| Title: | Sensitivity of calibrated parameters and water resource estimates on different objective functions and optimization algorithms |
| Authors: | Kouchi, D.H., K. Esmaili, A. Faridhosseini, S.H. Sanaeinejad, D. Khalili and K.C. Abbaspour |
| Year: | 2017 |
| Journal: | Water |
| Volume (Issue): | 9(6) |
| Pages: | |
| Article ID: | 384 |
| DOI: | 10.3390/w9060384 |
| URL (non-DOI journals): | |
| Model: | SWAT |
| Broad Application Category: | hydrologic only |
| Primary Application Category: | calibration, sensitivity, and/or uncertainty analysis |
| Secondary Application Category: | hydrologic assessment |
| Watershed Description: | 13,000 km^2 Salman Farsi Dam drainage area and 51,000 km^2 Karkheh River, located respectively in southwest and northwest Iran. |
| Calibration Summary: | |
| Validation Summary: | |
| General Comments: | |
| Abstract: | The successful application of hydrological models relies on careful calibration and
uncertainty analysis. However, there are many different calibration/uncertainty analysis algorithms,
and each could be run with different objective functions. In this paper, we highlight the fact
that each combination of optimization algorithm-objective functions may lead to a different set of
optimum parameters, while having the same performance; this makes the interpretation of dominant
hydrological processes in a watershed highly uncertain. We used three different optimization
algorithms (SUFI-2, GLUE, and PSO), and eight different objective functions (R2, bR2, NSE, MNS,
RSR, SSQR, KGE, and PBIAS) in a SWAT model to calibrate the monthly discharges in two watersheds
in Iran. The results show that all three algorithms, using the same objective function, produced
acceptable calibration results; however, with significantly different parameter ranges. Similarly,
an algorithm using different objective functions also produced acceptable calibration results, but with
different parameter ranges. The different calibrated parameter ranges consequently resulted in
significantly different water resource estimates. Hence, the parameters and the outputs that they
produce in a calibrated model are “conditioned” on the choices of the optimization algorithm and
objective function. This adds another level of non-negligible uncertainty to watershed models, calling
for more attention and investigation in this area. |
| Language: | English |
| Keywords: | calibration; uncertainty analysis; conditional parameters; SUFI-2; GLUE; PSO |