The Apache Longbow–Hellfire Missile Test at Yuma Proving Ground: Ecological Risk Assessment for Missile Firing

ABSTRACT

A multiple stressor risk assessment was conducted at Yuma Proving Ground, Arizona, as a demonstration of the Military Ecological Risk Assessment Framework. The focus was a testing program at Cibola Range, which involved an Apache Longbow helicopter firing Hellfire missiles at moving targets, that is, M60-A1 tanks. This article describes the ecological risk assessment for the missile launch and detonation. The primary stressor associated with this activity was sound. Other minor stressors included the detonation impact, shrapnel, and fire. Exposure to desert mule deer (Odocoileus hemionus crooki) was quantified using the Army sound contour program BNOISE2, as well as distances from the explosion to deer. Few effects data were available from related studies. Exposure-response models for the characterization of effects consisted of human “disturbance” and hearing damage thresholds in units of C-weighted decibels (sound exposure level) and a distance-based No-Observed-Adverse-Effects Level for moose and cannonfire. The risk characterization used a weight-of-evidence approach and concluded that risk to mule deer behavior from the missile firing was likely for a negligible number of deer, but that no risk to mule deer abundance and reproduction is expected.

Key Words:

• ecological risk assessment
• impulsive sound
• blast noise
• missile
• mule deer
• Sonoran desert
• military

ACKNOWLEDGMENTS

This research was funded by a contract from the U.S. Department of Defense Strategic Environmental Research and Development Program (SERDP) project CS-1054, A Risk Assessment Framework for Natural Resources on Military Training and Testing Lands, to Oak Ridge National Laboratory (ORNL), which is managed by UT-Battelle, LLC, for the U.S. Department of Energy under contract DE-AC05-00OR22725. We thank Bob Holst and John Hall for serving as project sponsors and Winifred Hodge Rose and Keturah Reinbold of the U.S. Army Corps of Engineers Construction Engineering Research Laboratory (CERL) for serving as Co-Principal Investigators. We also acknowledge the contributors of data, guidance, manuals, programming advice, text reviews, activity descriptions, and other assistance: Valerie Morrill, Chuck Botdorf, and Junior Kerns from YPG Environmental Sciences Division; Sergio Obregon, David McIntyre, and Bruce Goff from Jason & Associates,YPG Office; Rick Douglas and Bert Evans from YPG Aviation and Airdrop Systems; Dick Gebhart and Kim Majerus from CERL; Todd Kuiken, Paul Hanson, and Robert Washington-Allen from ORNL; and Catherine Stewart from the U.S. Army Center for Health Promotion and Preventive Medicine.

This article has been authored by a contractor of the U.S. Government under contract DE-AC05-00OR22725. Accordingly, the U.S. Government retains a nonexclusive, royalty-free license to publish or reproduce the published form of this contribution, or allow others to do so, for U.S. Government purposes.

William W. Hargrove is currently affiliated with the USDA Forest Service, Eastern Forest Environmental Threat Assessment Center, Asheville, NC, USA.

Notes

¹Statistics generated from BNOISE2 simulation of a Hellfire detonation under average weather conditions. Predicted variations in blast noise at 2432 meters is represented by the estimated percentage of blasts that would exceed various exposure levels. This variation is primarily due to assumed variations in weather conditions.

¹Larry Pater of the U.S. Army Corps of Engineers Construction Engineering Research Laboratory has approximately 20 years of experience in acoustics engineering and bioacoustics and provided these data.

²No reliable statistical data are available.

³Safety factors and other extrapolation factors are typically agreed to by regulatory agencies and other risk managers. Thus, the specific conversion factor of 10 is chosen for illustration only.

¹The authors have low confidence in the risk characterization for the Hellfire missile activity because of the paucity of relevant effects data.

²An effect is presumed to be negative if fewer than 20% of the mule deer are affected.

³Level of confidence in population-level effect would be low even if a large-scale behavioral effect was predicted.