|Nejadhashemi, Amir - KANSAS STATE UNIV|
|Shirmohammadi, Adel - UNIV. OF MARYLAND|
|Montas, Hubert - UNIV. OF MARYLAND|
Submitted to: Journal Hydrologic Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 7, 2008
Publication Date: October 1, 2008
Citation: Nejadhashemi, A.P., Shirmohammadi, A., Montas, H.J., Sheridan, J.M., Bosch, D.D. 2008. Watershed Physical and Hydrological Effects on Baseflow Separation. Journal of Hydrologic Engineering. 13:971-980. Interpretive Summary: It is important to separate the fraction of the streamflow derived from water running along the land-surface from the fraction which flows through the ground prior to entering the stream. The water quality characteristics of the two flow components and the time required for each to reach the stream are usually quite different. The impact of different landscape characteristics on the streamflow components for South Georgia streams was investigated through statistical analysis. Incorporating the physical and hydrological characteristics of the watershed improved the accuracy of hydrograph separation techniques. It is anticipated that these improvements will contribute to the accuracy of streamflow separation estimation for large-scale watersheds with diverse soils and cover conditions.
Technical Abstract: There is a great interest in understanding groundwater-surface water interactions among hydrologists and water resources planners. One of the most challenging parts of this concept is the separation and quantification of baseflow from the streamflow hydrograph. This study is widely devoted to define and test the dominant forces within a watershed and incorporate their impact on streamflow components. The study area is located in the Coastal Plain of the Southeastern United States where separately measured surface and subsurface flow data are available for a field scale watershed for nine years (1970-1978). Sensitivity analysis was conducted with respect to the impact of different watershed characteristics on streamflow components and parameters of interest were identified. Improvement in the streamflow partitioning accuracy was accomplished by incorporating the most sensitive parameters in the streamflow partitioning approach using a regression equation built based on watershed physical (e.g., land use, soils) and hydrologic characteristics (e.g. rainfall, soil moisture). Using the new technique improved the streamflow partitioning method’s performance significantly.