The backend design of an environmental monitoring system upon real-time prediction of groundwater level fluctuation under the hillslope.

Abstract:

:The groundwater level represents a critical factor to evaluate hillside landslides. A monitoring system upon the real-time prediction platform with online analytical functions is important to forecast the groundwater level due to instantaneously monitored data when the heavy precipitation raises the groundwater level under the hillslope and causes instability. This study is to design the backend of an environmental monitoring system with efficient algorithms for machine learning and knowledge bank for the groundwater level fluctuation prediction. A Web-based platform upon the model-view controller-based architecture is established with technology of Web services and engineering data warehouse to support online analytical process and feedback risk assessment parameters for real-time prediction. The proposed system incorporates models of hydrological computation, machine learning, Web services, and online prediction to satisfy varieties of risk assessment requirements and approaches of hazard prevention. The rainfall data monitored from the potential landslide area at Lu-Shan, Nantou and Li-Shan, Taichung, in Taiwan, are applied to examine the system design.

journal_name

Environ Monit Assess

authors

Lin HC,Hong YM,Kan YC

doi

10.1007/s10661-011-1975-0

subject

Has Abstract

pub_date

2012-01-01 00:00:00

pages

381-95

issue

1

eissn

0167-6369

issn

1573-2959

journal_volume

184

pub_type

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