"In the Sierra Nevada, the interplay between forest structure and snowpack, illuminated by lidar data, is critical for understanding and preserving vital water resources."
Posted: December 30, 2024
"In the Sierra Nevada, the interplay between forest structure and snowpack, illuminated by lidar data, is critical for understanding and preserving vital water resources."
In the Sierra Nevada, snowmelt is a key water resource for ecosystems and communities. This resource's sustainability hinges on understanding the relationship between forest structure and snowpack, a task enhanced by light detection and ranging (lidar) technology. Lidar provides high-resolution, spatially distributed measurements of forest structure and snow depth, essential for analyzing snowpack dynamics.
The author of the research highlights the significance of this approach: "Light detection and ranging (lidar) data provide the opportunity to understand these complex dynamics using high resolution, spatially distributed points that capture detailed forest structure and snow depth." This statement underscores the value of lidar in studying the interplay between forests and snow.
Climate shifts and increased disturbances like droughts and wildfires have altered forest structures, impacting snowpack accumulation and ablation. The study, focusing on the Sagehen Creek Basin in central Sierra Nevada, examines metrics such as leaf area index (LAI’) and gap width to tree height ratio in a 30-meter grid. Findings reveal that lower forest cover fraction (fVEG) and smaller gaps correlate with higher snow accumulation, whereas smaller gaps and higher fVEG can increase ablation. This pattern is consistent with predictions of more under-canopy ablation in regions like the Sierra Nevada.
The research also addresses the complexity of forest disturbances on snowpack. Analyzing data from before and after such disturbances shows variable patterns due to the combined effects of accumulation and ablation.
Through this study, the importance of forest structure in snowpack dynamics is brought to the forefront. The methodology developed, leveraging lidar data, provides a valuable tool for understanding forest-snow interactions. This approach can be applied to various vegetation and climate conditions, offering a strategic framework for forest management that prioritizes the preservation of vital water resources.
Read and download "Lidar-Derived Forest Metrics Are Critical for Predicting Snow Accumulation and Ablation in the Central Sierra Nevada, USA"
Author Cara Piske
Advisor Adrian Harpold