Weather forecasting and Flood Simulation for Sustainable Land Use Management: Bentota River Basin in Sri Lanka

  • Gayani Prasadika Ranasinghe Lecturer PhD Student
  • Ranjana Udaya Kumara Piyadasa Senior Lecturer Department of Geography University of Colombo
  • Prasad Danajaya Bandara Research Assistant
  • Sonali Herath Research Assistant
Keywords: sustainable land use management


Flood simulation modeling related to land use management is very important for mitigation and integration of disaster risk reduction in the development process. Flood estimation data obtained through gauging stations, Geographic Position System (GPS) devices and participatory-based mapping are poor in accuracy, and current software for flood simulation is costly and requires a vast amount of input data. Hence, it is essential to have a proper method to simulate flooding in the context of changes in rainfall patterns in a relatively fast and accurate manner for flood-prone areas of Sri Lanka. This study analyzes the time series characteristics of total monthly rainfall and maximum daily rainfall of the Bentota River basin applying Mann–Kendall (MK) tests to rainfall trends as major input data for a flood simulation model which has been developed applying Arc Geographic Information System (GIS) software and Python scripting. The model combined various factors such as rainfall, slope, hydrology, soil, land use, storm water drainage, and human behavior factors. The developed flood simulation model showed a good level of consistency between observed and simulated results, with 64.03% accuracy. Maximum daily rainfall of this area shows a general increasing trend, whereas total monthly rainfall shows a general decreasing trend. According to the results of this study, there will be an extreme variability of rainfall once every 5 years during any month from April to July resulting in a minor flood situation in the area. Introducing riparian buffers, a flood resistive green home gardening model, green paving, rain water harvesting, drenching inland waterways, and converting selected marshy lands as park areas could be implemented as sustainable land management strategies for flood disaster risk reduction in the area. Farmers and the local community will be the main beneficiaries of the findings of this study. Moreover, decision makers could make decisions based on this prediction relating to future flood occurrences, vulnerable areas, and flood levels. The approach adopted in this study will also be useful for other researchers, agriculturalists, and planners to identify future climatological influences and to develop flood simulation models for other river catchment areas.

Author Biographies

Gayani Prasadika Ranasinghe, Lecturer PhD Student


Department of Town and Country Planning
University of Moratuwa
Sri Lanka

Ranjana Udaya Kumara Piyadasa, Senior Lecturer Department of Geography University of Colombo

Senior Lecturer
Department of Geography
University of Colombo

Prasad Danajaya Bandara, Research Assistant

Research Assistant

Department of Geography
University of Colombo

Sonali Herath, Research Assistant

Research Assistant

Department of Geography
University of Colombo


Aziz, A. R. A., Anokye, M., Kwame, A., Munyakazi, L., & Nuamah, N. N. N. (2013). Modeling and forecasting rainfall pattern in Ghana as a seasonal ARIMA process: The case of Ashanti region. International Journal of Humanities and Social Science, 3(3), 224–233.

Barredo, J. I., & Engelen, G. (2010). Land use scenario modeling for flood risk mitigation. Sustainability. Retrieved from

Basos, N. (2013). GIS as a tool to aid pre- and post-processing of hydrodynamic models. Application to the Guadiana Estuary. Faro, Portugal: Faculdade de Ciências e Tecnologia e Instituto Superior de Engenharia, Universidade Do Algarve.

Bian, M., & Han, M. (2015, June 28–July 3). The research on 3d visualization system of Dam-Break flood routing based on Google Earth. E-proceedings of the 36th IAHR World Congress, The Hague, The Netherlands.

Box, G. E. P., & Jenkins, G. M. (1970). Time series analysis: Forecasting and control. San Francisco, CA: Holden Day.

Bratha, A., Montanaria, A., & Morettib, G. (2006). Assessing the effect on flood frequency of land use change via hydrological simulation (with uncertainty). Journal of Hydrology, 324(1–4), 141–153.

Buckle, C. (1996). Weather and climate in Africa. Essex, UK: Longman.

Cleve, C., Kelly, M., Kearns, F. R., & Moritz, M. (2008). Classification of the wildland–urban interface: A comparison of pixel- and object-based classifications using high-resolution aerial photography. Computer, Environment and Urban system, 32(4), 317–326.

