New Approach to Distributed Flood Prediction Model using Agents based Communication

Naveed Qasim


Flood is the overflow of water from its normal ways to submerges land which is usually dry. It is clear that floods cannot be stopped, but the timely prediction and management is the only way to combat this hazard. Much work is documented on physical and logical solution to predict on the basis of risk to save people and reduce the destruction of their belongings. In this work we developed a logical model based on client and server agent communication to predict the hazard. In the process, initially a conceptual model is developed, further, an algorithm is constructed. Moreover, for it correctness and verification the algorithm is transformed to formal language Z. Finally the specified formal model is implemented using JAVA programming language.

Full Text:



. Africa, E. (2011). Presentation to the Portfolio Committee: Update on the Management of Recent Disaster Incidents. Presentation given the Parliamentary Portfolio Committee on Cooperative Governance and Traditional Affairs. Cape Town: Parliament of South Africa.

. Ahmad, S., & Simonovic, S. P. (2000, 7). Dynamic modeling of flood management policies. (pp. 6-10). Bergen, Norway: In Proceedings of the 18th International Conference of the System Dynamics Society: Sustainability in the Third Millennium.

. Anding, P., Muzhuang, Y., & Bishan, C. (2010). Flood Hazard Evaluation and GIS in Guangzhou. (pp. 1-4). Guangzhou: In Multimedia Technology (ICMT), 2010 International Conference on IEEE.

. Asif, R. S. (2012). Analysis and Design of Flood Prediction Model using Mobile Agents. Lahore: Roa Sohail Iqbal Asif, University of Central Punjab.

. Balica, S. F., Popescu, I., Beevers, L., & Wright, N. G. (2013). Parametric and physically based modelling techniques for flood risk and vulnerability assessment: A comparison. Environmental Modelling & Software, 41, 84–92

. Ghazali, J. N., & Kamisn, A. (2008). A Real Time Simulation and Modeling of Flood Hazard. 12th WSEAS International Conference on System (pp. 438-443). Heraklion: WSEAS International Conference. Proceedings. Mathematics and Computers in Science and Engineering (No. 12). WSEAS.

. Iqbal, R. S., Alshmari, M., Khan, S. A., Zafar, N. A., & Islam, S. (2013, January). A Mobile Agent-Based Algorithm for Prediction of Inundation Area. Research Journal of Recent Sciences, 3(1), 72-77.

. Ministry of lands Japan. (2000). Japan Tokai Heavy Rain. WMO/GWP Associated Program on Flood Management. Tokai: WMO/GWP Associated Programme on Flood Management.

. Monga, O. (2000). Anfas—data fusion for flood analysis and decision support. (pp. 27-29). Europe: In Proceedings of an International European-Asian Workshop. Ecosystem & Flood 2000.

. Nelson, S. A. (2002). River systems and causes of flooding. Tulane: Tulane University.

. Sengupta, S. K., Bales, J. D., Jubach, R., Scott, A. C., & Kane, M. D. (2006, December). Flood Forecasting and Inundation Mapping in the Mahanadi River Basin. A Collaborative Effort between India and the United States. Odisha: A Collaborative Effort between India and the United States.

. Zhao, D. H., Shen, H. W., Tabios III, G. Q., Lai, J. S., & Tan, W. Y. (1994). Finite-volume two-dimensional unsteady-flow model for river basins. Journal of Hydraulic Engineering, 120(7), 863-883.

. Zuma, B. M., Luyt, C. D., Chirenda, T., & Tandlich, R. (2012). Flood Disaster Management in South Africa: Legislative Framework and Current Challenges. Konya: INTECH Open Access Publisher.



  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.