Sediment particle tracking data for the Carpathian reservoir under climate and land use change scenarios

IF 3.3 3区 地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY
Ewa Szalińska, Paweł S. Hachaj, Monika Szlapa, Paulina Orlińska-Woźniak, Paweł Wilk
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引用次数: 0

Abstract

Although the Carpathian Mts. area is considered as extremely prone to surface erosion which results in capacity loss of the dammed reservoirs, a lack of data to follow details of this process is perceivable. The research of the selected sediment fractions transport tracking was conducted using the capabilities of the digital platform—Macromodel DNS (Discharge-Nutrient-Sea) for the catchment with drinking water reservoir in the Polish part of Western Carpathian. The continuity of sediment transport simulation in two hydrologically different elements of the catchment—the river and the reservoir—was possible due to consolidation of two models in the platform—SWAT (Soil & Water Assessment Tool) and AdH/PTM (Adaptive Hydraulics Model/Particle Tracking Model). The result of those modules' integration was a database for tracking the individual sediment fractions delivered to the reservoir and deposited in specific reservoir zones. The implementation of climate and land use change scenarios allowed additionally to analyse the estimation of those processes in the future. The simulation outcomes consist of daily flows and monthly sediment loads at the reservoir inflow and the individual sediment particle fractions deposition location inside of the reservoir.

Abstract Image

Abstract Image

气候和土地利用变化情景下喀尔巴阡山水库的沉积颗粒跟踪数据
虽然喀尔巴阡山脉地区被认为是极易发生地表侵蚀的地区,而地表侵蚀会导致筑坝水库的库容损失,但可以看出缺乏跟踪这一过程细节的数据。利用数字平台--Macromodel DNS(排水-营养物-海洋)的功能,对西喀尔巴阡山波兰部分有饮用水水库的集水区进行了选定沉积物分馏迁移跟踪研究。由于整合了平台中的两个模型--SWAT(土壤采样;水评估工具)和 AdH/PTM(自适应水力学模型/颗粒跟踪模型),集水区两个不同水文要素(河流和水库)的沉积物迁移模拟得以连续进行。这些模块的集成结果是建立了一个数据库,用于跟踪运往水库并沉积在特定库区的各部分沉积物。气候和土地利用变化情景的实施还有助于分析对未来这些过程的估计。模拟结果包括水库流入口的日流量和月沉积物负荷,以及水库内部沉积物颗粒的各个沉积位置。
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来源期刊
Geoscience Data Journal
Geoscience Data Journal GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
5.90
自引率
9.40%
发文量
35
审稿时长
4 weeks
期刊介绍: Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered. An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices. Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.
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