A Guideline for Successful Calibration and Uncertainty Analysis for Soil and Water Assessment: A Review of Papers from the 2016 International SWAT Conference

Abstract

Application of integrated hydrological models to manage a watershed's water resources are increasingly finding their way into the decision-making processes. The Soil and Water Assessment Tool (SWAT) is a multi-process model integrating hydrology, ecology, agriculture, and water quality. SWAT is a continuation of nearly 40 years of modeling efforts conducted by the United States Department of Agriculture (USDA) Agricultural Research Service (ARS). A large number of SWAT-related papers have appeared in ISI journals, building a world-wide consensus around the model's stability and usefulness. The current issue is a collection of the latest research using SWAT as the modeling tool. Most models must undergo calibration/validation and uncertainty analysis. Unfortunately, these sciences are not formal subjects of teaching in most universities and the students are often left to their own resources to calibrate their model. In this paper, we focus on calibration and uncertainty analysis highlighting some serious issues in the calibration of distributed models. A protocol for calibration is also highlighted to guide the users to obtain better modeling results. Finally, a summary of the papers published in this special issue is provided in the Appendix.

Multi-Objective Validation of SWAT for Sparsely-Gauged West African River Basins—A Remote Sensing Approach

“…While the 500 runs used to evaluate the sensitivity of the global calibration seem appropriate, we believe 1000 runs for the local sensitivity analysis might have been too low, especially considering the large number of parameters used, which influences the relative sensitivity of each parameter [84]. While [84] suggest between 500 and 1000 runs suffice, we believe the effects of more runs especially when using many parameters should be studied. Opening the parameter ranges further might lead to increased p-values and better calibrations/validations.…”

Hydrological Alteration Index as an Indicator of the Calibration Complexity of Water Quantity and Quality Modeling in the Context of Global Change

“…A three year warm-up period from 1997 to 1999, was taken into consideration to set up the initial variables' value. Hydrology and nitrate loads were automatically calibrated based on sensitivity analysis at 47 gauging stations including 19 hydrological stations and 28 physical-chemical stations over the period 2000-2005. p-value (determines the significance of the sensitivity) and t-stat (provides a measure of sensitivity) were calculated to identify the sensitive parameters [69]. The LH-OAT sensitivity analysis tool [70] was used in order to determine the sensitive parameters that are presented in Table S1.…”

“…The LH-OAT sensitivity analysis tool [70] was used in order to determine the sensitive parameters that are presented in Table S1. The SUFI-2 algorithm of SWAT-CUP [13,69,71] was selected to perform the automatic multi-site calibration. The SUFI-2 algorithm is known to identify an appropriate parameter set in a limited number of iterations [72].…”

Hydrologic responses to projected climate change in ecologically diverse watersheds of the Gulf Coast, United States

“…The use of multi-site observed data combined with multi-variables however has become more common and can improve the calibration and validation processes (Cao et al, 2006;Zhang et al, 2008). The use of observed data for model calibration and validation from multiple watershed outlets also represent the spatial hydrologic variabilities of each sub-basin and provide reasonable discharge results within a watershed (Abbaspour et al, 2018). The multi-objective AMALGAM calibration approach was successfully implemented using an HPC cluster.…”