrodynamic Model,” Water Resources Management, vol. 39, no. 7, pp. 3443-3466, 2025, doi: 10.1007/s11269-025-04116-7.
L. Gao, Y. Gao, Y. Liu, and M. Wu, “Assessment of flood risk under Polder-Type flood control measure using improved projection pursuit model,” Ecological Indicators, vol. 170, p. 113038, 2025, doi: 10.1016/j.ecolind.2024.113038.
J. Liu, Z. Yang, Y. Liu, M. Li, and C. Zhou, “Can the regulation of Golden Inland Waterways meet the needs of navigation, flood control, and ecology? A model-based case study,” Ecological Engineering, vol. 196, p. 106998, 2023, doi: 10.1016/j.ecoleng.2023.106998.
J. Li, Z. Wang, and T. Zhang, “Flood simulation using the hydrological model and the hydrological–hydrodynamic coupling model in a small watershed in semi-arid and sub-humid region, North China,” Journal of water and climate change, vol. 14, no. 9/10, pp. 3496-3516, 2023, doi: 10.2166/wcc.2023.161.
H. Jin, X. Chen, R. Zhong, M. Liu, and C. Ye, “Construction of precipitation index based on ensemble forecast and heavy precipitation forecast in the Hanjiang River Basin, China,” Atmospheric Research, vol. 292, p. 106701, 2023, doi: 10.1016/j.atmosres.2023.106701.
Y. Gao, M. Wu, and G. Z. Zhang, “Analyzing the impact of polder-type flood control pattern on river system’s regulation and storage capacity under urbanization,” Journal of the American Water Resources Association, vol. 59, no. 6, pp. 1219-1245, 2023, doi: 10.1111/1752-1688.13128.
L. Sinha and S. M. Narulkar, “Optimal Operation of Multi-reservoir System Utilizing DEA, AIDE Algorithm and Flood Control Assessment by MCDM Approach,” Water Resources Management, vol. 39, no. 4, 2025, doi: 10.1007/s11269-024-04046-w.
E. Lee, S. Yi, J. Ji, J. Hong, S. Lee, J. Yoon, et al., “Development of a reservoir operation model determining the pre-release strategy for the flood events Open Access,” Journal of Hydroinformatics, vol. 27, no. 4, pp. 23, 2025, doi: 10.2166/hydro.2025.262.
L. Li, L. Chen, S. Chen, Y. Zhang, Y. Xu, X. Zhi, et al., “The cumulative effects of cascade reservoirs control nitrogen and phosphorus flux: Base on biogeochemical processes,” Water Research, vol. 252, p. 121177, 2024, doi: 10.1016/j.watres.2024.121177.
A. M. Enríquez-Hidalgo, A. Vargas-Luna, and A. Torres, “Evaluation of decision-support tools for coastal flood and erosion control: A multicriteria perspective,” Journal of Environmental Management, vol. 373, p. 123924, 2025, doi: 10.1016/j.jenvman.2024.123924.
Y. Xu, K. Liu, Y. Ma, Q. Wang, and C. Gao, “Potential Impact of Flood Control Projects on Hydrological Processes in the Coastal Regions of the Taihu Basin, China,” Journal of the American Water Resources Association, vol. 61, no. 1, 2025, doi: 10.1111/1752-1688.70003.
K. E. Schilling, E. Anderson, and M. T. T. C. Streeter, “Long-term nitrate-nitrogen reductions in a large flood control reservoir,” Journal of Hydrology, vol. 620, p. 129533, 2023, doi: 10.1016/j.jhydrol.2023.129533.
A. Ogihara, M. Maeda, G. Katou, K. Matsumoto, K. Miyaoka, and D. Hirayama, “Research Reports the Practice of Flood Control Education Materials Based on the Kumozu River Basin Case from Mie Prefecture,” Environmental Education, vol. 34, no. 2, 2024, doi: 10.5647/jsoee.2420.