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ARS Home » Pacific West Area » Reno, Nevada » Great Basin Rangelands Research » Research » Research Project #426687

Research Project: Quantifying Relative Contributions of Salt Mobilization and Transport from Rangeland Ecological Sites in the Intermountain West

Location: Great Basin Rangelands Research

Project Number: 2060-13610-002-03-I
Project Type: Interagency Reimbursable Agreement

Start Date: Sep 15, 2014
End Date: Sep 14, 2019

Research on the topic of dissolved-solids (salts) loading to streams from rangelands is needed for identifying rangeland management practices that could reduce salt yields in the western United States. Specifically, there is a need to improve Ecological Sites Descriptions to better understand and predict sources and transport mechanisms of dissolved solids from federal rangelands as a function of State and Transition models used to guide management of federal rangelands. The ARS-BLM-University team will select Ecological Sites based on potential salinity contribution and quantify actual salt mobilization and transport processes by State within an Ecological Site. Goal two of the project is to enhance the Rangeland Hydrology and Erosion Model for assessing hydrology, erosion, and salt mobilization and loading responses associated with management of vegetation and provide this model to BLM for use in quantifying salt mobilization and transport from federal rangelands.

Rainfall simulation will be used to quantify the hydrologic, erosion, and salt mobilization and transport response on targeted Ecological Sites defined by the BLM within the semi-arid intermountain west region. Nine plots per state of the Ecological Site will be used to quantify salt mobilization and loading as a function of existing soil and vegetation condition. To quantify the hydrologic response of the different Ecological Sites (3 states per Ecological Site) we propose to evaluate, we will use a rainfall simulator (2 m wide x 6 m long) with rainfall rates at 2, 10, and 50-year return period rainfall events. We will follow, in general, the rainfall simulation procedures that were developed during the USDA Water Erosion Prediction Project to quantify soil characteristics, infiltration, runoff, and erosion rates. Rainfall simulation plots will be characterized prior to rainfall simulation to document vegetation (canopy and ground cover, standing biomass, and plant height). Post rainfall simulation ground cover will be reassessed to quantify changes in distribution in ground cover as a function of runoff and soil loss. Soil surface attributes (topography, bulk density, aggregate stability, surface texture, and soil salinity) will be quantified before and after rainfall simulation. Depth of wetting front will be quantified after each rainfall simulation experiment to estimate transport of salts to vadose zone. Three digital cameras will be mounted on the rainfall simulator to provide for a synoptic view of the entire plot (1-mm pixel resolution) and will be used to identify the gap frequency between shrubs. A digital camera will be located on a trolley mounted on the outside frame of the simulator (2 meter AGL) and a picture will be taken along the entire perimeter of the plot with 90% overlap for the development of a plot digital elevation model. Images will be taken before and after rainfall simulation allowing for determination of soil movement (both loss and deposition) to be calculated. In addition, time-lapse photography from the overhead cameras during the rainfall simulation will allow us to trace fluorescent dye applied at the top of the plot as it is transported down slope. We will quantify the number and distribution of concentrated flow paths and how they change as a function of rainfall intensity using commercially available image analysis software, such as ERDAS and ESRI (ArcGIS 10). These data will also be used to develop model parameters for RHEM for predicting runoff, sediment yield, and salt loads. RHEM model performance will be evaluated using the Nash and Sutcliffe coefficient by using observed data versus modeled predicted runoff volume, peak flows and sediment yield.