Global lakes depth-area-volume relationship with 0.1m resolution

Our research presents comprehensive approaches to modeling the depth-area-storage relationships of over 1.4 million global water bodies with a high accuracy of 0.1 meters. It addresses critical ecological challenges exacerbated by human activities, like climate change and industrial impacts on freshwater systems. The study employs a dual methodology, combining polynomial equations (first to fifth order) and a power function, offering representations of area, depth, and volume relationships in water bodies. Our advanced approaches enhance the precision in predicting water bodies’ bathymetric dynamics, crucial for ecological modeling and sustainable water management. The research's significant contribution lies in laying the foundation for advanced hydrodynamic and water quality models, important for monitoring and predicting ecological changes in freshwater ecosystems.本研究针对全球超过140万个水体，构建了深度-面积-蓄水量关系的综合建模方案，建模精度可达0.1米。本研究旨在解决人类活动加剧的关键生态难题，其中包括气候变化与工业活动对淡水生态系统造成的负面影响。研究采用双轨建模方法，结合一阶至五阶多项式方程与幂函数，实现水体面积、深度与体积三者关系的精准表征。本研究的先进建模方案大幅提升了水体水深动态变化的预测精度，而该精度对于生态建模与可持续水资源管理均具有关键价值。本研究的核心贡献在于为先进水动力学模型与水质模型奠定了坚实基础，此类模型对于监测与预测淡水生态系统的生态变化至关重要。

搜集汇总

背景与挑战

背景概述

该数据集提供了全球超过140万个水体的深度-面积-体积关系模型，精度高达0.1米，采用多项式方程和幂函数双方法进行建模。它旨在解决气候变化和人类活动引发的淡水生态挑战，为水动力和水质模型提供基础，支持生态建模和可持续水资源管理。