Applying the Soil Water Assessment Tool to 5th Canadian Division Support Base Gagetown

2014 ◽  
Vol 49 (4) ◽  
pp. 372-385
Author(s):  
Shawn Burdett ◽  
Michael Hulley ◽  
Andy Smith

A hydrologic and water quality model is sought to establish an approach to land management decisions for a Canadian Army training base. Training areas are subjected to high levels of persistent activity creating unique land cover and land-use disturbances. Deforestation, complex road networks, off-road manoeuvres, and vehicle stream crossings are among major anthropogenic activities observed to affect these landscapes. Expanding, preserving and improving the quality of these areas to host training activities for future generations is critical to maintain operational effectiveness. Inclusive to this objective is minimizing resultant environmental degradation, principally in the form of hydrologic fluctuations, excess erosion, and sedimentation of aquatic environments. Application of the Soil Water Assessment Tool (SWAT) was assessed for its ability to simulate hydrologic and water quality conditions observed in military landscapes at 5th Canadian Division Support Base (5 CDSB) Gagetown, New Brunswick. Despite some limitations, this model adequately simulated three partial years of daily watershed outflow (NSE = 0.47–0.79, R2 = 0.50–0.88) and adequately predicted suspended sediment yields during the observation periods (%d = 6–47%) for one highly disturbed sub-watershed in Gagetown. Further development of this model may help guide decisions to develop or decommission training areas, guide land management practices and prioritize select landscape mitigation efforts.

2011 ◽  
Vol 54 (5) ◽  
pp. 1677-1684 ◽  
Author(s):  
P. Tuppad ◽  
K. R. Douglas-Mankin ◽  
T. Lee ◽  
R. Srinivasan ◽  
J. G. Arnold

2008 ◽  
Vol 7 (5) ◽  
pp. 453-466 ◽  
Author(s):  
Étienne Lévesque ◽  
Luc Lamontagne ◽  
Ann Van Griensven ◽  
Peter A. Vanrolleghem ◽  
François Anctil

2021 ◽  
Vol 5 (2) ◽  
pp. 173-182
Author(s):  
Shehu Usman Haruna ◽  
Aliyu Kasim Abba ◽  
Rabi'u Aminu

The present study compared the performance of two different models for streamflow simulation namely: Soil Water Assessment Tool (SWAT) and the Artificial Neural Network (ANN). During the calibration periods, the Nash-Sutcliff (NS) and Coefficient of Determination (R2) for SWAT was 0.74 and 0.81 respectively, whereas for ANN, it was 0.99 and 0.85 respectively. The ANN performs better during the validation period as the result revealed with NS and R2 having 0.98 and 0.89 respectively, while for the SWAT model it was 0.71 and 0.74 respectively. Based on the recommended comparison of graphical and statistical evaluation performances of both models, the ANN model performed better in estimating peak flow events than the SWAT model in the Upper Betwa Basin. Furthermore, the rigorous time required and expertise for calibration of the SWAT is much less as compared with the ANN. Moreover, the results obtained from both models demonstrate the performances of the


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