Numerical and conceptual evaluation of preferential flow in Zarqa River Basin, Jordan Academic Article uri icon

abstract

  • © 2019 European Regional Centre for Ecohydrology of the Polish Academy of Sciences Farmers along the main reach of the Zarqa River Basin (ZRB) commonly utilize treated wastewater for irrigation. Deep percolation is expected to occur as a result of irrigation, and it is expected that preferential flow pathways may facilitate the downward movement of irrigation water. Therefore, the aim of this research was to investigate the susceptibility of soils near Zarqa River to preferential flow, and the HYDRUS and Soil and Water Assessment Tool (SWAT) models were used. The methodology consisted of taking tension infiltrometer measurements along the Zarqa River to determine the main physical properties relevant to preferential flow, such as infiltration rate and macroscopic capillary length, followed by investigating the downward water movement using HYDRUS and SWAT. The HYDRUS simulations were conducted using single porosity (SP) and dual porosity (DP) constitutive functions pertaining to matrix and preferential flow, respectively. The in situ tension infiltrometer measurements were used to parameterize the surface layer of the HYDRUS DP model. HYDRUS simulations showed that preferential flow occurring in the surface layer of the soil profile controlled the vertical movement of soil water in excess of field capacity. The comparison between SWAT, SP and DP showed that both SWAT and DP were capable of simulating preferential flow in arid watersheds. However, SWAT simulations of lateral discharge and deep percolation resemble that of the DP only when the evaporation soil compensation factor (ESCO) was set to a value of 0.8 and the length of the soil slope was set to its maximum value. This research recommends using HYDRUS model to verify SWAT model predictions of soil water redistribution in the soil profile and to improve the parameterization of the SWAT model. The research also suggests an approach for the combined use of both models.

author list (cited authors)

  • Rahbeh, M., Srinivasan, R., & Mohtar, R.

citation count

  • 5

publication date

  • April 2019