U.S. flagAn official website of the United States government
                    Here's how you know **Official websites use .gov**
                            
                            A **.gov** website belongs to an official government organization in the United States.
 **Secure .gov websites use HTTPS**
                            
                            A **lock** (                            
                              A locked padlock                                                      
                            
                            ) or **https://** means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.


Menu Agricultural Research Service
						
                    U.S. DEPARTMENT OF AGRICULTURE
 Hydrology and Remote Sensing Laboratory: Beltsville, MD
 close



    Research

                    Research Projects
                                    Publications
                                    Collaborations
                                    News
                                    Software
                People

                    Staff Listing
                                    CareersSearch small
                    Search
            
            ARS Home
                                About ARS
                                Contact Us




ARS Home Northeast Area Beltsville, Maryland (BARC) Beltsville Agricultural Research Center Hydrology and Remote Sensing Laboratory Research Publications at this Location





- ARS National Programs
- Search for a scientific manuscript
- Search for a research project
- ARS Software
- Programs and Projects
- Collaborations
- Subjects of Investigation
- Publications
- People
- Research Sites
- Pesticide Volatilization
- Watershed Modeling
- Climate Change
- Soil Moisture
- Drought and ET
- HRSL Brochure

Title:   Author  item
                                            Sadeghi, Aliitem
                                            Beeson, Peteritem
                                            Daughtry, Craigitem
                                            Arnold, Jeffreyitem
                                            Anderson, Marthaitem
                                            HAIN, C - University Of Marylanditem
                                            Alfieri, Josephitem
                                            Kustas, William

                                                         - *Bill*
  Submitted to: Annual International SWAT Conference
                                    Publication Type: Abstract Only
                                    Publication Acceptance Date: 7/17/2013
                                    Publication  Date: 7/17/2013
                                    Citation: Sadeghi, A.M., Beeson, P.C., Daughtry, C.S., Arnold, J.G., Anderson, M.C., Hain, C., Alfieri, J.G., Kustas, W.P. 2013. Significance of uncertainty in evapotranspiration estimates on water balance modeling in SWAT [abstract].  SWAT International Conference, Book of Abstracts. p. 60.Interpretive Summary:
                                Technical Abstract: In water quality models, such as the Soil and Water Assessment Tool (or SWAT), accurate forcing of potential evapotranspiration (PET) is crucial for producing reasonable predictions of water budget components, sediment and other pollutant loads from larger river basins.  Methods and data, needed to compute PET, vary in space and time such as air temperature, vapor pressure, wind speed, and solar radiation.  In SWAT, PET is required as an input and is either computed internally by the weather generator using available weather data by a choice of three different methods: i) Priestly-Taylor; ii) Penman-Monteith; and iii) Hargreaves methods, or calculated by an external source and provided to SWAT as an input.  The actual ET (AET) is then calculated in SWAT based on available water, crop and soil moisture conditions.  Most often, the modelers rely on the models to simply match AET annual means, provided by the literature values, when calibrating the models due to sparse data (both temporal and spatial).  For this study, we used three methods to calibrate AET parameters: i) basin-wide/annual (using literature values); ii) subbasin/monthly (using Atmosphere-Land Exchange Inverse (ALEXI) model output); and iii) HRU/daily (using the NDVI/crop coefficient method from two in situ towers in corn and soybean fields).  After calibration, most PET inputs produced accurate AET estimates on a basin-wide, annual basis; however, on finer spatial and temporal scales, PET computed from local or regional data performed the best. The weather generator inputs were only able to capture the annual averages, not the variation throughout the growing season affecting biomass and yield estimates.  This research provides insight into the importance of correct estimations of both potential and actual ET for water balance components and for the application of physically-based watershed models.


Return to top


Connect with ARS Sign up


ARS Home
                            USDA.gov
                            Plain Writing
                            Policies & Links
                            Civil Rights Statements
                            FOIA
                            Accessibility Statement
                            Privacy Policy
                            Non-Discrimination Statement
                            Quality of Information
                            USA.gov
                            WhiteHouse.gov