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Category:åÊMonitoring Change for Resource Management
Project Team: Lake Tahoe Water Resources
Team Location: NASA Ames Research Center ÛÒ Mountain View, California
Authors:
Nolan Cate
Anton Surunis
Chelsea Ackroyd
Mentors/Advisors:
Dr. Brian Coltin (NASA Ames Research Center)
Dr. Juan Torres-PÌ©rez (Bay Area Environmental Research Institute)
Abstract:
As global climate change continues to escalate and droughts become more frequent and severe, it becomes increasingly necessary to monitor and regulate available water resources. Lake Tahoe (California/Nevada) is an important reservoir for tourism, local ecosystems, and drinking water. Its nearly 5 million annual visitors contribute at least $300 million to the local economy, making it one of California’s most popular attractions. Decreasing water levels are a concern for residents, the economy, and a number of endangered species that live on Lake Tahoe’s shores, such as the yellow cress. Current methods of monitoring lake levels, however, rely on depth gauges that require time-intensive fieldwork to retrieve data and are limited in their spatial coverage. Satellite imagery provides a far greater spatial extent while still providing regular measurements. Utilizing satellite imagery from the Landsat program, the Lake Level Automated Monitoring Algorithm (LLAMA) is a continuous detection lake level monitoring algorithm that uses a Modified Normalized Difference Water Index (MNDWI), thermal band analysis, and visible band reflectance values processed through Google’s cloud-based geospatial program Earth Engine. In addition to a lake area measurement, LLAMA is able to show measurements of turbidity and algae levels over any given lake worldwide. Thus, LLAMA has the ability to provide water managers near real-time data regarding the turbidity, algae, and water levels for any lake or reservoir of sufficient size via Google Earth Engine.