The Weather Dependency Framework (WDF): A tool for assessing the weather dependency of outdoor recreation activities
- Citation data:
Journal of Outdoor Recreation and Tourism, ISSN: 2213-0780, Vol: 18, Page: 88-99
- Publication Year:
- Business, Management and Accounting
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. The article suggests a new tool for the interpretation and consideration of weather dependency of outdoor recreation activities. The application could enhance the management and contribute To assess the weather related needs and behaviors of recreationists by activity type, To predict recreation participation under specific weather conditions and for specific activities, To inform about potential risks under certain weather conditions and for specific activities, To plan site infrastructure improvements and adaptation, To aid festival and event planning and the 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.