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Table 1. Estimated daily rainfall (mm) for different return periods.

P: depth of precipitation for a specific return period (mm),

S: the watershed storage (mm), and can be calculated using Equation (2),

CN: the curve number.

The volume of the runoff was calculated for subbasins to show the local effect of runoff and was also calculated for the major basins to show the total volume of runoff flood. The volume of the runoff can be calculated using Equation (3)

${V}_{Q}=Q\cdot A$ (3)

where

VQ: Volume of runoff (m3),

Q: Depth of runoff (m),

A: Basin area (m2).

5. Results

The flood characteristics were calculated using the rainfall depth (P) equals 106.3 mm for a return period of 100 years as shown in Table 1. These characteristics include area, longest flow length and the runoff volume of the main basins in Jeddah watershed area as shown in Table 2. The results show that there are 7 major and 5 minor basins in Jeddah as shown in (Figure 7). The areas of the

Figure 7. Basins and main streams.

Table 2. Morphometric and flood parameters of basins.

major basins range from 59.04 to 555.5 square kilometers, and their longest flow paths range from 12.7 to 77.4 kilometers, while the areas of the minor basins range from 6.9 to 15.5 square kilometers, and their longest flow paths range from 7.48 to 10.23 kilometers. The total runoff volume was calculated and found to be more than 136 million cubic meters.

Refereeing to (Table 2), one can notice that the runoff depth (Q) is directly proportional to the curve number and inversely proportional to slope and the curve number has the great effect on it.

The proposed approach of using remote sensing and GIS applying the CN method for runoff coeffecient estimation has many advantages over other approaches. Firstly, it uses one software to perform all procedure steps. Secondly, only satellite image, soil maps and DEM are needed to calculate the runoff parameters. Thirdly, all needed calculations are done within the GIS environment using field calculation. Fourthly, it can be modeled using model builder so, runoff parameters estimation process can be efficient, faster, and easily performed for several return period scenarios and for any regions.

6. Conclusion

This research article presented an efficient approach to accurate determination of potential runoff coefficient in Jeddah city using remote sensing and GIS. The effects of land use, soil hydrological characteristics, surface slope, were considered in calculating runoff coefficient and consequently runoff depth and runoff volume. The results of the research show that the total runoff volume for a rainfall depth of 106.3 mm is 136.5 million m3. Results also show that the main factors affect the total flood volumes, are the basin area, and the flow length. Additionally, it has been concluded that the higher CN value and slope percent, the higher runoff and flood hazards.

Cite this paper

Khalil, R. (2017) Determination of Potential Runoff Coefficient Using GIS and Remote Sensing. Journal of Geographic Information System, 9, 752-762. https://doi.org/10.4236/jgis.2017.96046

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