Flood modelling requires a reliable model, a set of quality data and a good modeler to produce meaningful outputs for water infrastructure to achieve a sustainable environment with effective water resources management. Though flood modelling to predict the peakflow values was a great achievement in the past, the technology in the recent years have paved the way to go into great details such as inundation levels, inundation extents, spatial distribution and temporal distribution of flooding. Remote sensing techniques using satellites, drones, ground based cameras, CCTV along with mobile telecommunication based big data concepts, and GIS technology for mapping, has changed the world to levels that now demands user specific flood information. in most developed nations this will be the ground reality in a few years from now. It is important to realize the basics required for water managers in the south Asian region to achieve this kind of information are immense. If one looks at the requirements, then it starts with the human resources and then goes on to list as models, data, verification, effectiveness, etc., etc. In the region there are a handful of experts who are capable of fitting in to the slot of human resources requirement but it is far below the critical mass. UMCSAWM at present is targeting to achieve the fulfillment of this need. In this effort the huge obstacle is the data requirement. Even if sharing is kept aside for a moment, the rarity is the shortage of demonstrations to point out the importance of spatial and temporal data to evaluate and provide infrastructure solutions for flooding and perform sufficient flood forecasting. Though this is common to handling the other water related disasters as well, a good start will be to take policy decisions on human capacity building and preparation of guidelines for flood modelling. UMCSAWM from its ESD program for water resources engineering and management has carried out flood modelling of most Sri Lankan river basins with the use of commonly used models such as HEC, SWMM5, Snyder’s UH etc. These research has looked at aspects such as, capacity required for modelling, selection of appropriate process functionalities from a flood model, data requirement, calibration and verification methods and thresholds. Based on this knowledge and experience it is possible to make flood modelling recommendations similar to the following.
The decision makers need to establish a policy and associated regulations for the practicing agencies to evaluate causes, effects, impacts and alternative solutions to handle flood situations in a country through a commission of independent experts who would ensure the accuracy of outputs as part of their terms of reference. Then it is necessary to extend the policy to provide the information of such assessments, solutions and guidance to the public.