GLOBathy全球湖泊水深数据集

水体（天然湖泊和水库）是流域生态和水文平衡的关键组成部分，在许多情况下，通过自然减弱或可控控制决定下游河流的流量。研究水体动力学主要依赖于理解其形态和地球物理特征，这些主要由水深测量决定。水深条件定义了水体中的阶段-储存关系以及环流/输运过程。然而，由于缺乏水深测量数据，许多研究过于简化了这些机制。我们开发了一个新的GLObal水深测量（GLOBathy）数据集，涵盖140万+个水体，以与成熟的全球数据集HydroLAKES保持一致。GLOBathy利用基于GIS的框架，基于水体的最大深度估计和HydroLAKES的几何/地球物理属性生成水深测绘图。最大深度估计在1503个水体中进行了验证，利用多个观测数据源。我们还根据GLOBathy数据集的水深图，提供HydroLAKES水体水头-面积-体积（h-A-V）关系估计。h-A-V关系为全球水体系统的水平衡和水文研究提供了重要信息。GLOBathy水深图的栅格文件，采用TIFF格式存储，每个水体单独成图，分辨率为1角秒，基于WGS84坐标系。

Water bodies (natural lakes and reservoirs) are key components of watershed ecological and hydrological balance, and in many cases determine downstream river flow through natural attenuation or controlled regulation. Research into water body dynamics primarily relies on understanding their morphological and geophysical characteristics, which are mainly determined by bathymetric surveys. Bathymetric conditions define the stage-storage relationships and circulation/transport processes within water bodies. However, due to the lack of bathymetric survey data, many studies have oversimplified these mechanisms. We developed a new Global Bathymetry (GLOBathy) dataset covering over 1.4 million water bodies, which is consistent with the mature global HydroLAKES dataset. GLOBathy uses a GIS-based framework to generate bathymetric maps based on maximum depth estimates of water bodies and the geometric and geophysical properties of HydroLAKES. Maximum depth estimates were validated across 1,503 water bodies using multiple observational data sources. We also provide estimates of the head-area-volume (h-A-V) relationships for HydroLAKES water bodies based on the bathymetric maps from the GLOBathy dataset. The h-A-V relationships provide critical information for water balance and hydrological studies of global water body systems. The raster files of GLOBathy bathymetric maps are stored in TIFF format, with each water body mapped individually, at a resolution of 1 arc-second and based on the WGS84 coordinate system.

搜集汇总

背景与挑战

背景概述

GLOBathy全球湖泊水深数据集是一个覆盖全球140多万个水体的水深测量数据集，基于HydroLAKES数据集和随机森林回归模型生成，并以1弧秒分辨率的TIFF格式存储。该数据集为全球水系统的水平衡和水文学研究提供了重要信息。