Large-scale hydrological modeling using the ECHSE* framework - Test of computational concepts and verification of satellite-based precipitation estimates*) Eco-hydrological simulation environment

使用 ECHSE* 框架进行大规模水文建模 - 计算概念测试和卫星降水估算验证*) 生态水文模拟环境

• 批准号: 229163563
• 负责人: Dr. David Kneis
• 金额: --
• 依托单位: Department of Agricultural and Food Engineering
• 依托单位国家: 德国
• 项目类别: Research Fellowships
• 财政年份: 2012
• 资助国家: 德国
• 起止时间: 2011-12-31 至 2012-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/229163563?language=en
• 关键词: Large; scale; hydrological; modeling; using

In the context of the PROGRESS project, the ECHSE hydrological modeling framework has been developed by the applicant. The ECHSE is a generic tool to efficiently create (eco)-hydrological simulation models. So far, the framework has been used to set up rainfall-runoff models for meso-scale river basins. In the proposed project, it is planned to test the usability of an ECHSE-based hydrological model for large-scale applications. Studies are to be conducted in the Mahanadi River Basin, India (approx. 130000 sqkm).The first goal of the proposed project is to gain experience with the application of ECHSE-based hydrological models at large spatial scales. In the focus of interest are the effects of spatial discretization and parallelization on computational efficiency. The planned experiments aim at the identification of possible limits of the ECHSE's generic model core. Another aim is the derivation of guidelines for future large-scale applications and computationally expensive applications in general.The second goal is to study the suitability of precipitation estimates created by merging rain gage information with satellite-based TRMM-3B42 data on a daily basis (TRMM: Tropical Rainfall Measuring Mission). Precipitation estimates are to be verified by cross-validation as well as by analyzing their performance in hydrological modeling. Ideally, a spatially transferable solution for quantitative precipitation estimation in tropical regions with sparse rain gage networks is developed. Such a solution would be of interest to many other projects in practice and research. Rainfall regionalization using spatially continuous co-variables is currently an active field of research.It is envisaged to conduct this study in cooperation with the Indian Institute of Technology at Kharagpur. In particular, collaboration is planned with the group of Prof. R. Singh and C. Chatterjee (Department of Agricultural & Food Engineering). This group is specialized on hydrological modeling, including forecasting. They conducted several studies related to water management in the Mahanadi River basin. Members of the Indian group already visited the applicant's home institute for collaborative research and teaching in recent years.

在PROGRESS项目的背景下，申请人开发了ECHSE水文建模框架。ECHSE是一个通用的工具，有效地创建（生态）水文模拟模型。到目前为止，该框架已被用于建立中尺度流域的整体径流模型。在拟议的项目中，计划测试基于ECHSE的水文模型在大规模应用中的可用性。研究将在印度Mahanadi河流域进行（约拟议项目的第一个目标是获得在大空间尺度上应用基于ECHSE的水文模型的经验。感兴趣的焦点是空间离散化和并行化对计算效率的影响。计划中的实验旨在确定ECHSE通用模型核心的可能限制。另一个目标是为今后的大规模应用和一般计算费用昂贵的应用制定准则，第二个目标是研究通过将雨量计信息与卫星TRMM-3 B42数据每日合并而产生的降水量估计值的适用性（TRMM：热带降雨测量使命）。降水估计值将通过交叉验证以及分析其在水文建模中的性能来验证。理想情况下，一个空间可转移的解决方案，定量降水估计在热带地区稀疏的雨量计网络。这样的解决方案将在实践和研究中对许多其他项目感兴趣。使用空间连续协变量的降雨区域化目前是一个活跃的研究领域，设想与印度Kharagpur理工学院合作进行这项研究。特别是，计划与R. Singh和C. Chatterjee（农业与食品工程系）。该小组专门从事水文建模，包括预报。他们在Mahanadi河流域进行了几项与水管理有关的研究。近年来，印度小组的成员已经访问了申请人的家乡研究所，进行合作研究和教学。