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
 Agroecosystems Management Research: Ames, IA
 close



    Research

                    Research Projects
                                    Publications
                                    Collaborations
                                    News
                People

                    Staff Listing
                                    Careers


        


                    CRIS ProjectsSearch small
                    Search
            
            ARS Home
                                About ARS
                                Contact Us




ARS Home Midwest Area Ames, Iowa National Laboratory for Agriculture and The Environment Agroecosystems Management Research 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
                                            Malone, Robert

                                                         - *Rob*item
                                            YAGOW, GENE - Virginia Techitem
                                            Baffaut, Claireitem
                                            GITAU, MARGARET - Florida A & M Universityitem
                                            QI, ZHIMING - McGill University - Canadaitem
                                            AMATYA, DEVENDRA - Us Forest Service (FS)item
                                            PARAJULI, PREM - Mississippi State Universityitem
                                            Bonta, James

                                                         - *Jim*item
                                            Green, Timothy
  Submitted to: Transactions of the ASABE
                                    Publication Type: Peer Reviewed Journal
                                    Publication Acceptance Date: 12/3/2014
                                    Publication  Date: 12/1/2015
                                    Citation: Malone, R.W., Yagow, G., Baffaut, C., Gitau, M., Qi, Z., Amatya, D., Parajuli, P., Bonta, J.V., Green, T.R. 2015. Parameterization guidelines and considerations for hydrologic models. Transactions of the ASABE. 58(6):1681-1703.Interpretive Summary: Parameterization is an important and difficult task that can be defined as imparting knowledge of the physical processes of a system to a model and determining a set of parameter values for a hydrologic or water quality model application. A large amount of literature has been devoted to the use and development of these models over the years; however, few articles have been devoted to developing general parameterization guidelines. Therefore, we developed the following general parameterization guidelines to assist in hydrologic model application: use site specific measured or estimated parameter values where possible; focus parameterization efforts on the most uncertain and sensitive parameters; minimize the number of optimized parameters ("optimized parameters" are parameters that are adjusted to achieve a good fit between model output and field observations such as streamflow or soil water content); constrain parameter values to within justified ranges that conform to accepted literature sources; use multi-criteria to optimize parameter values (multi-criteria refers to more than one model output or target to compare with observed field data); use “soft” data to optimize parameter values (“soft” data are estimated or qualitative knowledge from experimentalists such as estimated evapotranspiration where site specific field measurements are unavailable); and use an initial warm-up period to allow the model output such as simulated soil water content to stabilize before comparing model results with field observations. A few soil and hydrologic parameters common to many models are briefly described along with discussion of measurement and estimation methods and how sensitive the models are to a change in the parameter values. Weather and management inputs such as rainfall and tillage are discussed because they are critical field or watershed information that must be imparted to the model. Several “case studies” briefly illustrate the parameterization guidelines. This research will help model users more consistently parameterize agricultural system models, which will result in more accurate model simulations that are more representative of the field or watershed conditions.
                                Technical Abstract: Imparting knowledge of the physical processes of a system to a model and determining a set of parameter values for a hydrologic or water quality model application (i.e., parameterization) is an important and difficult task. An exponential increase in literature has been devoted to the use and development of these models over the years; however, few articles have been devoted to developing general parameterization guidelines. Our objective is to develop general parameterization guidelines to assist in hydrologic model application. The following guidelines were extracted from reviewing the special collection of 22 articles (Moriasi et al., 2012) along with other relevant literature: use site specific measured or estimated values where possible; focus parameterization efforts on the most uncertain and sensitive parameters; minimize the number of optimized parameters; constrain parameter values to within justified ranges; use multi-criteria to optimize parameter values; use “soft” data to optimize parameters; and use an initial warm-up period to initialize state variables. A few soil and hydrologic parameters common to many models are briefly described along with discussion of measurement and estimation methods and parameter sensitivity (curve number, manning’s n, soil bulk density and porosity, soil hydraulic conductivity, soil field capacity and wilting point, leaf area index). Weather and management inputs are discussed because they are critical hydrologic system information that must be imparted to the model. Several “case studies” briefly illustrate the parameterization guidelines.


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