Prediction of Runoff in Watersheds Located within Data-Scarce Regions

Abdulnoor A.J. Ghanim, Salmia Beddu, Teh Sabariah Binti Abd Manan, Saleh H. Al Yami, Muhammad Irfan, Salim Nasar Faraj Mursal, Nur Liyana Mohd Kamal, Daud Mohamad, Affiani Machmudah, Saba Yavari, Wan Hanna Melini Wan Mohtar, Amirrudin Ahmad, Nadiah Wan Rasdi, Taimur Khan

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


The interest in the use of mathematical models for the simulation of hydrological processes has largely increased especially in the prediction of runoff. It is the subject of extreme research among engineers and hydrologists. This study attempts to develop a simple conceptual model that reflects the features of the arid environment where the availability of hydrological data is scarce. The model simulates an hourly streamflow hydrograph and the peak flow rate for any given storm. Hourly rainfall, potential evapotranspiration, and streamflow record are the significant input prerequisites for this model. The proposed model applied two (2) different hydrologic routing techniques: the time area curve method (wetted area of the catchment) and the Muskingum method (catchment main channel). The model was calibrated and analyzed based on the data collected from arid catchment in the center of Jordan. The model performance was evaluated via goodness of fit. The simulation of the proposed model fits both (a) observed and simulated streamflow and (b) observed and simulated peak flow rate. The model has the potential to be used for peak discharges’ prediction during a storm period. The modeling approach described in this study has to be tested in additional catchments with appropriate data length in order to attain reliable model parameters.

Original languageEnglish
Article number7986
JournalSustainability (Switzerland)
Issue number13
Publication statusPublished - 1 Jul 2022


  • catchment modeling
  • design flood
  • hydrologic modelling
  • rainfall–runoff relation


Dive into the research topics of 'Prediction of Runoff in Watersheds Located within Data-Scarce Regions'. Together they form a unique fingerprint.

Cite this