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.
Highlights
A warmer climate, with its increased climate variability, will increase the risk of both floods and droughts [1], whose management and mitigation are important to protect property, life, and natural environment
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
The DatalogV1 is activated to supply sensor devices and take readings and afterwards it returns to sleep mode
Summary
A warmer climate, with its increased climate variability, will increase the risk of both floods and droughts [1], whose management and mitigation are important to protect property, life, and natural environment. Researchers have directly collected data at the places of interest This has been commonly substituted by automatic sensor and datalogger systems, which provide high temporal data resolution, while reducing operational human resource requirements. 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 [3]. Specific literature on sensor network for flood forecasting is sparse, with only a few examples available (e.g., [4,5,6,7,8])
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