4.6 Article

Effect of Watershed Delineation and Climate Datasets Density on Runoff Predictions for the Upper Mississippi River Basin Using SWAT within HAWQS

期刊

WATER
卷 13, 期 4, 页码 -

出版社

MDPI
DOI: 10.3390/w13040422

关键词

SWAT; watershed delineation; climate data; UMRB; HAWQS; runoff prediction; water components

资金

  1. NSFC-MWR-CTGC Joint Yangtze River Water Science Research Project [U2040213]

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The study found that the delineation of subbasins and hydrologic response units, as well as the density of climate data, significantly impact the accuracy of runoff predictions in watershed modeling. Results showed that simulations with 12-digit subbasins performed relatively worse, indicating variations in hydrological responses across a large basin.
The quality of input data and the process of watershed delineation can affect the accuracy of runoff predictions in watershed modeling. The Upper Mississippi River Basin was selected to evaluate the effects of subbasin and/or hydrologic response unit (HRU) delineations and the density of climate dataset on the simulated streamflow and water balance components using the Hydrologic and Water Quality System (HAWQS) platform. Five scenarios were examined with the same parameter set, including 8- and 12-digit hydrologic unit codes, two levels of HRU thresholds and two climate data densities. Results showed that statistic evaluations of monthly streamflow from 1983 to 2005 were satisfactory at some gauge sites but were relatively worse at others when shifting from 8-digit to 12-digit subbasins, revealing that the hydrologic response to delineation schemes can vary across a large basin. Average channel slope and drainage density increased significantly from 8-digit to 12-digit subbasins. This resulted in higher lateral flow and groundwater flow estimates, especially for the lateral flow. Moreover, a finer HRU delineation tends to generate more runoff because it captures a refined level of watershed spatial variability. The analysis of climate datasets revealed that denser climate data produced higher predicted runoff, especially for summer months.

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