A tool for assessing the weather dependency of outdoor recreation activities

This paper describes the creation of a Weather Dependency Framework (WDF) and its potential usefulness for managers and researchers. The WDF is a mechanism for understanding the multi-dimensional variables that influence the weather dependency of outdoor recreation activities.

The need for this work was evident because of the growing number of studies probing the general influence of weather on outdoor recreation without an organizing framework for making sense of those influences. A modified Internet-based Delphi process employing a panel of 27 experts in the areas of weather, climate, outdoor recreation, and natural resource management was facilitated in the summer of 2015 to develop the WDF.

Additionally, the panel of experts tested the WDF’s potential usefulness by applying it to three outdoor recreation activities that represent a likely spectrum of weather dependency. The paper concludes by considering other possible applications as well as recommendations for the WDF’s future development.

Management implications

The article suggests a new tool for managers and researchers interested in interpreting and understanding the weather dependency of outdoor recreation activities in a multitude of settings. The application of the WDF could enhance management and contribute to assessing the weather related needs and behaviors of recreationists by activity type to aid in effective protected area planning; predict recreation participation under specific weather conditions and for specific activities; inform natural resource and outdoor recreation managers about potential risks under certain weather conditions and for specific activities; plan site infrastructure improvements and adaptation; and conduct site assessments to aid festival and event planning in respective site selection. Overall, managers’ resulting use of the WDF may lead to reconsidering programs and policies, recreation impact mitigation, inspire weather-based planning initiatives, and predict land access trends.