Chapter scenarios of return periods 25 years, 50

Chapter 2 Methodology and Data2.1 preliminary investigationFor the beginning of this study it was decided to carry out preliminary investigation based on Pannala city to identify the real impacts due to floods events. By interviewing the residences and the related government authorities such as Irrigation Department of Katugampala Division and pradeshiya sabha information were collected to identify the gravity and necessity of this study based on this Pannala city.

Based on their opinion it was understood that need of this project is very essential. There is a high flood risk of this area which is increasing times to time. Flood vulnerability of this area is so high due to many reasons such as high flood intensities, low elevation, sand and clay mining of large extent and illegal wetland fillings.

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2.2 selection of the catchmentStudy area was selected based on the Pannala city for this study. It was decided to perform flood model analysis to mapping inundation area.

To perform flood forecasting model it was needed various flood scenarios of return periods 25 years, 50 years and 100 years. As well as we needed to identify upstream and downstream boundary conditions of specified area and daily average river discharge values for calibrate and validate the food model. When considering the availability of the rainfall and river discharge data it was planned to select Giriulla gauging station as the upstream boundary condition and Badalgama gauging station as the downstream boundary condition.2.3 water basin delineation (ARC GIS)Spatial data preparation was done using Arc GIS 10.5 software package. It is one of the best spatial data preparation software. Both hydrology and hydraulic model associated with the topographical information of the catchment.

Both software systems consists of processor programs to facilitate graphical editing and mapping which simulate channel and flood plain details. Digital elevation model represent the topography as series of a small tiles. DEM was downloaded by Alaska satellite facility (https://www.asf.alaska.edu/) with 12.

5 meter resolution. As the next step specified area was identified on digital elevation model by adding Arc world imagery map layer as base map. Specified area was clipped using clip tool coming under As per the study based on “EVENT BASED FLOOD MODELING IN LOWER KELANI BASIN” the system of FLOW-2D system consists of processor programs to enable graphical editing and mapping which simulate stream and flood zone topography. The Grid Developer System (GDS) produces a grid system that signify the landscape as a series of small grid. The GDS was used to produce 250 m x 250 m grids covering the lower basin area. The required topographical data derived from the data which were taken by Department of Survey, Colombo; 1:10,000 map layers were used to develop Digital Elevation model.10 Figure 1.

2 DEM of Giriulla Pannala catchment areaWater shed is an upslope area that gives water flow as focused drainage. This area can be delineated from a digital elevation model DEM using the hydrology toolset from the spatial analyst tool box. The following guidelines were provided a work flow to classify the watershed model using the hydrology toolset from the spatial analyst toolbox and translate the model to watershed bounding polygons.• Run the fill tool.In Arc Catalog, navigate to Toolboxes > System Toolboxes > Spatial Analyst Tools > Hydrology > Fill.

Digital elevation model (DEM) was used as input raster layer. The Fill tool fills sinks to eliminate imperfections from the DEM. A Z-limit touches the result of the tool. It was suggested to state the Z-limit if the depths of the sinks are known. The Sink (Spatial Analyst) tool can be used to classify the sinks and their depths prior to using the Fill tool. When a Z-limit is not definite in the Fill tool window, all sinks, regardless of depth, are filled.

Figure 2.7 Fill DEM of study area• Run the flow direction toolIn Arc Catalog, navigate to Toolboxes > System Toolboxes > Spatial Analyst Tools > Hydrology > Flow Direction. Fliied DEM was used as the input raster layer to create flow direction. Flow direction tool determined the direction of flow from the each cell to its steepest downslope neighbor. Figure 2.9 Flow direction• Run the flow accumulation In Arc Catalog, navigate to Toolboxes > System Toolboxes > Spatial Analyst Tools > Hydrology > Flow Accumulation. Used the output raster layer from flow direction to create flow accumulation. Flow accumulation tool computes the accumulated flow to each flow to each cell as resolute by the accumulated weight of all cells that flow into each downslope cell.

It was decided to analyze by rater calculation as flow accumulation > 4500 to identify the required flow accumulation on study area. Figure 2.8 flow accumulation• Run the Snap Pour Point tool Run snap pour point tool to locate the pour points to cells of high accumulated flow. In Arc Catalog, navigate to Toolboxes > System Toolboxes > Spatial Analyst Tools > Hydrology > Snap Pour Points. Pour points are points at which water flows out of an area, usually the outlet or re-entrant places from the flow accumulation. The Snap Pour Point tool snaps these points to the cell of maximum flow accumulation within a identified detachment. Either input a point feature class or a raster as the ‘Input raster or feature pour point data’. When creating snap note that pour points cells were not No Data (cells with values) were considered pour points and were snapped if a raster inputs was used while a point feature input specified the location of the cells to be snapped.

