Modeling of the stormwater runoff quantity and quality in Amman-Zarqua Basin, Jordan

  • Othman Al-MashaqbehEmail author
  • Malek Shorman
Original Paper


The Storm Water Management Model (SWMM) was applied to simulate stormwater runoff quantity and quality generated from different land uses at Amman-Zarqa Basin (AZB) over two winter seasons (October 25, 2012 to May 31, 2014). The model was calibrated and validated using several storm events over two winter seasons for a measured surface flow data at the inlet of King Talal Dam (KTD). The calibration and validation results showed good agreement between simulated and measured surface runoff flow data at AZB. The results showed that the total precipitation estimated by the model is about 1106 MCM during the study period. About 93.2% of precipitation (1031 MCM) is lost by infiltration and evaporation and 6.8% (75 MCM) is generated as runoff in AZB. The total predicted surface flow by the model was about 207 MCM compared with a measured value of 213 MCM in the basin. It is noticed that the contribution of surface runoff flow is about 36% of the total storage of KTD during the study period. Based on the results of this preliminary modeling study, pollutant loads (BOD5, COD, and TSS) carried by stormwater runoff were much higher than those by treated wastewater over the study period. The SWMM is a very effective model and has successfully modeled both hydraulic and pollutant loads generated from Amman-Zarqa Basin.


Rainfall-runoff simulations Stormwater modeling Pollutant loads SWMM 



The Jordan Scientific Research Fund (SRSF) (Grant no. EWE/1/08/2011)/Ministry of Higher Education and Scientific Research provided full support for this research.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Water and Environment CentreRoyal Scientific SocietyAmmanJordan
  2. 2.KEO International ConsultantsKuwaitKuwait

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