2005 Salt Lake City Annual Meeting (October 16–19, 2005)

Paper No. 3
Presentation Time: 8:40 AM

USE OF A STREAMFLOW HYDROGRAPH TO ESTIMATE GROUND-WATER RECHARGE AND DISCHARGE IN HUMID SETTINGS


RUTLEDGE, Albert T. and RUTLEDGE, Albert T., U.S. Geological Survey, 433 National Center, Reston, VA 20192, rutledge@usgs.gov

An analytical model was developed to estimate the ground-water discharge component of the streamflow hydrograph. This model is intended for humid settings where the ground-water-flow system is driven by recharge to the water table and ground-water discharge to a gaining stream. After the hydrologist provides a preliminary estimate of the timing and quantity of recharge, the model is used to calculate ground-water discharge over time. A visual comparison is made between the calculated hydrograph and the streamflow hydrograph, and recharge is adjusted until a reasonable match between the two is achieved for periods when streamflow is considered to be only ground-water discharge. Recharge can be simulated as instantaneous or gradual and the principle of superposition is used to account for multiple events. The process of ground-water evapotranspiration can be approximated as a negative gradual recharge. The model can be used if streamflow is the only available dataset, but enhanced use of the model may be possible using ground-water level data, which can be used to ascertain the timing or magnitude of recharge. Other interpretations can be made on the basis of ground-water-level data but there are uncertainties related to the altitude of the outflow boundary, the relation between ground-water level and ground-water discharge, and other site-specific conditions. After calibration of the analytical model, the hydrologist can assemble a monthly tabulation of ground-water recharge and discharge. In regional studies with large datasets, the model might be used to provide fairly detailed results for a subset of the data. These results might be compared with results of fully automated hydrograph-separation methods that are used to analyze a larger dataset. This process might help corroborate results of the automated methods.