| Title: | Evaluation of satellite and gauge-based precipitation products through hydrologic simulation in Tigris River Basin under data-scarce environment |
| Authors: | Ajaaj, A.A., A.K. Mishra and A.A. Khan |
| Year: | 2019 |
| Journal: | Journal of Hydrologic Engineering |
| Volume (Issue): | 24(3) |
| Pages: | |
| Article ID: | 05018033 |
| DOI: | 10.1061/(ASCE)HE.1943-5584.0001737 |
| URL (non-DOI journals): | |
| Model: | SWAT |
| Broad Application Category: | hydrologic only |
| Primary Application Category: | climate data effects |
| Secondary Application Category: | hydrologic assessment |
| Watershed Description: | 445,656 km² Tigris River, which drains parts of northern Iraq (56.1%), southeast Turkey (24.5%), northwest Iran (19%) and southern Syria (0.4%) |
| Calibration Summary: | |
| Validation Summary: | |
| General Comments: | |
| Abstract: | This study investigates four widely used satellite and gauged-based precipitation products for hydrological evaluation in the poorly gauged Tigris River basin (TRB), with an area of 445,656 km2, using the Soil and Water Assessment Tool (SWAT) watershed model. The multiple precipitation data sources (PDSs) evaluated in this study include Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), Multisource Weighted-Ensemble Precipitation (MSWEP), Asian Precipitation Highly Resolved Observational Data Integration towards the Evaluation of water resources project (APHRODITE), and National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) data. The SWAT model was calibrated using three approaches to identify more realistic parameters. Overall, APHRODITE could capture the spatiotemporal distributions of daily precipitation with a correlation coefficient of 0.65, root-mean square error of 0.62 mm, and percent bias of 19.1%. In addition, APHRODITE also captured the monthly streamflow with reasonably accuracy for selected streamflow stations in the TRB with mean Nash-Sutcliffe efficiency of >0.65. Conversely, MSWEP overestimated and CPC underestimated the observed mean climatology, respectively, and had similar effects on monthly streamflow simulations. Among all the selected precipitation products, the relative performance of CPC is poor in comparison to other data sets. DOI: 10.1061/(ASCE)HE.1943-5584.0001737. © 2018 American Society of Civil Engineers. |
| Language: | English |
| Keywords: | Precipitation; Spatiotemporal variability; Soil and water assessment tool (SWAT); Remote sensing data. |