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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 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

References

  1. 1. Gheith, H. and Sultan, M. (2002) Construction of a Hydrologic Model for Estimating Wadi Runoff and Groundwater Recharge in the Eastern Desert, Egypt. Journal of Hydrology, 263, 36-55. https://doi.org/10.1016/S0022-1694(02)00027-6

  2. 2. Mahmoud, S.H., Mohammad, F.S. and Alazba, A.A. (2013) A GIS-Based Approach for Determination of Potential Runoff Coefficient for Al-Baha Region, Saudi Arabia. 2013 International Conference on Sustainable Environment and Agriculture IPCBEE, 57, 97-102.

  3. 3. Wanielista, M.P. and Yousef, Y.A. (1993) Stormwater Management. John Wiley & Sons, Inc., New York.

  4. 4. Dawod, G.M, Mirza, M.N. and Al-Ghamdi, K.A. (2012) GIS-Based Estimation of Flood Hazard Impacts on Road Network in Makkah City, Saudi Arabia. Environmental Earth Sciences, 67, 2205-2215. https://doi.org/10.1007/s12665-012-1660-9

  5. 5. Sherwood, J.M. (1993) Estimation of Flood Volumes and Simulation of Flood Hydrographs for Ungagged Small Rural Streams in Ohio. Ohio Department of Transportation, Columbus.

  6. 6. Ahmad, I., Verma, V. and Verma, M.K. (2015) Application of Curve Number Method for Estimation of Runoff Potential in GIS Environment. 2015 2nd International Conference on Geological and Civil Engineering IPCBEE, 80, 16-20.

  7. 7. Xiao, B., Wang, Q.H., Fan, J., Han, F.P. and Dai, Q.H. (2011) Application of the SCS-CN Model to Runoff Estimation in a Small Watershed with High Spatial Heterogeneity. Pedosphere, 21, 738-749. https://doi.org/10.1016/S1002-0160(11)60177-X

  8. 8. Jasrotia, A. and Singh, R. (2006) Modeling Runoff and Soil Erosion in a Catchment Area, Using the GIS, in the Himalayan Region, India. Environmental Geology, 51, 9-37. https://doi.org/10.1007/s00254-006-0301-6

  9. 9. Saleh, A. and Al-Hatrushi, S. (2009) Torrential Flood Hazards Assessment, Management, and Mitigation, in Wadi Aday, Muscat Area, Sultanate of Oman, a GIS and RS Approach. Egyptian Journal of Remote Sensing and Space Science, 12, 81-86.

  10. 10. Chang, H., Franczyk, J. and Kim, C. (2009) What Is Responsible for Increasing Flood Risks? The case of Gangwon Province, Korea. Natural Hazards, 48, 339-354. https://doi.org/10.1007/s11069-008-9266-y

  11. 11. Pandey, A. and Sahu, A.K. (2009) Generation of Curve Number Using Remote Sensing and Geographic Information System. Geospatial World. https://www.geospatialworld.net/article/generationofcurvenumberusingremotesensingandgeographicinformationsystem/

  12. 12. Zhao, D.Q., Chen, J.N., Wang, H.Z., Tong, Q.Y., Cao, S.B. and Sheng, Z. (2009) GIS-based Urban Rainfall-Runoff Modeling Using an Automatic Catchment-Discretization Approach: A Case Study in Macau. Environmental Earth Sciences, 59, 465-472. https://doi.org/10.1007/s12665-009-0045-1

  13. 13. Chen, J., Hill, A. and Urbano, L. (2010) A GIS-Based Model for Urban Flood Inundation. Journal of Hydrology, 373, 184-192. https://doi.org/10.1016/j.jhydrol.2009.04.021

  14. 14. Sumarauw, J.S.F. and Ohgushi, K. (2012) Analysis on Curve Number, Land Use and Land Cover Changes and the Impact to the Peak Flow in the Jobaru River Basin, Japan. International Journal of Civil & Environmental Engineering, 12, 17-23. http://www.ijens.org/Vol_12_I_02/124102-3535-IJCEE-IJENS.pdf

  15. 15. Nasiri, A. and Alipur, H. (2014) Determination the Curve Number Catchment by Using GIS and Remote Sensing. International Journal of Environmental, Chemical, Ecological, Geological and Geophysical Engineering, 8, 342-345.

  16. 16. Bansode, A. and Patil, K.A. (2014) Estimation of Runoff by Using SCS Curve Number Method and ArcGIS. International Journal of Scientific & Engineering Research, 5, 1213-1229.

  17. 17. Viji, R., Prasanna, P.R. and Ilangovan, R. (2015) GIS Based SCS-CN Method for Estimating Runoff in Kundahpalam Watershed, Nilgries District, Tamilnadu. Earth Sciences Research Journal, 19, 59-64. https://doi.org/10.15446/esrj.v19n1.44714

  18. 18. Gajbhiye, S. (2015) Estimation of Surface Runoff Using Remote Sensing and Geographical Information System. International Journal of u- and e-Service, Science and Technology, 8, 113-122. https://doi.org/10.14257/ijunesst.2015.8.4.12

  19. 19. Subyani, A.M. and Hajjar, A.F. (2016) Rainfall Analysis in the Contest of Climate Change for Jeddah Area, Western Saudi Arabia. Arabian Journal of Geosciences, 9, 122. https://doi.org/10.1007/s12517-015-2102-2

  20. 20. Sharif, H.O., Al-Juaidi, F.H., Al-Othman, A., Al-Dousary, I., Fadda, E., Jamal-Uddeen, S. and Elhassan, A. (2016) Flood Hazards in an Urbanizing Watershed in Riyadh, Saudi Arabia. Geomatics, Natural Hazards and Risk, 7, 702-720. https://doi.org/10.1080/19475705.2014.945101

  21. 21. Youssef, A., Pradhan, B. and Sefry, S. (2014) Remote Sensing-Based Studies Coupled with Field Data Reveal Urgent Solutions to Avert the Risk of Flash Floods in the Wadi Qus (East of Jeddah) Kingdom of Saudi Arabia. Natural Hazards, 75, 1465-1488. https://doi.org/10.1007/s11069-014-1383-1

  22. 22. USDA (1986) Urban Hydrology for Small Watersheds. USDA, NRCS, CED, TR55. https://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb1044171.pdf

  23. 23. Subyani, A.M. and Al-Modayan, A.A. (2011) Flood Analysis in Western Saudi Arabia. Journal of King Abdulaziz University, 22, 17-36. https://doi.org/10.4197/Ear.22-2.2

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