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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Water Management and Systems Research » Research » Publications at this Location » Publication #286605
Title: Toward improved calibration of watershed models: multisite many objective measures of information

Author
item AHMADI, MEHDI - Colorado State University
item ARABI, MAZDAK - Colorado State University
item Ascough Ii, James
item FONTANE, DARRELL - Colorado State University
item ENGEL, BERNARD - Purdue University

Submitted to: Environmental Modelling & Software
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/2/2014
Publication Date: 6/10/2014
Citation: Ahmadi, M., Arabi, M., Ascough II, J.C., Fontane, D.G., Engel, B.A. 2014. Toward improved calibration of watershed models: multisite many objective measures of information. Environmental Modelling & Software. 59:135-145.

Interpretive Summary: This paper presents a computational framework for incorporation of disparate information from observed hydrologic responses at multiple locations into the calibration of watershed models. Application of the proposed framework for calibration of the Soil and Water Assessment Tool (SWAT) in the Eagle Creek watershed, Indiana, revealed that aggregation of streamflow and nitrate information measured at multiple locations within the watershed into a single measure of weighted errors would result in faster convergence to a solution with a lower overall objective function value than using multiple measures of information. However, the solution from adaptive Markov chain Monte Carlo method of DREAM was the only single objective approach that satisfied the conditions defined for characterizing system behavior. This study demonstrates the importance of the availability of hydrologic and water quality data at multiple locations, and also highlights the use of multiobjective approaches for proper calibration of watershed models that are used for pollutant source identification and watershed management.

Technical Abstract: This paper presents a computational framework for incorporation of disparate information from observed hydrologic responses at multiple locations into the calibration of watershed models. The framework consists of four components: (i) an a-priori characterization of system behavior; (ii) a formal and statistically correct formulation of objective function(s) of model errors; (iii) an optimization engine to determine the Pareto-optimal front for the selected objectives; and (iv) a multicriteria decision analysis tool to select optimal solutions from the Pareto-optimal front that are most consistent with the goals of the modeling study. Application of the proposed framework for calibration of the Soil and Water Assessment Tool (SWAT) in the Eagle Creek watershed, Indiana, revealed that aggregation of streamflow and nitrate information measured at multiple locations within the watershed into a single measure of weighted errors would result in faster convergence to a solution with a lower overall objective function value than using multiple measures of information. However, the solution from adaptive Markov chain Monte Carlo method of DREAM was the only single objective approach that satisfied the conditions defined for characterizing system behavior. In particular, aggregation of streamflow and nitrate responses undermined finding very good behavioral solutions for nitrate, primarily because of the significantly larger number of observations for streamflow. Aggregation of only nitrate responses into a single measure expedited finding better solutions; although, aggregation of data from nested sites appeared inappropriate because of correlated errors. This study demonstrates the importance of the availability of hydrologic and water quality data at multiple locations, and also highlights the use of multiobjective approaches for proper calibration of watershed models that are used for pollutant source identification and watershed management.