Abstract

The Automated Geospatial Watershed Assessment Tool (AGWA) and the Rangeland Hydrology Erosion Model (RHEM) were used to evaluate conservation practices on the Cienega Creek watershed (CCW) that were implemented under the Conservation Effects Assessment Project (CEAP) on Grazing Lands. CEAP on Grazing Lands is a multi-agency effort to quantify the environmental effects of conservation practices and programs, and develop the science base for managing rangelands for environmental quality using conservation practices (Spaeth et al. 2013). The evaluation was performed on the CCW and the Empire Ranch, located in southeastern Arizona, where numerous conservation practices have been implemented to achieve their management goals of maintaining desired plant communities and watershed processes. To assess the effects of the conservation practices on long-term soil and water loss, RHEM was applied to the entire CCW using National Resources Inventory (NRI) data. Four analysis periods were selected based on climatic contrasts, conservation spending, and availability of NRI sample points. The CCW results showed that the simulations using RHEM parameters derived from NRI data could be used to demonstrate the impact of climate on vegetation condition and sediment yield. A subsection, dubbed “select treatment areas,” of the CCW, which received extensive treatments with brush removal, prescribed burns, and stock ponds, was assessed using remotely sensed data. The select treatment areas were modeled over three different periods, representing preconservation spending, postconservation spending, and later postconservation spending. Remote sensing was capable of detecting and estimating the changes in vegetation cover from brush removal and prescribed burns. Simulations of sediment yield using pre- and posttreatment data indicated a modest reduction in sediment yield. Simulations in the select treatment areas indicated mechanical brush treatments were typically more effective than prescribed burns for improving watershed condition as estimated by reductions in sediment yield, but were more costly to implement. Stock ponds had a larger impact on sediment yield than the land treatments. The assessment demonstrated the utility of remotely sensed estimates of plant growth form and cover for model inputs to estimate changes in runoff and sediment yield with changing cover conditions over large areas.

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