Quantifying the influence of landscape ecology on wind erosion in the western United States using the APEX-LWE model

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  • Rangeland, a dominant land type in the arid desert regions of the western United States, is highly vulnerable to wind erosion due to its arid, erosive surface texture and fine sand properties. Fire, indiscriminate land use, and increased temperature due to climate change reduced the wind resistance of the rangeland, accelerating land degradation and dust emissions. This delineates the importance of quantifying and reproducing wind erosion processes in arid areas. This study evaluates the modeling approach of the Landscape Wind Erosion (LWE) model integrated into the process-oriented Agricultural Policy/Environmental eXtender (APEX) by comparing it with measured sediment flux data from wind erosion monitoring sites at the Jornada Experimental Range, NM (JER), Moab, UT and the San Luis Valley, CO (SLV). These sites cover typical weather conditions of the western United States rangelands and are thus representative of these environments. The model parameters were calibrated for each site by considering soil and vegetation properties and through sensitivity analysis. Using daily inputs of average wind speed and simulated vegetation gap (LWE-operational), the APEX-LWE model reproduced reasonably well the measured horizontal sediment flux (2015-2019) with an R2 of 0.53, 0.52, and 0.57 at the JER, Moab, and SLV sites, respectively. Using high-resolution daily wind speed distribution and measured vegetation gap distribution (LWE-measured), R2 values slightly increased to 0.64 (JER), 0.66 (Moab), and 0.68 (SLV) for the same period. The APEX-LWE model derives a consistent relationship between vegetation environment and wind erosion. These results suggest that the APEX-LWE model, through sufficient calibration, can produce a stable wind erosion process, reducing uncertainty in long timescale simulation. In particular, reliable LWE-operational modeling outcomes are potentially useful for areas with limited land monitoring data and will serve as a valuable decision-making tool for monitoring the effectiveness of policy and management initiatives.