An observational and modeling study of energy, water, and carbon transport in eco-hydro-meteorological systems

• Main Author: Zhu, Modi
• Other Authors: Wang, Jingfeng, Georgakakos, Aris, Luo, Jian, Deng, Yi, Liu, Heping, Civil and Environmental Engineering
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: Georgia Institute of Technology 2024
• Subjects: Energy Transport; Water Transport; Carbon Transport; Non-gradient Models; In-situ Field Observations; Machine Learning Methods; permafrost
• Online Access: https://hdl.handle.net/1853/73205

Eco-hydro-meteorological systems play a critical role in regulating the Earth's energy, water, and carbon cycles. Understanding the physical mechanisms driving ecosystem functioning is essential for predicting and mitigating the impacts of global environmental change. The primary objective of this study is to understand the complex mechanisms and interactions that govern the transport of energy, carbon, and water in various eco-hydro-meteorological systems. However, the mechanisms in different eco-hydro-meteorological systems are quite different. This study, by employing a blend of observational data and modeling techniques, investigates the physical transportation of energy, water, and carbon within diverse ecosystems --forest, permafrost, and lake --each with its distinct mechanisms, and develops a comprehensive understanding of how these ecosystems function and respond to environmental changes. In the observational phase, data is gathered using flux towers that measure the exchange of energy, water, and carbon between the Earth's surface and the atmosphere. Datasets from multiple flux towers across forest, permafrost, and lake ecosystems are scrutinized to discern patterns and drivers of eco-hydro-meteorological system processes. The observations have revealed the differences of how energy, water, and carbon are transported in different eco-hydro-meteorological systems and the importance of further study. In the modeling phase, the past traditional models of energy, water, and carbon transport of eco-hydro-meteorological systems have been carefully reviewed. The non-gradient models are widely applied in modeling the meteorological processes in recent decades. This study utilizes Maximum Entropy Production (MEP) Model and Half-order Derivative (HOD) Methods together with newly proposed inference models to simulate the eco-hydro-meteorological processes, which yielded consistent results compared to field experiments. Overall, this study has significant implications for our understanding of how ...