[A-CG42] Water and sediment dynamics from land to coastal zones

[ACG42-08] Data Assimilation for Estimating Human-Regulated River Flow Dynamics

*Menaka Revel¹, Julien Eric Boulange², Dai Yamazaki¹, Naota Hanasaki³ (1.The University of Tokyo, 2.Tokyo University of Agriculture and Technology, 3.National Institute for Environmental Studies)

Keywords:Data Assimilation, Satellite Altimetry, Human Water Use

Water management in large river systems has become an increasingly complex issue in recent years due to the growing demand for water resources and the need to maintain healthy aquatic ecosystems. Representing human water usage in numerical models has been challenging due to the dynamic nature of water usage and the complexity of water management practices. In this context, data assimilation has emerged as a promising tool for improving our understanding of human-regulated flow dynamics in large rivers. In this study, we present a method for estimating human-regulated flow dynamics in large rivers using data assimilation. We utilize virtual SWOT (Surface Water and Ocean Topography) observations in combination with a numerical model and a data assimilation approach using adaptive empirical localization. The adaptative empirical localization method was developed considering dam location. Our results demonstrate that discharge estimation is significantly improved in river basins regulations were applied on seasonality of water rather than on the magnitude. The method provides a robust framework for integrating virtual observations into models, thereby improving our understanding of human-regulated flow dynamics in large rivers. The proposed method provides a promising tool for water resource management, helping decision-makers to better understand the impact of human water usage on large river systems and to develop more effective water management strategies.