ISSN 1424-8220 www.mdpi.com/journal/sensors Article
A Real-Time Measurement System for Long-Life Flood Monitoring and Warning Applications Rafael Marin-Perez 1, , Javier Garc´a-Pintado 2,3 and Antonio Skarmeta G´ mez 1 ı o 1
Department of Information and Communication Engineering, University of Murcia, Campus de Espinardo, E-30100, Murcia, Spain; E-Mail: email@example.com 2 Euromediterranean Water Institute, Campus de Espinardo, E-30100, Murcia, Spain; E-Mail: firstname.lastname@example.org 3 National Centre for Earth Observation, University of Reading, Harry Pitt Building, 3 Earley Gate, Whiteknights, Reading RG6 6AL, UK Author to whom correspondence should be addressed; E-Mail: email@example.com.
Received: 7 February 2012; in revised form: 14 March 2012 / Accepted: 22 March 2012 / Published: 28 March 2012
Abstract: A ﬂood warning system incorporates telemetered rainfall and ﬂow/water level data measured at various locations in the catchment area. Real-time accurate data collection is required for this use, and sensor networks improve the system capabilities. However, existing sensor nodes struggle to satisfy the hydrological requirements in terms of autonomy, sensor hardware compatibility, reliability and long-range communication. We describe the design and development of a real-time measurement system for ﬂood monitoring, and its deployment in a ﬂash-ﬂood prone 650 km2 semiarid watershed in Southern Spain. A developed low-power and long-range communication device, so-called DatalogV1, provides automatic data gathering and reliable transmission. DatalogV1 incorporates self-monitoring for adapting measurement schedules for consumption management and to capture events of interest. Two tests are used to assess the success of the development. The results show an autonomous and robust monitoring system for long-term collection of water level data in many sparse locations during ﬂood events. Keywords: real-time data acquisition; sensor network; hydrological monitoring; ﬂood warning system
Sensors 2012, 12 1. Introduction
A warmer climate, with its increased climate variability, will increase the risk of both ﬂoods and droughts , whose management and mitigation are important to protect property, life, and natural environment. Real-time accurate monitoring of hydrologic variables is key for ﬂood forecasting, as well as for optimizing related warning systems for damage mitigation. Recent studies show that in the speciﬁc case of semiarid and arid areas, adequate deployment of monitoring networks is essential to a real understanding of the underlying processes generating run-off in storm events, and to achieve effective emergency systems (e.g., ). Traditionally, researchers have directly collected data at the places of interest. This has now been commonly substituted by automatic sensor and datalogger systems, which provide high temporal data resolution, while reducing operational human resource requirements. Dataloggers permit local automatic and unattended data gathering, and reduce environmental perturbation. However, data retrieval from standard dataloggers and storage in processing and control/warning centers still has to be done either manually, which prevents its applicability in ﬂood warning systems, or through wired connections, which leads to substantial investments and operational costs. To confront these problems, sensor network technology has been proposed in many monitoring applications . Yet, speciﬁc literature on sensor network for ﬂood forecasting is sparse, with only a few examples available (e.g., [4–8]). Basically, a sensor network comprises a set of nodes, where each node includes a processor, a wireless radio module, a power supply, and is equipped with sensor hardware to capture environmental data. Each node performs the tasks of data gathering, physical parameter processing, and wireless data transmission to...