利用新的高分辨率排水数据推进非洲的水安全。

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Komlavi Akpoti, Naga Manohar Velpuri, Naoki Mizukami, Stefanie Kagone, Mansoor Leh, Kirubel Mekonnen, Afua Owusu, Primrose Tinonetsana, Michael Phiri, Lahiru Madushanka, Tharindu Perera, Paranamana Thilina Prabhath, Gabriel E L Parrish, Gabriel B Senay, Abdulkarim Seid
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引用次数: 0

摘要

VegDischarge v1 覆盖非洲 64,000 多条河段,是通过耦合建模(农业水文 VegET 模型和 mizuRoute 路由模型,2001-2021 年)生成的自然河流排水数据集。利用遥感数据和水文建模系统,使用 mizuRoute 对 VegET 模拟的 1 公里径流场进行了路由。性能指标显示模型可靠性很高,在大陆尺度上,R²为 0.5-0.9,NSE 为 0.6-0.9,KGE 为 0.5-0.8。非洲的年均总排水量为 3271.4 千米³年-1,其中流入大洋盆地的水量为:流入北大西洋的水量为 1000.0 千米³年-1,主要来自塞内加尔河、冈比亚河、沃尔特河和尼日尔河;流入南大西洋的水量为 1327.2 千米³年-1,主要来自刚果河;流入地中海的水量为 214.7 千米³年-1,主要来自尼罗河;流入印度洋的水量为 729.4 千米³年-1,来自赞比西河等河流。该数据集对于利益相关者和研究人员了解水的可用性、影响与水有关的基础设施规划的时间和空间变化、可持续资源分配以及气候适应性战略的制定非常有价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advancing water security in Africa with new high-resolution discharge data.

VegDischarge v1, which covers over 64,000 river segments in Africa, is a natural river discharge dataset produced by coupled modeling; the agro-hydrologic VegET model and the mizuRoute routing model for the period 2001-2021. Using remote sensing data and hydrological modeling system, the 1-km runoff field simulated by VegET, was routed with mizuRoute. Performance metrics show strong model reliability, with R² of 0.5-0.9, NSE of 0.6-0.9, and KGE of 0.5-0.8 at the continental scale. The total average annual discharge for Africa is quantified at 3271.4 km³·year-1, with contributions to oceanic basins: 1000.0 km³·year-1 to the North Atlantic, primarily from the Senegal, Gambia, Volta, and Niger Rivers; 1327.2 km³·year-1 to the South Atlantic, largely from the Congo River; 214.7 km³·year-1 to the Mediterranean Sea, predominantly from the Nile River; and 729.4 km³·year-1 to the Indian Ocean, with inputs from rivers such as the Zambezi. The dataset is valuable for stakeholders and researchers to understand water availability, its temporal and spatial variations that affect water-related infrastructure planning, sustainable resource allocation, and the development of climate resilience strategies.

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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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