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contributor authorAws A. Ajaaj; Ashok K. Mishra; Abdul A. Khan
date accessioned2019-03-10T12:11:31Z
date available2019-03-10T12:11:31Z
date issued2019
identifier other%28ASCE%29HE.1943-5584.0001737.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4255056
description abstractThis 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.
publisherAmerican Society of Civil Engineers
titleEvaluation of Satellite and Gauge-Based Precipitation Products through Hydrologic Simulation in Tigris River Basin under Data-Scarce Environment
typeJournal Paper
journal volume24
journal issue3
journal titleJournal of Hydrologic Engineering
identifier doi10.1061/(ASCE)HE.1943-5584.0001737
page05018033
treeJournal of Hydrologic Engineering:;2019:;Volume ( 024 ):;issue: 003
contenttypeFulltext


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