| Title: | An assessment of mean areal precipitation methods of simulated stream flow: A SWAT Model performance assessment |
| Authors: | Zeiger, A. and J. Hubbart |
| Year: | 2017 |
| Journal: | Water |
| Volume (Issue): | 9(7) |
| Pages: | |
| Article ID: | 459 |
| DOI: | 10.3390/w9070459 |
| URL (non-DOI journals): | |
| Model: | SWAT |
| Broad Application Category: | hydrologic only |
| Primary Application Category: | climate data effects |
| Secondary Application Category: | calibration, sensitivity, and/or uncertainty analysis |
| Watershed Description: | 230 km^2 Hinkson Creek, located in Boone County in north central Missouri. |
| Calibration Summary: | |
| Validation Summary: | |
| General Comments: | |
| Abstract: | Accurate mean areal precipitation (MAP) estimates are essential input forcings for
hydrologic models. However, the selection of the most accurate method to estimate MAP can
be daunting because there are numerous methods to choose from (e.g., proximate gauge, direct
weighted average, surface-fitting, and remotely sensed methods). Multiple methods (n = 19) were
used to estimate MAP with precipitation data from 11 distributed monitoring sites, and 4 remotely
sensed data sets. Each method was validated against the hydrologic model simulated stream flow
using the Soil and Water Assessment Tool (SWAT). SWAT was validated using a split-site method and
the observed stream flow data from five nested-scale gauging sites in a mixed-land-use watershed
of the central USA. Cross-validation results showed the error associated with surface-fitting and
remotely sensed methods ranging from −4.5% to −5.1%, and −9.8% to −14.7%, respectively. Split-site
validation results showed the percent bias (PBIAS) values that ranged from −4.5% to −160%. Second
order polynomial functions especially overestimated precipitation and subsequent stream flow
simulations (PBIAS = −160) in the headwaters. The results indicated that using an inverse-distance
weighted, linear polynomial interpolation or multiquadric function method to estimate MAP may
improve SWAT model simulations. Collectively, the results highlight the importance of spatially
distributed observed hydroclimate data for precipitation and subsequent steam flow estimations.
The MAP methods demonstrated in the current work can be used to reduce hydrologic model
uncertainty caused by watershed physiographic differences. |
| Language: | English |
| Keywords: | SWAT; PRISM; TRMM; CHIRPS; MAP; mixed-land-use hydrology; precipitation |