Volume 2, Issue 1, March 2017, Page: 10-18
An Overview of Big Data Applications in Water Resources Engineering
Sirisha Adamala, Applied Engineering Department, Vignan’s Foundation for Science, Technology and Research University (VFSTRU), Vadlamudi, Andhra Pradesh
Received: Jan. 23, 2017;       Accepted: Feb. 7, 2017;       Published: Mar. 1, 2017
DOI: 10.11648/j.mlr.20170201.12      View  2362      Downloads  272
One of the emerging challenges in the 21th century era is collecting and handling ‘Big Data’. The definition of big data changes from one area to other over time. Big data as its name implies is unstructured data that is very big, fast, hard and comes in many forms. Though the applications of big data was confined to information technology before 21st technology, now it is of emerging area in almost all engineering specializations. But for water managers/engineers, big data is showing big promise in many water related applications such as planning optimum water systems, detecting ecosystem changes through big remote sensing and geographical information system, forecasting/predicting/detecting natural and manmade calamities, scheduling irrigations, mitigating environmental pollution, studying climate change impacts etc. This study reviewed the basic information about big data, applications of big data in water resources engineering related studies, advantages and disadvantages of big data. Further, this study presented some of review of literature which has been done on big data applications in water resources engineering.
Big Data, Petabytes, Gigabyte, Water Resources, Climate, Artificial Neural Network, Remote Sensing
To cite this article
Sirisha Adamala, An Overview of Big Data Applications in Water Resources Engineering, Machine Learning Research. Vol. 2, No. 1, 2017, pp. 10-18. doi: 10.11648/j.mlr.20170201.12
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This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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