Document Type
Article
Date of Original Version
2020
Abstract
Runoff modeling of glaciated watersheds is required to predict runoff for water supply, aquatic ecosystem management and flood prediction, and to deal with questions concerning the impact of climate and land use change on the hydrological system and watershed export of contaminants of glaciated watersheds. A widely used pollutant loading model, Annualized Agricultural Non-Point Source Pollution (AnnAGNPS) was applied to simulate runoff from three watersheds in glaciated geomorphic settings. The objective of this study was to evaluate the suitability of the AnnAGNPS model in glaciated landscapes for the prediction of runoff volume. The study area included Sugar Creek watershed, Indiana; Fall Creek watershed, New York; and Pawcatuck River watershed, Rhode Island, USA. The AnnAGNPS model was developed, calibrated and validated for runoff estimation for these watersheds. The daily and monthly calibration and validation statistics (NSE > 0.50 and RSR < 0.70, and PBIAS ± 25%) of the developed model were satisfactory for runoff simulation for all the studied watersheds. Once AnnAGNPS successfully simulated runoff, a parameter sensitivity analysis was carried out for runoff simulation in all three watersheds. The output from our hydrological models applied to glaciated areas will provide the capacity to couple edge-of-field hydrologic modeling with the examination of riparian or riverine functions and behaviors.
Citation/Publisher Attribution
Tamanna, M., Pradhanag, S. M., Gold, A. J., Addy, K., Vidon, P. G. Bingner, R. L. (2020). Evaluation of AnnAGNPS Model for Runoff Simulation on Watersheds from Glaciated Landscape of USA Midwest and Northeast. Water, 12(12), 3525. doi: 10.3390/w12123525
Available at: https://doi.org/10.3390/w12123525
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Comment
Marzia Tamanna and Soni M. Pradhanang are from the Department of Geosciences.
Arthur J. Gold and Kelly Addy are from the Department of Natural Resources Science.