Coupling a physically-based, spatially distributed hydrological model with an Open Data Cube (ODC) ...
Coupling a physically-based, spatially distributed hydrological model with an Open Data Cube (ODC) ...
批准号:
2435741
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2020
资助国家:
英国
项目状态:
未结题
起止时间:
2020 至 --
中文摘要
标题:将基于物理的、空间分布的水文模型与开放数据立方体(ODC)生态系统相结合,作为数据储存库和分析工具,以量化气候变化对水安全的影响。对于全球许多地区,基于物理的水文模型具有基础作用,有助于为未来的气候变化适应和准备制定全面而稳健的计划,为水管理和洪水倡议提供信息,并增强对当地和区域水文过程的了解。虽然基于物理的水文模型的使用受到过程性质的限制,即所需的数据量和计算资源更大(Lewis等人,2018年),但在卫星衍生分析就绪数据(ARD)可用性和计算环境(在线和本地部署)方面的最新进展已成为这些模型更广泛使用的催化剂(Sun等人,2019年,Saran等人,2021年)。这项研究的目的是通过应用开放数据立方体项目(https://www.opendatacube.org)与SHETRAN模型(Ewen等人,2000年)利用免费提供的计算环境(JupyterHub)提供的开放和免费提供的地球观测卫星数据结构),研究气候变化对水安全的影响。
英文摘要
TITLE: Coupling a physically-based, spatially distributed hydrological model with an Open Data Cube (ODC) ecosystem as data repository and analysis tool to quantify the impacts of climate change in water security.For many areas across the globe physically-based hydrological models have a fundamental role helping devise a comprehensive and robust plan for future climate change adaption and preparedness, informing water management and flood initiatives, as well as enhancing knowledge of local and regional hydrological processes. Whilst the use of physically-based hydrological models have been restricted by the nature of the process i.e. large data volumes and greater computational resources required (Lewis et at., 2018), recent advances on satellite derived analysis ready data (ARD) availability and computational environments (online and local deployments) have served as catalyst to a wider use of these models (Sun et al., 2019, Saran et al., 2021).In this context, this research has the purpose to examine the effects of climate change on water security through the application of the open and freely available earth observation satellite data architecture made available by the Open Data Cube project (https://www.opendatacube.org) in conjunction with the SHETRAN model (Ewen et al., 2000) utilising a freely available computation environment (JupyterHub). This research will be expected to contribute towards the implementation and adaptation strategies of the Sustainable Development Goals (SDG's), in particular SDG 6 (clean water and sanitation), SDG 11 (Sustainable cities and communities) and SDG 13 (climate action).
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