Disaster Management Center. (2005). Towards a safer Sri Lanka: A road map for disaster management (Supported by United Nations Development Programme). Sri Lanka: Disaster Management Center, Ministry of Disaster Managemen, Colombo,Sri Lanka

Freeze, R. A., & Witherspoon, P. A. (1967). Theoretical analysis of regional groundwater flow: Effect of water-table configuration and subsurface permeability variation. Water Resources Research, 3(2), 623–634.

Jiang, L., Chen, Y., & Wang, H. (2015). Urban flood simulation based on the SWMM model remote sensing and GIS for hydrology and water resources (IAHS Publ. 368). Proceedings of RSHS14 and ICGRHWE14, Guangzhou, China. 24–27 August 2014.

Keredin, T. S., Annisa, M., Surendra, B., & Solomon, A. (2013). Long years comparative climate change trend analysis in terms of temperature, coastal Andhra Pradesh, India. National Monthly Refereed Journal Research in Science & Technology, 2(7),1-13. ISSN: 2277-1174.

Kim, T. W., & Jaun, B. V. (2003). A nonlinear model for drought forecasting based on conjunction of wavelet transforms and neural networks. Journal of Hydrologic Engineering, 8( 6), 1–37.

Lehner, B., Döll, P., Alcamo, J., Henrichs, T., & Kaspar, F. (2006). Estimating the impact of global change on flood and drought risks in Europe: A continental, integrated analysis. Climatic Change, 75(3), 273–299.

Miguez, M. G., & de Magalhães, L. P. C. (2010). Urban flood control, Simulation and Management: An integrated approach. In Methods and techniques in urban engineering (pp. 131–160). edited by Filho, A.C.D.P and Pina, A.C.D., Published: May 1, 2010 under CC BY-NC-SA 3.0 license. ISBN 978-953-307-096-4.( DOI: 10.5772/9574)

Nandalal, H. K., & Ratnayake, U. R. (2010, December 13–14). Setting up of indices to measure vulnerability of structures during a flood. Proceedings of the International Conference on Sustainable Built Environment (Icsbe-2010), Kandy, Sri Lanka.

Poesen, J. W. A., & Hooke, J. M. (1997). Erosion, flooding and channel management in Mediterranean environments of southern Europe. Progress in Physical Geography, 21(2), 157–199.

Ratnayake, M. (2008). Sri Lankawe Swabhawika Wyasana [Natural disasters in Sri Lanka]. M. D. Gunasena. ISBN: 978-955-590-085-0. (In Sinhala). Colombo.Sri Lanka

Silva, M. M. G. T.D, Weerakoon, S. B., Herath, S., & Ratnayake, U. R. (2012). Event based flood modeling in lower Kelani basin. Proceedings of SAITM Research Symposium on Engineering Advancements (SAITM – RSEA), 27th and 28th April 2012,SAITM Auditorium , Malabe, Sri Lanka

Smith, K., & Ward, R. (1998). Floods: Physical process and human impacts. West Sussex, UK: John Wiley.

Survey Department.(2010). Maps and Geo information. Retrieved from: surveyweb/home%20english/MapsandGEOInformation.php, accessed on 16th September 2016.

Thampapillai, D. J., & Musgrave, W. F. (1985). Flood damage mitigation: A review of structural and nonstructural measures and alternative decision frameworks. Water Resources Research, 21, 411–424.

Thomaz, S. M., Bini, L. M., & Bozelli, R. L. (2007). Floods increase similarity among aquatic habitats in river-floodplain systems. Hydrobiologia, 579(1), 1–13.

Tomczak, M. (1998). Spatial interpolation and its uncertainty using automated anisotropic inverse distance weighting (IDW). Cross-validation/jackknife approach. Journal of Geographic Information and Decision Analysis, 2, 18–30.

Venkatesh, M. F. O. (2008). Uncertainty in flood inundation mapping: Current issues and future directions. Journal of Hydrologic Engineering. July 2008.608-620. DOI: 10.1061/ ASCE1084-0699 200813:7 608 C.

Wallingford, H. R. (2006). Assessing the benefits of flood warning: A scoping study. Edinburgh, UK: SNIFFER. Retrieved from

Yerramilli, S. (2012). A hybrid approach of integrating HEC-RAS and GIS towards the identification and assessment of flood risk vulnerability in the city of Jackson, MS. American Journal of Geographic Information System, 1(1), 7–16.