OJAppS  Vol.5 No.7 , July 2015
Long Term Soil and Water Assessment Tool (SWAT) Calibration from an Ecohydrology Perspective
ABSTRACT
The performance on prediction by mathematical models which represent the conceived image of a system such as hydrology is oftentimes represented through calibration and verification processes. Oftentimes a best fit between observed and predicted flows is obtained through correlation coefficient (R2) and the Nash Sutcliffe model efficiency (NSE) by minimizing the average Root Mean Square Error (RMSE) of the observed versus simulated flows. However, these days, a new paradigm is emerging wherein accounting for the flow variability for the protection of freshwater biodiversity and maintenance of goods and services that rivers provide is paramount. Therefore, from an ecohydrology perspective, it is not clear if the existing method of model calibration meets the needs of the riverine ecosystem at its best. Thus, this study investigates and proposes a methodology using entropy theory to gage the calibration of Soil and Water Assessment Tool (SWAT) from an ecohydrology perspective characterized by the natural flow-regime paradigm: Indicators of Hydrologic Alteration.

Cite this paper
Mylevaganam, S. , Srinivasan, R. and Singh, V. (2015) Long Term Soil and Water Assessment Tool (SWAT) Calibration from an Ecohydrology Perspective. Open Journal of Applied Sciences, 5, 344-354. doi: 10.4236/ojapps.2015.57035.
References
[1]   Moriasi, D.N., Arnold, J.G., Van Liew, M.W., Bingner, R.L., Harmel, R.D. and Veith, T.L. (2007) Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations. Transactions of the ASABE, 50, 885- 900.
http://dx.doi.org/10.13031/2013.23153

[2]   Gassman, P.W., Reyes, M.R., Green, C.H. and Arnold, J.G. (2007) The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions. Transactions of the ASABE, 50, 1211-1250. http://dx.doi.org/10.13031/2013.23637

[3]   Balascio, C.C., Palmeri, D.J. and Gao H. (1998) Use of a Genetic Algorithm and Multi-Objective Programming for Ca- libration of a Hydrologic Model. Transactions of the ASAE, 41, 615-619. http://dx.doi.org/10.13031/2013.17229

[4]   Wang, X. and Melesse, A.M. (2005) Evaluation of the SWAT Model’S Snowmelt Hydrology in a Northwestern Minnesota Watershed. Transactions of the ASABE, 48, 1359-1376.
http://dx.doi.org/10.13031/2013.19194

[5]   Borah, D.K. and Bera, M. (2004) Watershed-Scale Hydrologic and Nonpoint-Source Pollution Models: Review of Applications. Transactions of the ASAE, 47, 789-803.
http://dx.doi.org/10.13031/2013.16110

[6]   Krause, P., Boyle, D.P. and Base, F. (2005) Comparison of Different Efficiency Criteria for Hydrological Model Assessment. Advances in Geosciences, 5, 89-97.
http://dx.doi.org/10.5194/adgeo-5-89-2005

[7]   Naiman, R.J., Bunn, S.E., Nilsson, C., Petts, G.E., Pinay, G. and Thompson, L.C. (2002) Legitimizing Fluvial Ecosystems as Users of Water: An Overview. Environmental Management, 30, 455-467. http://dx.doi.org/10.1007/s00267-002-2734-3

[8]   Postel, S. and Richter, B.D. (2003) Rivers for Life: Managing Water for People and Nature. Island Press, Washington DC.

[9]   Poff, N.L., Allan, J.D., Bain, M.B., Karr, J.R., Prestegaard, K.L., Richter, B.D., Sparks, R.E. and Stromberg, J.C. (1997) The Natural Flow Regime: A Paradigm for River Conservation and Restoration. BioScience, 47, 769-784. http://dx.doi.org/10.2307/1313099

[10]   Lytle, D.H. and Poff, N.L. (2004) Adaptation to Natural Flow Regimes. Trends in Ecology and Evolution, 19, 94-100. http://dx.doi.org/10.1016/j.tree.2003.10.002

[11]   Richter, B.D., Baumgartner, J.V., Powel, J. and Braun, D.P. (1996) A Method for Assessing Hydrologic Alteration within Ecosystems. Conservation Biology, 10, 1163-1174.
http://dx.doi.org/10.1046/j.1523-1739.1996.10041163.x

[12]   Singh, V.P. (1998) The Use of Entropy in Hydrology and Water Resources. Hydrological Processes, 11, 587-626.
http://dx.doi.org/10.1002/(SICI)1099-1085(199705)11:6<587::AID-HYP479>3.0.CO;2-P

[13]   Yager, R.R. (1999) Induced Ordered Weighted Averaging Operators. IEEE Transactions on Systems, Man and Cybernetics, 29, 141-150. http://dx.doi.org/10.1109/3477.752789

 
 
Top