Browsing by Author "Ratnayake, UR"

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item: Conference-Full-text
Editing a digital elevation model to achieve a correct stream network: an application to Kalu-Ganga River in Sri Lanka
(Department of Earth Resources Engineering, 2009-05) Nandalal, HK; Ratnayake, UR; Karunaratne, S
Modelling a watershed accurately is an important step in water management. Geographic Information Systems (GIS) together with mathematical models have made modelling watersheds an easy task. Digital Elevation Model (DEM) ts a primary data set necessary to model a watershed. DEMs developed using many methods and DEMs are developed from remotely sensed data are the cheapest. Some of them are freely available on-line. In modelling watersheds, it is a common practice to delineate the stream network from a DEM. Matching of the delineated stream network with the natural stream network will depend on the accuracy of the DEM. Some hydrologic models contain built-in functions to edit DEMs to overcome this problem. Hydrologic model, HEC GeoHMS, contains such a function to edit DEM as required by the user. To edit the DEM it is necessary to have the exact stream network to compare with the delineated network. In this work, Kaluganga River stream network was delineated using a DEM available freely on-line and it was compared with the natural stream network of Kalu-ganga River digitized from 1:50,000 maps produced by the Department of Survey. Then the DEM was edited using the HEC GeoHMS model to achieve the desired stream network.
item: Conference-Full-text
Editing a digital elevation model to achieve, a correct stream network: an application to , " Kalu-ganga river in, Sri Lanka
(2014-07-01) Nandalal, HK; Ratnayake, UR
Modelling a watershed accurately is an important step in water resources management. Geographic Information Systems (GIS) together with mathematical models have made modelling watersheds an easy task. Digital Elevation Model (OEM) is a primary data set necessary to model a watershed. OEMs are developed using many methods and OEMs developed from remotely sensed data are the cheapest. Some of them are freely available on-line. In modelling watersheds, it is a common practice to delineate the stream network from a OEM.Matching of the delineated stream network with the natural stream network will depend on the accuracy of the OEM. Some hydrologic models contain built-in functions to edit . OEMs to overcome this problem. Hydrologic model, HEC GeoHMS, contains such a function to edit OEMas-required by the user. To edit the OEM it is necessary to have the exact stream network to compare with the delineated network. In this work, Kaluganga River stream network was delineated using a OEM available freely on-line and it was compared with the natural stream network of Kalu-ganga River digitized from 1:50,000maps produced by the Department of Survey. Then the OEM was edited using the HEC GeoHMS model to achieve the desired stream network.
item: Conference-Full-text
Setting up of indices to measure vulnerability of structures During a flood
(2013-11-15) Nandalal, HK; Ratnayake, UR
Computation of flood extents and identification of vulnerable elements help to take mitigatory measures effectively and efficiently during a disaster. This is a baseline study carried out to examine how effectively the vulnerability of a small administrative division that depend on the type and facilities of existing structures can be assessed. In this study the flood extent of upper reaches of Kalu-Ganga River in Sri Lanka for a rainfall of 100 year return period was derived using HEC-HMS and HEC-RAS software. Building vulnerability within the administrative divisions affected by floods were derived using census data. Subsequently, flood risk maps with respect to structures due to 100 year return period rainfall were developed based on vulnerability derived from census data and the developed flood hazard maps. This approach could be used to identify high risk administrative divisions during a disastrous flood event to organize relief aids. It further helps in taking post disaster mitigatory measures according to the vulnerability levels of the buildings in each administrative division. Identification of crucial factors that influence vulnerability helps to reduce vulnerability and to mitigate the risks involved in future flood events.