prime-HYD - High Mountain Asian HYDrological variability

prime-HYD - 高山亚洲水文变率

• 批准号: 367416348
• 负责人: Professor Paolo Reggiani, Ph.D.
• 金额: --
• 依托单位: Lehrstuhl Wasserwirtschaft
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2017
• 资助国家: 德国
• 起止时间: 2016-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/367416348?language=en
• 关键词: prime; HYD; Mountain; Asian; HYDrological

Precipitation is one of the most important climate elements linking complex atmospheric processes with the hydrological cycle, snow cover and mass balances of glaciers and ice caps. Precipitation is also a key variable for water resource management and natural disaster prevention and mitigation such as floods and droughts. This holds particularly true for the study region of the proposed project bundle PRIME, which encompasses High Mountain Asia (HMA), i.e., the Tibetan Plateau (TP) and its surrounding high-mountain ranges. Research within PRIME aims at generating and validating improved gridded precipitation data sets relying on new remote sensing (RS) information and advanced limited-area atmospheric modeling for the HMA, known as HAR* (i). The project bundle subsequently investigates spatial and temporal patterns, region-specific large-scale drivers and meso- to local-scale processes controlling precipitation variability (ii). The improved accuracy and enhanced knowledge on precipitation type and variability enhances the understanding of spatial and temporal variations of the regional hydrological cycle, including ice mass balances, seasonal snow cover fluctuations and surface water storage in different sub-regions of High Asia (iii). The sub-project PRIME-HYD in particular focusses on the surface water cycle and how it is affected by precipitation and temperature variability. To this end two test bed basins in HMA are selected: the endorheic Pangong lake basin (1) at and the Upper Brahmaputra basin (2), both originating in close proximity on the TP. A distributed hydrological model is set up for both basins which includes an ice and snow simulation component. The model is driven by a downscaled probabilistic precipitation product that is obtained through combined Bayesian processing of RS precipitation and limited area atmospheric model output, conditioned on ground observations. RS temperature and 2m air temperature from HAR* simulations, which is necessary for ice and snowpack simulations, will be processed analogously. Once the hydrologic model has been calibrated and validated in terms of snow cover extension and flow rates over a selected time window, it is used to study the propagation of sub-decadal scale atmospheric forcing variability through the surface water cycle and its effects on river flow rates and lake level dynamics on the TP. The hydrologic signals will be analyzed in the frequency domain to detect potential variability patterns. Importantly, the study also delivers one of the first ground-validated hydrological models for to date scientifically underexplored drainage basins on the TP. The ground observations will be obtained through association of the Chinese Ministry of Water Resources with the project.

降水是最重要的气候要素之一，它将复杂的大气过程与水文循环、积雪以及冰川和冰帽的物质平衡联系起来。降水量也是水资源管理以及预防和减轻洪水和干旱等自然灾害的一个关键变量。这对于拟议项目包PRIME的研究区域尤其如此，该项目包包括亚洲高山地区（HMA），即，青藏高原（TP）及其周围的高山山脉。PRIME内的研究旨在生成和验证改进的网格化降水数据集，这些数据集依赖于新的遥感（RS）信息和HMA的高级有限区域大气建模，称为HAR*（i）。该项目包随后调查空间和时间模式，区域特定的大尺度驱动程序和中尺度到地方尺度的过程控制降水变化（二）。准确性的提高和对降水类型和变异性的了解的增加，有助于加深对区域水文循环的时空变化的了解，包括对高亚洲不同次区域的冰量平衡、季节性积雪波动和地表水储存的了解㈢。 子项目PRIME-HYD特别关注地表水循环以及它如何受到降水和温度变化的影响。为此，选择了HMA中的两个试验床盆地：内流的班公湖盆地（1）和雅鲁藏布江上游盆地（2），两者都起源于TP附近。分布式水文模型建立了两个流域，其中包括冰雪模拟组件。该模型是由一个降尺度的概率降水产品，通过结合贝叶斯处理的RS降水和有限区域大气模型输出，地面观测条件下获得。将类似地处理来自HAR* 模拟的RS温度和2 m空气温度，这是冰和积雪模拟所必需的。一旦水文模型已被校准和验证在选定的时间窗口的积雪覆盖范围和流量，它被用来研究传播的亚十年尺度大气强迫变率通过地表水循环和其对河流流量和湖泊水位动态的TP的影响。水文信号将在频域中进行分析，以检测潜在的变化模式。重要的是，这项研究还提供了第一个地面验证的水文模型，迄今为止，科学上未充分勘探的流域TP。地面观测将通过中国水利部与该项目的合作获得。