|Talebizadeh, Mansour - Orise Fellow|
|Starks, Patrick - Pat|
Submitted to: American Water Resources Association Summer Specialty Conference
Publication Type: Abstract Only
Publication Acceptance Date: 3/22/2016
Publication Date: 7/13/2016
Citation: Nelson, A.M., Moriasi, D.N., Talebizadeh, M., Steiner, J.L., Starks, P.J., Gowda, P. 2016. Evaluation of impact of length of calibration time period on the APEX model streamflow simulation. American Water Resources Association Summer Specialty Conference: GIS and Water Resources, Sacramento, California, July 11-13, 2016. Available: http://www.awra.org/meetings/Sacramento2016/doc/PP/Sess%2030%20abs.pdf.
Interpretive Summary: Abstract only.
Technical Abstract: Due to resource constraints, continuous long-term measured data for model calibration and validation (C/V) are rare. As a result, most hydrologic and water quality models are calibrated and, if possible, validated using limited available measured data. However, little research has been carried out to determine the impact of the length of available calibration data on the most important/sensitive parameters and performance of the models to simulate outputs of interest. This study used good quality long-term continuous measured streamflow data in Rock Creek watershed, located in northern Ohio, to quantify the impact of length of calibration data on calibration parameters and the performance of the Agricultural Policy/Environmental eXtender (APEX) model to simulate streamflow. Three short term (5-year), two mid-term (10-year), and one long term (25-year) streamflow calibration period scenarios were carried out. Preliminary results for a 30-year calibration period scenario indicated that runoff curve number (CN) residue adjustment parameter, soil evaporation coefficient, Hargreaves potential evapotranspiration (PET) equation coefficient, runoff curve number initial abstraction, exponential coefficient used to account for rainfall intensity on CN, Hargreaves PET equation exponent, return flow/(return flow + deep percolation), expands CN retention parameter, soil water lower limits, and maximum rainfall interception by plant canopy are the most sensitive APEX parameters for streamflow. Complete scenario results will be presented. These results will help model users estimate uncertainty associated with streamflow simulated. The ultimate goal is to extend these analyses to determine the most APEX sensitive parameters and their corresponding reasonable values that minimize uncertainty on simulated streamflow, sediments, nitrogen, and phosphorus. These results will be used by USDA to parameterize and validate APEX to support nation-wide deployment of the nutrient tracking tool (NTT), a user-friendly web-based computer program used to estimate reductions in nutrient losses to the environment associated with alternative practices.