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ARS Home » Pacific West Area » Tucson, Arizona » SWRC » Research » Research Project #441252

Research Project: Skutumpah Terrace Sagebrush Steppe Enhancement Hydrology/Erosion Study

Location: Southwest Watershed Research Center

Project Number: 2022-13610-012-052-I
Project Type: Interagency Reimbursable Agreement

Start Date: Dec 1, 2021
End Date: Sep 30, 2024

Objective:
• Quantify short-term and long-term effects of pinyon and juniper encroachment and removal treatments on vegetation, soils, ground cover, infiltration, and runoff and erosion rates across fine (0.5 m2) to coarse (tens of m2) spatial scales on sagebrush rangelands. • Improve understanding and knowledge of hydrologic and erosion process connectivity between areas of a hillslope under pinyon/juniper canopies and areas between tree canopies (intercanopy) for untreated and treated conditions. • Quantify short- and long-term effects of pinyon and juniper removal treatments on hillslope-scale hydrology and erosion through combination of field experiments and hydrology and erosion modelling (Rangeland Hydrology and Erosion Model, RHEM).

Approach:
Established methods of small (0.5 m2) and large (12 m2) plot artificial rainfall simulation and overland flow experiments (8 m2) will be used to quantify infiltration, runoff, rainsplash and sheetflow erosion, and concentrated flow erosion on one or more tree-encroached (pinyon and juniper) sagebrush site subjected to tree-removal practices (control, burned, cut, mastication). Experiments will be conducted immediately prior to treatments and within untreated control and treated areas 1 to 2 yr post-treatment. Treatment effects will be tested using a mixed model analysis of variance. Response variables will include infiltration, runoff, and erosion measured on small and large artificial rainfall plots and overland flow plots. Additional treatment response variables will include canopy and ground cover, soil properties, surface roughness, soil water repellency, and litter depth for each experimental plot. Correlations between dependent and independent variables will be defined using univariate and multivariate regression techniques to determine critical thresholds and drivers of treatment responses.