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Big data and hydroinformatics

机译：大数据与水信息学

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摘要

Big data is popular in the areas of computer science, commerce and bioinformatics, but is in an early stage in hydroinformatics. Big data is originated from the extremely large datasets that cannot be processed in tolerable elapsed time with the traditional data processing methods. Using the analogy from the object-oriented programming, big data should be considered as objects encompassing the data, its characteristics and the processing methods. Hydroinformatics can benefit from the big data technology with newly emerged data, techniques and analytical tools to handle large datasets, from which creative ideas and new values could be mined. This paper provides a timely review on big data with its relevance to hydroinformatics. A further exploration on precipitation big data is discussed because estimation of precipitation is an important part of hydrology for managing floods and droughts, and understanding the global water cycle. It is promising that fusion of precipitation data from remote sensing, weather radar, rain gauge and numerical weather modelling could be achieved by parallel computing and distributed data storage, which will trigger a leap in precipitation estimation as the available data from multiple sources could be fused to generate a better product than those from single sources.
机译：大数据在计算机科学，商业和生物信息学领域很流行，但在水信息学处于早期阶段。大数据源自无法使用传统数据处理方法在可容忍的经过时间内进行处理的超大型数据集。使用面向对象编程的类比，应将大数据视为包含数据，其特征和处理方法的对象。水信息学可以从大数据技术中受益，其中包括新出现的数据，技术和分析工具来处理大型数据集，从中可以挖掘创意和新价值。本文对与水信息学相关的大数据进行了及时的回顾。讨论了对降水大数据的进一步探索，因为降水估算是水文学在管理洪水和干旱以及了解全球水循环中的重要组成部分。有望通过并行计算和分布式数据存储实现来自遥感，天气雷达，雨量计和数值天气预报的降水数据融合，这将触发降水估算的飞跃，因为可以融合来自多个来源的可用数据产生比单一来源更好的产品。

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