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Using GIS for Flash Flood Hazard Mapping in Oman

By Ghazi Al-Rawas, Dr. Magaly Koch, and Dr. Farouk El-Baz

Introduction
Methodologies in geographic information systems (GIS) provide a way to address common environmental problems, including flash floods in arid areas. Flash floods are generated when precipitation saturates the drainage capacity of the basin slope and causes impoundment of the drainage network, resulting in exceptionally high discharge amounts at the basin's outlet.

Flash flood hazard map of the Saham basin in northern Oman (Figure 5).
Flash-flood-prone wadis (dry river channels cut into the terrain) can be assessed and delineated through the use of GIS. As a part of a research project, we used this methodology to determine the hazard of flash floods in the wadis of the Sultanate of Oman. Data used in this study consisted of two raster layers: a digital elevation model (DEM) at a 90m resolution, and an annual mean rainfall layer at a 1km resolution. These layers were used as input data for ArcView GIS software in order to delineate the watersheds and calculate the flow accumulation in each of the 28 major drainage basins of Oman (Figure 1).
      Several morphometric parameters were identified for each basin in order to estimate its flash flood potential. The morphometric analysis consisted of classifying and measuring the geometry of drainage basins and their components in a quantitative manner. There are many morphometric parameters describing the geometry of drainage basins that have an effect on the creation of flash floods. The GIS hydrologic modeling approach was used along with a DEM, plus Landsat TM images, in order to identify the following parameters in an automated way: flow accumulation, mean land slope, mean rainfall, and shape factor.

Methods
To calculate these identified parameters, a customized ArcView GIS hydrology program was employed. The parameters were calculated for each basin based upon the DEM at a 90m resolution. Applying this program to the DEM, watersheds and their topographic properties were delineated in a faster and highly accurate way, giving more reliable measurements than do traditional techniques - based on manual calculation - that use hard copies of maps.

1. Flow Accumulation
To calculate flow accumulation at the outlet of a stream, two steps are required. First, the program needs to fill sinks (if there are any) in the DEM data. Second, it must acquire the flow direction grid that shows the direction of flow for each cell in the DEM.
      Sinks: There are grid cells with no neighboring cells of lower elevation, so that there is no downslope flow path to a neighboring cell. This means the inclusion of flat areas and closed depressions that can be largely eliminated from sub-segment calculations. Some sinks may be landscape features, but most result from errors during DEM generation, plus the limited resolution of the DEM itself (Figure 2).
      Flow direction: The flow direction for every cell of the filled DEM is one of the keys to deriving the hydrologic characteristics of a surface. This function directs the flow out of each cell. There are eight output directions, each related to the eight adjacent cells where flow can travel. The flow direction is determined by finding the direction of steepest decent or maximum drop from each cell.
      Flow accumulation is calculated based upon the flow direction. This function calculates the accumulated flow as the weight of all cells flowing through each downslope cell in the output grid. The output of flow accumulation represents the amount of rain that would flow through each cell, assuming that all rain would become runoff and there is no interception, evapotranspiration, or loss to groundwater. This can also be viewed as the amount of rain that falls on the surface, upslope from each cell (ArcInfo 6.1 user's guide: cell-based modeling with GRID).
      Watershed: The watershed is created based upon the DEM, and by specifying the minimum number of the cells that comprise it. It is defined as an area that drains surface water into a common outlet as concentrated drainage. Watersheds are delineated from the flow direction layer. Other terms for watersheds include basin, catchment, or contributing area. This area is normally defined as the total area flowing into a given outlet, or pour point. Sub-watersheds are divisions based upon the drainage divide of a watershed. Pour points are the points at which water flows out of an area. This is the lowest point along the boundary of the watershed. Once the watersheds have been identified, they are used as measurement areas to calculate the parameters for estimating hazard floods in each respective basin (Figure 3).

2. Mean Land Slope
Mean-land-slope values are derived for each watershed. The slope plays a large role in the estimation of hazardous floods. High slopes can lead to flash flood generation. Using the DEM, the slope of each basin is derived. A raster layer of slope is used with an ArcInfo grid program to generate a theme that shows the mean slope of each sub-watershed within the basin.

3. Mean Rainfall
The rainfall coverage with 1km resolution for the whole country was used in this study. The mean rainfall was calculated for each sub-watershed within each basin. 4. Shape Factor Shape factor is a measure of the shape of a basin computed as the ratio of length of the basin to its computed area. The formula for such computation is as follows: Shape factor = (LB)2 / A.
      A comparative study conducted in three selected sites in the Egyptian desert suggests that circular basins create flash floods with sharp discharge peaks (quick flow), whereas elongated basins are generally characterized by slower flood-water flow (Table 1).

Results and Conclusions
Wadis that are expected to carry flash floods are ranked according to risk factors to establish the most dangerous places in the event of a flash flood. One example of these results is given here for the Saham basin of northern Oman (Number 5 in Figure 1). Figure 4 shows all parameters that were used to determine the hazardous wadis in this basin. These parameters are calculated and entered in the attribute table of the basin, and by setting a threshold for flash flood hazards. The most dangerous areas are identified based upon the calculated parameters of the basin and buffer (Figure 5). For example, the buffered wadis have the highest risk for generating flash floods as compared to others in the sub-watersheds of the Soham basin. The graduated red color represents the level of danger in terms of flow accumulation for every wadi. A TM image of this basin shows that a hazardous wadi leads to a dam. The shape factor shows that this wadi is more circular than the others, which is more dangerous in this case than the elongated one as mentioned above.
       This study further shows that the parameters related to flash flood hazards are more accurate and reliable when directly calculated from a DEM. Automation of morphometric parameters calculation is faster than with traditional techniques. The drainage network digitized from Landsat TM data, to the drainage network delineated directly from the DEM, shows similar patterns, especially the main flow-channel segments of the network. However, the flat areas are less well represented (straight lines) by the flow accumulation and the stream network. The flash-flood-hazard wadis were determined and mapped for most of the basins in the Sultanate of Oman. These maps may prove to be very important for infrastructure planning, tourism, and water management. For example, based upon these maps, the best location for building dams can more easily be identified in order to recharge wells and prevent flash flood occurrence, especially in residential areas.

About the Authors:
Mr. Ghazi Al-Rawas is a graduate student at the Center for Remote Sensing, Boston University. He is also an assistant lecturer at Sultan Qaboos University in Oman. He may be reached via e-mail at ghazi@crsa.bu.edu, or at ghazi@squ.edu.om.
Magaly Koch, Ph.D., is a research assistant professor at the Center For Remote Sensing at Boston University. His e-mail address is koch@crsa.bu.edu.
Farouk El-Baz, Ph.D., is the director of the Center for Remote Sensing, Boston University. His e-mail address is farouk@crsa.bu.edu.

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