i-Tree Hydro is designed for users interested in watershed scale analyses of vegetation and impervious cover effects on hydrology. The most recent version of Hydro provides users with several key improvements including a more user-friendly interface with integrated help, executive summary reporting and qualitative modeling capabilities at the city scale.
What is Hydro?
Hydro is a stand-alone application designed to simulate the effects of changes in tree and impervious cover characteristics within a defined watershed on stream flow and water quality. It was designed specifically to handle urban vegetation effects so urban natural resource managers and urban planners can quantify the impacts of changes in tree and impervious cover on local hydrology to aid in management and planning decisions.
It is also designed for ease of use, utilizing available data sets as inputs to the model. Hydro is a combination of two modules. A base module designed to simulate hourly changes in stream flow due to changes in urban tree and impervious cover characteristics and a water quality module that uses outputs from the base program to simulate changes in water quality.
i-Tree Hydro enhancements
Hydro Learning Resources and FAQs
What will Hydro tell me?
Given various changes in tree and impervious cover characteristics provided by the users, Hydro will quantify and illustrate hourly and total changes in stream flow and water quality. Data will be presented in tabular summaries as well as through graphs (hydrographs) that illustrate the changes between the base case (conditions as they are now) and an alternate case specified by the user.
Why is the information produced by Hydro important?
Urbanization significantly alters stream flows and water quality due to increased impervious surfaces, increased pollutants emitted from various sources and decreases in natural vegetation cover. These changes lead to increased runoff and flashiness of stream flow after storms, potential flooding issues, and poorer water quality that affect human health and well-being.
Through the Clean Water Act, the U.S. Environmental Protection Agency has designated various water quality requirements that affect city managers. As trees affect the environment, the ability to quantify these effects could lead to the incorporation of urban vegetation management strategies (and potential funding) to help meet these environmental regulations. Urban trees can potentially be used to meet clean water regulations associated with Total Maximum Daily Loads (TMDLs) and storm water programs.
How can Hydro help urban natural resource managers & urban planners?
The Hydro model could be used to determine how various best management practices (including urban forestry) affect water quality. In addition, by altering the precipitation inputs to simulate storms of various intensities, the model can be used to determine how management practices can affect local flooding. Model results can be used to improve urban forest management and urban planning and design to help improve water quality and reduce the risk of flooding.
Visit the Green Infrastructure Modeling in i-Tree Hydro web page developed by SUNY College of Environmental Science and Forestry Team members to see an example of how i-Tree Hydro can be used to simulate hydrologic impacts of green infrastructure.
Who developed Hydro?
The i-Tree Hydro model was originally developed by Drs. Jun Wang SUNY College of Environmental Science and Forestry (SUNY-ESF), Ted Endreny (SUNY-ESF), and David J. Nowak, USDA Forest Service, Northern Research Station (USFS-NRS). The model code has been improved and integrated within i-Tree based on the work of Michael Kerr (Davey Institute), Yang Yang (SUNY-ESF), Sanyam Chaudhary (Syracuse University), and Rahul Kumbhar (Syracuse University). Many other individuals have contributed to the design, development, and testing process, including Andrew Lee (SUNY-ESF), Robert Hoehn (USFS-NRS), Tian Zhou (SUNY-ESF), Alexis Ellis (Davey Institute), Mike Binkley (Davey Institute), Lianghu Tian (Davey Institute), Scott Maco (Davey Institute), Dr. Jim Fawcett (Syracuse University), Yu Chen (Syracuse University), Shannon Conley (Syracuse University) and Tom Taggart (SUNY ESF).