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
 close



Research
                Research Home
                            National Programs
                            Research Projects
                            Scientific Manuscripts
                            International Engagement
                            Scientific Software/Models
                            Databases and Datasets
                            Office of Scientific Quality Review
            Media
                News & Features
                            Multimedia
                            Briefing Room
                            Down on the Farm
                            Press Room
                            Science in Your Shopping Cart
                            Scientific Discoveries
                            Tellus
                            Under the Microscope
            About ARS
                About ARS Home
                            Staff Directory
                            Labs and Research Centers (Map)
                            Headquarter Offices
                            Organizational Chart
                            Employee Services (REE Employees Only)
                            Office of Outreach, Diversity, and Equal Opportunity
            Work With Us
                Work With Us Home
                            ARS Vacancies at USAJOBS
                            Careers at ARS Information
                            Scientific Collaborations
                            Extramural Agreements
                            1890 Faculty Research Sabbatical ProgramSearch small
                    Search
            
            ARS Home
                                About ARS
                                Contact Us




ARS Home 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

Title:   Author  item
                                            SEXTON, AISHA - University Of Marylanditem
                                            Sadeghi, Aliitem
                                            SHIRMOHAMMADI, ADEL - University Of Marylanditem
                                            McCarty, Gregoryitem
                                            HIVELY, W - Us Geological Survey (USGS)
  Submitted to: Proceedings of the Watershed Technology Conference and Workshop, Improving Water Quality and the Environment
                                    Publication Type: Proceedings
                                    Publication Acceptance Date: 12/22/2009
                                    Publication  Date: 2/21/2010
                                    Citation: Sexton, A.M., Sadeghi, A.M., Shirmohammadi, A., McCarty, G.W., Hively, W.D. 2010. Modeling cover crop effectiveness on Maryland's Eastern Shore. In: Proceedings of the Watershed Technology, Improving Water Quality and Environment, February 21-24, 2010, San Jose, Costa Rica. 2010 CDROM.Interpretive Summary:
                                Technical Abstract: The value of watershed-scale, hydrologic/water quality models to ecosystem management is increasingly evident as more programs adopt these tools to evaluate the effectiveness of different management scenarios and their impact on the environment. Quality of precipitation data is critical for appropriate application of watershed models. In small watersheds, where no dense rain gauge network is available, modelers are faced with a dilemma to choose between different data sets. In this study, we used the German Branch (GB) watershed (~50 km2), which is included in the USDA-Conservation Effects Assessment Project (CEAP), to examine the implications of using surface rain gauge and Next Generation Radar (NEXRAD) precipitation data sets on the performance of the Soil and Water Assessment Tool (SWAT). The GB watershed is located in the Costal Plain of Maryland on the Eastern Shore of the Chesapeake Bay. Stream flow estimation results using surface rain gauge data revealed the importance of using rain gauges within the same direction as the storm pattern with respect to the watershed. In the absence of a spatially representative network of rain gauges within the watershed, NEXRAD data produced good estimates of stream flow at the outlet of the watershed. Three NEXRAD datasets, including 1) non-corrected (NC), 2) bias-corrected (BC), and 3) Inverse Distanced Weighted (IDW) corrected NEXRAD data, were produced. Nash-Sutcliffe Efficiency coefficients for daily stream flow simulation using these three NEXRAD data ranged from 0.46 to 0.58 during calibration, and 0.68 to 0.76 during validation. Overall, correcting NEXRAD with rain gauge data is promising to produce better hydrologic modeling results. Given the multiple precipitation datasets and corresponding simulations, we explored the combination of the multiple simulations using Bayesian Model Averaging. The results show that this Bayesian scheme can produce better deterministic prediction than any single simulation and provide reasonable uncertainty estimation. The optimal water balance obtained in this study is an essential precursor to acquiring realistic estimates of sediment and nutrient loads in future GB modeling efforts. The results presented in this study are expected to provide insights into selecting precipitation data for watershed modeling in small Coastal Plain catchments.


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