• Run the water shed toolIn Arc Catalog, navigate to Toolboxes > System Toolboxes > Spatial Analyst Tools > Hydrology > Watershed. Figure 2.8 identify water shed area related to the catchment• Run the Raster to polygon tool to create polygon features from the watershed rasterIn Arc Catalog, navigate to Toolboxes > System Toolboxes > Conversion Tools > From Raster > Raster to Polygon. In here it was decided to consider both automatic extraction Giriulla and Pannala watershed as one terrain for perform hydraulic and hydrology models by using HEC RAS and HEC HMS orderly. 04 Generate hydrology model (HEC HMS)4.1 Data for hydrologic modelling HEC-HMSRequired data for hydrologic modelling (HEC-HMS) are:• Digital Elevation Model• Land use and soli cover • Climate data (precipitation, temperature, evapotranspiration, humidity, sunshine)• Flow dataRequired data sourceDigital Elevation Model Alaska satellite facility (https://www.

asf.alaska.edu/)Land use and soil cover Urban Development AuthorityClimate data (precipitation, temperature, evapotranspiration, humidity, sunshine)Flow data Metrological Department of Sri LankaFlow data Irrigation Department of Sri Lanka4.1.2 Hydrologic Model DevelopmentRainfall runoff modelling was carried out with the help of HEC-HMS and ArcGIS. Detailed description regarding these software has been done in chapter 2. An overview of working mechanism of rainfall runoff model is shown with the help of schematic diagram below in figure 4.14.

Figure 4.14 Modelling approaches Rainfall Runoff ModellingThe methodology used for carrying out Rainfall Runoff Modelling can be described by categorizing them into two sections which are as follows.• 01 Creating Basin Model• 02 Developing Hydrological Parameters• 03 Hydrological Modelling01 Creating Basin ModelBasin model was created by ArcGISTerrain Pre-processingBefore carrying out terrain pre-processing, the input terrain data DEM was distinguished using DEM reconditioning. After this process, the DEM was pre-processed to originate sub-basins and drainage network of the catchment. The steps comprised were fill sinks, flow direction, flow accumulation, stream definition, stream segmentation, catchment grid delineation, catchment polygon processing, and adjoin catchment processing. After terrain pre-processing, HEC-HMS project was created. At first, a project point was defined at the downstream end of the watershed based on which the software delineated the project area. The resulting project area for Giriulla Badalgama catchment was 64.

8 square kilometers.Basin processingThe delineated sub-basins and rivers were merged based on river junctions. For each of the sub-basins and river, physical physiognomies were computed based on therefined DEM. The computed characteristics for river included river length and river slope andfor basin included basin slope, longest flow path to the basin, basin centroid, centroidelevation and centroid longest flowpath. To calculate basin slope, watershed slope wasrequired which was calculated using Arc Hydro tool.

02 Developing Hydrological ParametersWhen developing hydrological parameters, it was estimated by using the land and soil use data for sub basin. Various steps involved for developing hydrological parameters are follows. Select HMS process: HMS process for modelling loss, transform, base flow and routing were selected.4.1 model applicationThe daily stream flows were computed using the HEC-HMS 3.

4 model and theprepared data maps were used in the model. Watershed and meteorology information were combined to simulate the hydrologic responses. Data that are requiredfor the hydrological modeling of the catchment are; area of the catchment and thesub catchments, landuse patterns of the catchment areas, daily rainfall data, dailyriver flow data, monthly evaporation data, base flow, peaking coefficient, imperviousness, standard lag, initial deficit, constant rate, time of concentration, storagecoefficient and curve number. These values were taken considering the prominentsoil type in the catchment area. The main geological formations in the basin area arelaterite, unconsolidated sand, alluvium, peat deposits and crystalline basementrocks (Wijesekara and Kudahetty, 2010).4.2 model calibrationDunamale sub catchment was used to calibrate the model. Daily rainfall data forthree years (2005e2007), monthly base flows of the river, monthly evaporation dataof the catchment and the catchment area were inserted to the model.

The model wascalibrated employing three different approaches in order to determine the mostsuitable method for the study catchment. The flows simulated from each of themethods were tested statistically05 Generate hydraulic model (HEC RAS)5.1 Data for hydraulic modelling (HEC-RAS)Data required for hydraulic modelling HEC-RAS are:• Triangulated Irregular Network (TIN)• Land use• Flow data5.1.1 Triangulated Irregular Network (TIN)Digital Terrain Model in the form of Triangulated Irregular Network (TIN) is compulsory for the hydraulic analysis of river system. TIN must be of high-resolution with continuous surfaceand should signify bottom of the river and adjacent flood plains as all the cross-sectionaldata will be extracted from it.

TIN for both study areas were consequent from their particularDEM.5.1.2 Land Use The Manning’s value for different land use types used in both basins are listed in Table 4.1below.Table 4.1: Manning’s n values (Chow et al.

, 1988)Land Use Manning’s nCropland 0.05Pasture 0.05Barren land 0.04Water bodies 0.035Forest 0.1Developed areas 0.125.

13 Flow DataDischarge gages of Giriulla and Badalgama basin are shown in Figure 4.12 and Figure 4.13respectively. In case of Giriulla and Badalgama discharge gauges has been used for hydraulic analysis FLO-2Dmoves the flood volume around on a series of tilesfor overland flow or through stream segments forchannel routing. Flood routing in two dimensions is accomplished through a numerical integration ofthe continuity equation and the equations of motion5.06 Mapped flood inundation area.