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CAMELS-BR: hydrometeorological time series and landscape attributes for 897 catchments in Brazil

机译:骆驼-BR:巴西897集水区的水矫脉时间序列和景观属性

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We introduce a new catchment dataset for large-sample hydrological studies in Brazil. This dataset encompasses daily time series of observed streamflow from 3679 gauges, as well as meteorological forcing (precipitation, evapotranspiration, and temperature) for 897 selected catchments. It also includes 65 attributes covering a range of topographic, climatic, hydrologic, land cover, geologic, soil, and human intervention variables, as well as data quality indicators. This paper describes how the hydrometeorological time series and attributes were produced, their primary limitations, and their main spatial features. To facilitate comparisons with catchments from other countries, the data follow the same standards as the previous CAMELS (Catchment Attributes and MEteorology for Large-sample Studies) datasets for the United States, Chile, and Great Britain. CAMELS-BR (Brazil) complements the other CAMELS datasets by providing data for hundreds of catchments in the tropics and the Amazon rainforest. Importantly, precipitation and evapotranspiration uncertainties are assessed using several gridded products, and quantitative estimates of water consumption are provided to characterize human impacts on water resources. By extracting and combining data from these different data products and making CAMELS-BR publicly available, we aim to create new opportunities for hydrological research in Brazil and facilitate the inclusion of Brazilian basins in continental to global large-sample studies. We envision that this dataset will enable the community to gain new insights into the drivers of hydrological behavior, better characterize extreme hydroclimatic events, and explore the impacts of climate change and human activities on water resources in Brazil. The CAMELS-BR dataset is freely available at https://doi.org/10.5281/zenodo.3709337 (Chagas et al., 2020).
机译:我们介绍了巴西大型水文研究的新集水区数据集。该数据集包括从3679张仪表中观察到的流出的日常时间序列,以及897个选定的集水区的气象迫使(降水,蒸发和温度)。它还包括65个属性,涵盖一系列地形,气候,水文,陆地覆盖,地质,土壤和人为干预变量,以及数据质量指标。本文介绍了如何产生水样时间序列和属性,其主要限制及其主要空间特征。为了促进与其他国家的集群的比较,数据遵循与前一群骆驼(集水属性和大型研究)的标准相同的标准,用于美国,智利和英国的美国数据集。 Camels-Br(巴西)通过在热带地区和亚马逊雨林中提供数百个集水区的数据来补充其他骆驼数据集。重要的是,使用若干网格产品评估沉淀和蒸散性不确定性,并提供了对水资源的人类影响的耗水量的定量估计。通过从这些不同的数据产品中提取和组合数据并将骆驼 - BR公开提供,我们的目的是为巴西的水文研究创造新的机会,并促进在大陆纳入全球大型研究中的巴西盆地。我们设想,此数据集将使社区能够进入水文行为驱动程序,更好地表征极端水平事件的新见解,并探讨气候变化和人类活动对巴西水资源的影响。骆驼-BR数据集在HTTPS://doi.org/10.5281/zenodo.3709337(Chagas等,2020)上免费提供。

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