Keywords

SWAT, precipitation, hydrology, watershed modeling

Start Date

26-6-2018 5:00 PM

End Date

26-6-2018 7:00 PM

Abstract

Precipitation is one of the major inputs for hydrological modeling and often it is the most important driver in watershed models. Even though precipitation measurements at gages are considered as the most accurate datasets, gages are unable to capture the spatial and temporal variability of precipitation. Interpolated gridded precipitation data sources have become increasingly available as alternatives to ground based measurements that address spatiotemporal issues. However, the use of gridded precipitation sources is limited, mainly due to mismatch of these gridded data to the requirements of models and difficulty in processing. This study uses the U.S. EPA Hydrologic Micro Services (HMS) infrastructure to acquire and process precipitation inputs for Soil and Water Assessment Tool (SWAT) from Daily Surface Weather Data (DAYMET), North American Land Data Assimilation System (NLDAS), Global Land Data Assimilation System (GLDAS), and Precipitation-elevation Regressions on Independent Slopes Model (PRISM). Global Historical Climate Network-Daily (GHCN-D), an integrated database of daily climate summaries from ground-based stations across the globe, was used as reference data to evaluate how closely the gridded data represent precipitation. SWAT was used to identify the effects of different sources on hydrological processes in an agricultural catchment. The preliminary results indicated that there were considerable differences among GHCN-D (the observed data) and the gridded data in terms of number and consecutive wet and dry days. PRISM and DAYMET closely matched GHCN-D in those indices, while NLDAS and GLDAS showed much weaker correlations with GHCN-D. Similar differences were also observed for SWAT streamflow simulations.

Stream and Session

E1: Coupled Surface-Subsurface Hydrologic Modelling

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Jun 26th, 5:00 PM Jun 26th, 7:00 PM

Poster Abstract: Effects of precipitation data source selection on SWAT hydrologic simulation

Precipitation is one of the major inputs for hydrological modeling and often it is the most important driver in watershed models. Even though precipitation measurements at gages are considered as the most accurate datasets, gages are unable to capture the spatial and temporal variability of precipitation. Interpolated gridded precipitation data sources have become increasingly available as alternatives to ground based measurements that address spatiotemporal issues. However, the use of gridded precipitation sources is limited, mainly due to mismatch of these gridded data to the requirements of models and difficulty in processing. This study uses the U.S. EPA Hydrologic Micro Services (HMS) infrastructure to acquire and process precipitation inputs for Soil and Water Assessment Tool (SWAT) from Daily Surface Weather Data (DAYMET), North American Land Data Assimilation System (NLDAS), Global Land Data Assimilation System (GLDAS), and Precipitation-elevation Regressions on Independent Slopes Model (PRISM). Global Historical Climate Network-Daily (GHCN-D), an integrated database of daily climate summaries from ground-based stations across the globe, was used as reference data to evaluate how closely the gridded data represent precipitation. SWAT was used to identify the effects of different sources on hydrological processes in an agricultural catchment. The preliminary results indicated that there were considerable differences among GHCN-D (the observed data) and the gridded data in terms of number and consecutive wet and dry days. PRISM and DAYMET closely matched GHCN-D in those indices, while NLDAS and GLDAS showed much weaker correlations with GHCN-D. Similar differences were also observed for SWAT streamflow simulations.