Advanced Remote Sensing and Modeling Approaches for Estimating Reservoir Evaporation: A Case Study of Lake Texana, Texas

Abstract Submission: This study explores innovative methods for estimating evaporation from reservoirs using remote sensing technologies, with a focus on Lake Texana in Texas. Recognizing the significant impact of evaporation on water resources, the study leverages the capabilities of Google Earth Engine (GEE) to process satellite imagery and generate accurate measurements of reservoir surface areas and evaporation rates. The research utilizes the Modified Normalized Difference Water Index (MNDWI) to effectively identify water bodies within satellite images. To refine evaporation estimates, the study incorporates advanced methods like the Penman-Monteith equation, which uses meteorological data such as temperature, humidity, wind speed, and solar radiation for more precise calculations. These methods are cross-validated with satellite-derived evaporation estimates from platforms like Sentinel-2, and Landsat 8, providing a comprehensive comparison of evaporation rates across different spatial resolutions and time scales. The integration of multiple data sources enhances the accuracy and scalability of evaporation estimates, addressing the limitations of conventional methods. By analyzing data from 2013 to 2023, this approach offers a more efficient and scalable solution to monitor reservoir dynamics and manage water resources effectively. The findings demonstrate the potential of using GEE, coupled with advanced models, for large-scale environmental assessments. This method provides valuable insights into reservoir evaporation's spatial and temporal patterns, contributing to improved water resource management practices in Texas and other regions facing similar challenges.

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